Archive

Abstract:

This study applies a Max-Plus algebra-based model to optimize traffic signal timing and enhance intersection efficiency in urban settings, with a case study conducted at the Pejanggik–Bung Hatta intersection in Mataram, Indonesia. Primary data, including signal durations and traffic density, were gathered through direct field observations. A directed graph was developed to represent traffic movements and potential conflicts, after which the Welch-Powell algorithm and Max-Plus algebra were applied to design a synchronized and periodic signal schedule. The optimized system successfully reduced the total traffic light cycle time from 525 to 375 seconds, maintaining an equitable distribution of green times and achieving a 28.57% improvement in efficiency. An eigenvalue of 75 seconds was obtained, indicating a stable and recurring timing cycle. These results demonstrate the practical utility of the Max-Plus approach in managing urban traffic, offering a cost-effective and mathematically robust strategy to alleviate congestion and promote sustainable transportation planning. The methodology is adaptable to other intersections experiencing similar traffic issues and provides valuable guidance for policymakers and urban traffic engineers in developing responsive and inclusive traffic control solutions.

Keywords:

Max-Plus Algebra,Mataram City,Urban Traffic,Sustainable Cities,

Refference:

I. A. A. Aminu, S. E. Olowo, I. M. Sulaiman, N. Abu Bakar, M. Mamat: ‘On application of max-plus algebra to synchronized discrete event system’. Math. Stat., 2021, 9(2), 81-92. 10.13189/ms.2021.090201
II. A. E. S. H. Maharani, A. Suparwanto: ‘Application of system max-plus linear equations on serial manufacturing machine with storage unit’. BAREKENG: J. Math. Appl. Sci., 2022, 16(2), 525-530. 10.30598/barekengvol16iss2pp525-530.
III. B. Heidergott, G. J. Olsder, J. van der Woude: ‘Max Plus at Work Modeling and Analysis of Synchronized Systems: A Course on Max-Plus Algebra and Its Applications’. De Gruyter Brill, 2006.
IV. D. Dubey, S. K. Neogy, S. Sinha: ‘Max plus algebra, optimization and game theory’. Mathematical Analysis and Applications in Modeling, 2020, 302, 345-361.
V. D. Li, J. Wu, M. Xu, Z. Wang, K. Hu: ‘Adaptive Traffic Signal Control Model on Intersections Based on Deep Reinforcement Learning’. J. Adv. Trans., 2020, 6505893, 1-14. 10.1155/2020/650589
VI. E. Carnia, R. Wilopo, R. Napitupulu, N. Anggriani, A. K. Supriatna: ‘Modified Kleene star algorithm using max-plus algebra and its application in the railroad scheduling graphical user interface’. MDPI: Computation, 2023, 11(1), 11. 10.3390/computation11010011
VII. E. Joelianto, H. Y. Sutarto, D. G. Airulla, M. Zaky: ‘Design and simulation of traffic light control system at two intersections using max-plus model predictive control’. Int. J. Artif. Intell., 2020, 18(1), 97-116.
VIII. F. Baccelli, G. Cohen, G. J. Olsder, J-P. Quadrat: ‘Synchronization and Linearity: An Algebra for Discrete Event Systems’. Wiley, New York, 1992.
IX. F. S. Schanzenbächer: ‘Max-plus modeling of traffic on passenger railway lines with a junction: fundamental diagram and dynamic control’. PhD Thesis (2020). 10.48550/arXiv.2010.12992.
X. G. P. T. Hanefa, Siswanto: ‘Petri net model and max-plus algebra in outpatient care at Solo Peduli Clinic, Surakarta’. J. Phys.: Conf. Ser., 2021, 1776, 012047. 10.1088/1742-6596/1776/1/012047.
XI. H. Zaher, H. A. Khalifa, A. Ahmed: ‘Fuzzy max plus algebra algorithm for traffic problems’. Int. J. Emerg. Technol. Eng. Res., 2019, 7(11), 530-535. 0.30534/ijeter/2019/217112019
XII. I. O. Olayode, L. K. Tartibu, M. O. Okwu, U. F. Uchechi: ‘Intelligent transportation systems, un-signalized road intersections and traffic congestion in Johannesburg: a systematic review’. Procedia CIRP, 2020, 91, 844-850. 10.1016/j.procir.2020.04.137.
XIII. J. Komenda, S. Lahaye, J-L. Boimond, T. van den Boom: ‘Max-plus algebra in the history of discrete event systems’. Annu. Rev. Control., 2018, 45, 240-249. 10.1016/j.arcontrol.2018.04.004.
XIV. J.-P. Quadrat: ‘Max-plus algebra and applications to system theory and optimal control’. Proc. Int. Congress Math., 1995, 1511–1522. 10.1007/978-3-0348-9078-6_148.
XV. K. Fahim, K. Subiono, J. van der Woude: ‘On a generalization of power algorithms over max-plus algebra’. Discrete Event Dynamic Systems, 2017, 27, 181-203. 10.1007/s10626-016-0235-4.
XVI. M. I. D. Firmansyah, M. S. Mufid, Subiono, B. Davvaz: ‘Disordered discrete-time quantum walk over max-plus algebra’. Discrete Event Dynamic Systems, 2025, 35, 1–21. 0.1007/s10626-025-00409-6
XVII. M. U. Romdhini, A. Nawawi, F. Al-Sharqi, A. Al-Quran, S. R. Kamali: ‘Wiener-Hosoya energy of non-commuting graph for dihedral groups’. Asia Pac. J. Math., 2024, 11(9), 1-9. 10.28924/APJM/11-9.
XVIII. M. U. Romdhini, A. Nawawi, B. N. Syechah: ‘Seidel Laplacian and Seidel signless Laplacian energies of commuting graph for dihedral groups’. Mal. J. Fund. Appl. Sci., 2024, 20(3), 701–713. 10.26554/sti.2025.10.3.
XIX. P. Butkovic: ‘Max-linear Systems: Theory and Algorithms’. Springer, 2010.
XX. R. U. Hurit, A. Rudhito: ‘Max-plus algebraic modeling of three crossroad traffic queue systems with one underpass’. J. Phys.: Conf. Ser., 2019, 1307, 012013. 10.1088/1742-6596/1307/1/012013.
XXI. S. Watanabe, A. Fukuda, E. Segawa, I. Sato: ‘A walk on max-plus algebra’. Linear Algebra Appl., 2020, 598, 29–48. 10.1016/j.laa.2020.03.025
XXII. T. J. J. van den Boom, B. De Schutter: ‘Analytic expressions in stochastic max-plus-linear algebra and their application in model predictive control’. IEEE Trans. Automat. Control, 2021, 66(4), 1872-1878. 10.1109/TAC.2020.2997851.
XXIII. T. Sulistyaningsih, Siswanto, Pangadi: ‘Petri net model and max-plus algebra on queue in clinic UNS Medical Center’. J. Phys.: Conf. Ser., 2020, 1494, 012004. 10.1088/1742-6596/1494/1/012004.
XXIV. Z. Liu: ‘A novel model for train operation adjustment in high-speed railway based on max-plus algebra’. Int. J. Circuits Syst. Signal Process., 2020, 14, 881-887. 10.46300/9106.2020.14.114.
XXV. Z. Sya’diyah: ‘Max plus algebra of timed petri net for modeling single server queuing systems’. BAREKENG: J. Math. Appl. Sci., 2023, 17(1), 0155-0164.

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Abstract:

In today's volatile business environment, brand resilience is crucial for survival. Drawing inspiration from the resilient termite mounds found in Africa, this paper proposes a Termite Framework for building sustainable brand resilience. The framework consists of five pillars: Resilience, Adaptation, Cooperation, Resourcefulness, and Endurance (RACRE). Most brands in Africa fade and disappear in the market within a short period of time. It is with great concern that Africa needs to build brand resilience to meet globalisation changes for sustainability. The environment is DVUCADD, meaning it is dynamic, volatile, uncertain, complex, ambiguous, diverse, and disruptive. There is an imminent need for brand resilience. This study proposed a model framework focusing on termite behaviour. Resilient brands are adaptive, change direction, take knocks and setbacks, and come back stronger. These brands can easily extend to new products, take their customers with them, and take on new business models. Main characteristics of resilient brands are setting goals and priorities, having a strategy, working together, uncovering new threats proactively, regrouping, and retesting. In retesting and regrouping, resilient brands protect their customers, reputation, and revenue, continually refining their tactics. In this sense, they communicate failures and successes to team members to reevaluate their methodology until the desired results are achieved. These brand resilience characteristics match the life and behaviour of termites. Termites go through a cycle like that of an organisation. Termites are flexible, which is the major characteristic of resilient brands. Agility is the major element in building resilient brands. Termites have teamwork through which they complement each other’s strengths and complement each other’s weaknesses without discrimination. Termite mounds reveal residence, cooperation, resourcefulness, and endurance. We explore each pillar's application in the African context, using observation and literature sources. It is with great emphasis that Africa builds resilient nations, organisations, products and services for continental sustainability in line with economic, social, technological, and ecological aspects, like the termite resilience and cooperation.

Keywords:

Brand resilience,Cooperation,Endurance,Sustainability,Termites,

Refference:

I. Adeola, O. (2021). African Business Resilience in a Disruptive Era. Springer.
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XX. Papadopoulosa, N. and Hamzaoui-Essoussi, L. (2015) ‘Place Images and Nation Branding in the African Context: Challenges, Opportunities, and Questions for Policy and Research’, Africa Journal of Management.
XXI. Radic, M., Herrman, P., Haberland, P., and Riese, C.R., 2022. ‘Development of a Business Model Resilience Framework for Managers and Strategic Decision-Makers’, Schmalenbach Journal of Business Research, Vol. 74, pg. 575-601.
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XXIII. Mwangi, P. (2020). Strategic partnerships and organizational resilience: A case study of Safaricom’s mobile money ecosystem. Journal of Business and Management, 15(2), 123-138.
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XXVI. The Zimbabwe Mail, (2024). ‘Zimbabwe’s Retail Sector Faces Crisis as Prominent Brands Near Bankruptcy’, The Zimbabwe Mail. November 15, https://www.thezimbabwemail.com/business/zimbabwes-retail-sector-faces-crisis-as-prominent-brands-near-bankruptcy/.
XXVII. Turner, R. (2019). Termites as ecosystem engineers. Journal of Insect Science, 19(4), 761-774.

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Abstract:

This article presents a study of the mechanical properties of geopolymer concrete reinforced with steel rebar and polyester fibers and compares their performance under different loading conditions. Geopolymer concrete, known for its environmental benefits due to its low CO₂ emissions, has been enhanced with micro silica as an activator and sodium silicate to accelerate the curing process. In this study, non-destructive ultrasonic testing (UT) was used to evaluate the compressive strength, dynamic and static Young's modulus, shear modulus, and pore characteristics. Steel rebar is more suitable for applications requiring high load-bearing capacity, but polyester fibers increase the ductility and resistance of geopolymer concrete to sudden failure by absorbing more energy. The optimum content of polyester fibers is 6%, which ensures the highest flexural load (10,080 kN) and displacement (2.6 mm). Failure analysis revealed shear cracks in samples with steel rebar and vertical cracks in polyester fiber-reinforced samples, indicating different failure mechanisms. The study highlights the trade-off between flexural load and ductility, providing insights for individual applications in sustainable construction. The SADRA algorithm and UT methods have proven their effectiveness in predicting mechanical properties, confirming the potential of geopolymer composites in modern engineering.

Keywords:

Geopolymer Concrete,Steel Rebar,Polyester Fiber,Ultrasonic Testing,Mechanical Properties,Failure Mechanism,Sustainable Construction,

Refference:

I. Adak D, Sarkar M, Mandal S. (2017). Structural performance of nano-silica modified fly-ash based geopolymer concrete. Construction and Building Materials, 135, 430–439.
II. Adesina A. (2020). Recent advances in the concrete industry to reduce its carbon dioxide emissions. Environmental Challenges, 1, 100004.
III. Ahmed HU, Mohammed AS, Faraj RH, Qaidi SMA, Mohammed AA. (2022). Compressive strength of geopolymer concrete modified with nano-silica: experimental and modeling investigations. Case Studies in Construction Materials, 16, e01036.
IV. Amin M, Elsakhawy Y, Abu el-hassan K, Abdelsalam BA. (2022). Behavior evaluation of sustainable high strength geopolymer concrete based on fly ash, metakaolin, and slag. Case Studies in Construction Materials, 16, e00976.
V. Ashnani MHM, Hasani AM, Hasani E. (2008). A proposal for a comparative assessment process and environmental planning for sustainable rural development in Iran. Journal of Village and Development, 11(1), 77–100.
VI. Assi LN, Deaver E, Elbatanouny MK, Ziehl P. (2016). Investigation of early compressive strength of fly ash-based geopolymer concrete. Construction and Building Materials, 112, 807–815.
VII. Choi W, Jung K, Jang S, Yun H. (2019). The influence of steel fiber tensile strengths and aspect ratios on the fracture properties of high-strength concrete. Materials, 12, 2105.
VIII. De Araujo Thomaz W, Miyaji DY, Possan E. (2021). Comparative study of dynamic and static Young’s modulus of concrete containing basaltic aggregates. Case Studies in Construction Materials, 15, e00645.
IX. Duan P, Yan C, Zhou V. (2017). Compressive strength and microstructure of fly ash based geopolymer blended with silica fume under thermal cycle. Cement and Concrete Composites, 78, 108–119.
X. Esparham A, Vatin NI, Kharun M, Hematibahar M. (2023). A study of modern eco-friendly composite (geopolymer) based on blast furnace slag compared to conventional concrete using the life cycle assessment approach. Infrastructures, 8, 58.
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XII. Hasanzadeh A, Vatin NI, Hematibahar M, Kharun M, Shooshpasha I. (2022). Prediction of the mechanical properties of basalt fiber reinforced high-performance concrete using machine learning techniques. Materials, 15, 7165.
XIII. Hematibahar M, Kharun M, Bhowmik A, Romanovski A. (2025). The SADRA algorithm as a framework for sustainable innovation: a review of case studies on 3D-printed reinforced concrete beam and fiber-reinforced concrete. Engineering Reports, 7, e70208.
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Abstract:

This manuscript aims to formulate an innovative approach based on Cat Mouse Based Optimization (CMBO) integrated with a Hybrid Fast Fuzzy-2-Degree-of-Freedom Fractional-Order Tilt Integral Derivative Controller (CMBO-HFF-2DoF-FOTIDC) aimed at enhancing the performance of Grid-Interfaced Solar Inverter Systems (GISIS) while reducing total harmonic distortion. The proposed solar inverter system comprises several elements, including a photovoltaic array, a Relift Luo Converter (RLC), and a 15-Level Switch-Minimized Multilevel Inverter (15L-SMMI), alongside the CMBO-HFF-2DoF-FOTIDC controller. The choice of the RLC over the others from the category stems from its capability to mitigate parasitic capacitance effects, achieve high efficiency, increase power density, reduce ripple voltage magnitude, and lower duty cycle requirements. This control strategy employs a fuzzy-logic-based, optimized 2DoF fractional-order tilt integral derivative controller (2DoF-FOTIDC). The CMBO algorithm optimizes the controller's parameters. Comparative analysis of the CMBO-HFF-2DoF-FOTIDC controller with other state-of-the-art controllers demonstrates its superior performance and effectiveness. Additionally, the manuscript explores the implementation of the Random Pulse Position Pulse Width Modulation (RPPPWM) method alongside the proposed approach. The proposed GISIS aims to address harmonic distortions reduction, alongside improvements in the performance of the solar inverter, robustness, stability, and enhanced capabilities to deal with system uncertainties.

Keywords:

CMBO-HFF-2DoF-FOTIDC,CMBO,RLC,robustness,15L-SMMI,RPPPWM,

Refference:

I. Abualigah, L., & Gandomi, A. H. Aquila optimizer: a novel meta-heuristic optimization algorithm. Computers & Industrial Engineering, 157(1), 1–25. 2021.
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Abstract:

This paper introduces a next-generation hybrid system for industrial process monitoring and control, integrating advanced statistical process control (SPC) charts with state-of-the-art artificial intelligence (AI) models. By combining robust adaptive charts such as Max-mixed EWMA and Bayesian SPC with deep learning architectures including Transformers, Graph Neural Networks (GNNs), and reinforcement/meta-learning agents, the framework achieves real-time detection, precise diagnosis, and autonomous recovery from process anomalies. Evaluation on a real-world manufacturing dataset demonstrates that the hybrid approach consistently outperforms traditional SPC and standalone neural models across key metrics, including detection delay, false alarm rate, recovery time, and interpretability. The modular architecture allows for flexible extension, human-in-the-loop transparency, and scalable deployment in dynamic, sensor-rich industrial environments. This work sets a new benchmark for smart manufacturing, highlighting the synergistic value of statistical-AI fusion for trustworthy and adaptive quality control.

Keywords:

Artificial Intelligence,Control charts,EWMW,Hybrid Models,

Refference:

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Abstract:

This paper explores certain generalizations of the generating function of Bernoulli numbers, the computation of integrals, and the investigation of the convergence of integrals from these functions. The primary tools employed in the research include the use of Taylor series, theorems on uniform continuity (such as Weierstrass's and Dini's theorems), as well as special functions such as the gamma function, incomplete gamma function, Riemann zeta function, and Lambert function. Various examples for specific parameter values are considered in the article. The obtained results can be strengthened in subsequent works and generalized to a broader class of functions. The derived estimates can be applied in various tasks related to the assessment of similar integrals.

Keywords:

Bernoulli numbers,generating function,Taylor series,uniform convergence,special functions,incomplete gamma function,Riemann zeta function,Lambert function,

Refference:

I. Ding, Xianfeng, Dan Qu, and Haiyan Qiu. (2018). A New Production Prediction Model Based on Taylor Expansion Formula. Mathematical Problems in Engineering. 10.1155/2018/1369639.
II. Kong, Qingkai, Timmy Siauw, and Alexandre M. Bayen. (2021). Chapter 18 – Taylor Series. In Python Programming and Numerical Methods, Academic Press, pp. 315–323. ISBN 9780128195499. 10.1016/B978-0-12-819549-9.00028-2.
III. Kitagawa, T.L. (2022). The Origin of the Bernoulli Numbers: Mathematics in Basel and Edo in the Early Eighteenth Century. Mathematical Intelligencer, 44, pp. 46–56. 10.1007/s00283-021-10072-y.
IV. Li, C. (2022). Taylor Series Expansion and Application in Error Estimate. In Time Series Data Analysis in Oceanography: Applications using MATLAB, Cambridge University Press, pp. 110–129. 10.1017/9781108697101.007.
V. Morse, P.M., and H. Feshbach. (1953). Derivatives of Analytic Functions, Taylor and Laurent Series. § 4.3 in Methods of Theoretical Physics, Part I, McGraw-Hill, pp. 374–398.

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Abstract:

Multi-objective Linear Programming (MOLP) traditionally optimizes multiple conflicting objectives simultaneously. This research extends the De Novo Programming (DNP) concept, which focuses on optimal system design, to situations with uncertainty in resource allocation and budget constraints. A novel mathematical model, Rough Interval Multi-Objective De Novo Programming (RIMODNP), has been introduced. This model incorporates the Rough Interval (RI) concept, where all problem coefficients are represented by lower and upper interval bounds, each having two terms (upper and lower). The study outlines the mathematical formulation of the RIMODNP model, detailing the methodology used to transform its uncertain nature into deterministic sub-problems. It presents two primary approaches, Zeleny's and the Optimum-Path Ratio Method, for finding optimal designs. Applied to the Baghdad Water Department, the model optimizes resource allocation for increased water production, improved water quality, and reduced water loss while considering unknown constraints. The results, obtained by solving the deterministic sub-problems, provide the decision-maker with a range of optimal system designs. The application to the Baghdad Water Department shows significant increases in profit and cost savings across different scenarios, highlighting the model's ability to offer robust and effective solutions under conditions of uncertainty.

Keywords:

De Novo programming,Multi-objective linear programming,Resource allocation,Rough Interval,Tong-Shaoching method,Zeleny Approach,Optimal path-ratios.,

Refference:

I. A. Hamzehee, A. Yaghoobi, and M. Mashinchi, “Linear programming with rough interval coefficients,” J. Intell. Fuzzy Syst., vol. 26, pp. 1179–1189, 2014. 10.3233/IFS-130804.
II. C. Sen, “Sen’s Multi-Objective Optimization (MOO) technique – A review,” Int. J. Mod. Trends Sci. Technol., vol. 6, no. 9, pp. 208–210, 2020. 10.46501/IJMTST060931.
III. H. M. Saad and M. J. Mhawes, “The relationship and impact of the external auditor’s fees on audit quality of financial statements,” Tech. J. Manag. Sci., vol. 2, no. 1, 2025.
IV. I. A. Hussein, H. Zaher, N. Saeid, and H. Roshdy, “A multi-objective de novo programming models: A review,” Int. J. Prof. Bus. Rev., vol. 9, no. 1, pp. 1–22, 2024. 10.26668/businessreview/2023.v9i1.4180 .
V. I. A. Hussein, H. Zaher, N. Saeid, and H. Roshdy, “Optimum system design using rough interval multi-objective de novo programming,” Baghdad Sci. J., vol. 20, no. 4, p. 8740, 2023. 10.21123/bsj.2023.8740.
VI. J. Chen, T. Du, and G. Xiao, “A multi-objective optimization for resource allocation of emergent demands in cloud computing,” J. Cloud Comput., vol. 10, no. 20, pp. 1–17, 2021. 10.1186/s13677-021-00237-7.
VII. M. Allahdadi and M. Nehi, “The optimal value bounds of the objective function in the interval linear programming problem,” Chiang Mai J. Sci., vol. 42, no. 2, pp. 501–511, 2015.
VIII. M. M. Luhandjula and P. Pandian, “A new method for finding an optimal solution of interval integer transportation problems,” Appl. Math. Sci., vol. 4, no. 37, pp. 1819–1830, 2010.
IX. M. Zeleny, “Multiple criteria decision making (MCDM): From paradigm lost to paradigm regained?,” J. Multiple Criteria Decis. Anal., vol. 18, pp. 77–89, 2011. 10.1002/mcda.473.
X. N. K. Bisuiki, S. Mazumader, and G. A. Panda, “Gradient-free method for multi-objective optimization problem,” in Optimization, Variational Analysis and Applications, vol. 355, 2020, pp. 19–34. 10.1007/978-981-16-1819-2_2.
XI. T. Shaocheng, “Interval number and fuzzy number linear programming,” Fuzzy Sets Syst., vol. 66, no. 3, pp. 301–306, 1994. 10.1016/0165-0114(94)90097-3.
XII. W. C. Lo, C. H. Lu, and Y. C. Chou, “Application of multi-criteria decision making and multi-objective planning methods for evaluating metropolitan parks in terms of budget and benefits,” Mathematics, vol. 8, no. 8, pp. 1–17, 2020. 10.3390/math8081304.
XIII. Y. H. Hasan Al-Karawi and H. Ghodrati, “The effect of the source of commitment and ethical style of auditors on independent auditors’ whistle-blowing,” Tech. J. Manag. Sci., vol. 1, no. 1, 2024.
XIV. Y. Shi, “Studies on optimum-path ratios in multi-criteria de novo programming problems,” Comput. Math. Appl., vol. 29, no. 5, pp. 43–50, 1995. 10.1016/0898-1221(94)00247-I.
XV. Z. Y. Zhuang and A. Hocine, “Meta goal programing approach for solving multi-criteria de novo programing problem,” Eur. J. Oper. Res., vol. 265, no. 1, pp. 228–238, 2018. doi: 10.1016/j.ejor.2017.07.035.

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Abstract:

The main focus of this research is the design and simulation of a cable television DTTB SYSTEM THAT IS viewable in a QPSK demodulator, within a Gaussian noise interference channel. QPSK is the industry standard for encoding video signals. It's possible to find practical issues that prevent streaming. This, I would assume, is partially due to Equipment and encoding inconsistencies. For this research, QPSK has been used for encoding. This encoding will be made use as a part of the Gaussian channel for transmission and response. Adaptive equalization, but digital ones are being included to fix deficiency problems such as digital segregation and interference. Whenever data is comprehensively transmitted forth and back, the model forecasts that it would be possible to increase the transmission quality. In Particular, the model ensured a defined BER performance below 1 percent and provided reasonable throughput when SNR was in the range of 15 to 20 decibels. Broadly, the whole system can be divided into three functional blocks, which are the input and output sections (which are, in simpler terms, termed as communication channels) and the last block, which is the modulator block, and in this case, is the QPSK block. So, in a simple quest for this purpose, the system is designed in such a way as to limit the degradation of the received signal due to the presence of noise and interference in the Gaussian channel. Adaptation, or commonly known as equalization, is also the process of channel estimation, where the channel distortion is compensated for. It has improved in the simulation.

Keywords:

Digital Video Broadcasting Communications,Quadrature Phase Shift Key (QPSK) Modulation,Gaussian Interference Channel,Digital Adaptive Equalizers,Throughput,

Refference:

I. Ahn, C., et al. “Implementation of an SDR Platform Using GPU and Its Application to a 2×2 MIMO WiMAX System.” Analog Integrated Circuits and Signal Processing, vol. 69, no. 1, 2011, pp. 107–120. 10.1007/s10470-011-9645-7.
II. Arrano, Hernan F., and Cesar A. Azurdia-Meza. “OFDM: Today and in the Future of Next Generation Wireless Communications.” 2016 IEEE Central America and Panama Student Conference (CONESCAPAN), 2016, pp. 1–6. 10.1109/CONESCAPAN.2016.7815720.
III. Batra, A., et al. “A Massive MIMO Signal Processing Architecture for GHz to THz Frequencies.” Proceedings of the 2018 First International Workshop on Mobile Terahertz Systems (IWMTS), IEEE, 2–4 July 2018, pp. 1–6. 10.1109/IWMTS.2018.8439066.
IV. Batra, A., et al. “A Massive MIMO Signal Processing Architecture for GHz to THz Frequencies.” Proceedings of the 2018 First International Workshop on Mobile Terahertz Systems (IWMTS), IEEE, 2–4 July 2018, pp. 1–6. 10.1109/IWMTS.2018.8439066.
V. Caire, Giuseppe, et al. “Bit-Interleaved Coded Modulation.” IEEE Transactions on Information Theory, vol. 44, no. 3, 1998, pp. 927–946. 10.1109/18.669123.
VI. Chang, Yu-Kuo, and Fu-Berg Ueng. “A Novel Turbo GFDM-IM Receiver for MIMO Communications.” AEU – International Journal of Electronics and Communications, vol. 87, 2018, pp. 22–32. 10.1016/j.aeue.2018.02.011.
VII. Foo, S. “Liquid-Crystal Reconfigurable Metasurface Reflectors.” IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, July 2017, pp. 2069–2070. 10.1109/APUSNCURSINRSM.2017.8072855.
VIII. Gardner, W. A. “Exploitation of Spectral Redundancy in Cyclostationary Signals.” IEEE Signal Processing Magazine. 10.1109/79.366549.
IX. Gokalgandhi, Bhushan, et al. “Accelerating Channel Estimation and Demodulation of Uplink OFDM Symbols for Large Scale Antenna Systems Using GPU.” 2019 International Conference on Computing, Networking and Communications (ICNC), IEEE, 18–21 Feb. 2019, pp. 955–959. 10.1109/ICCNC.2019.8685564.
X. Hasan, W. B., et al. “Real-Time Maximum Spectral Efficiency for Massive MIMO and Its Limits.” IEEE Access, vol. 6, 2018, pp. 46122–46133. 10.1109/ACCESS.2018.2865946.
XI. Hoda, B., and B. Babamir. “Enhancing Efficiency of Software Fault Tolerance Techniques in Satellite Motion System.” Journal of Information Systems and Telecommunication (JIST), vol. 5, no. 20, 2017, pp. 236–241. URL: https://www.jist.ir/article_22595.html.
XII. Ijiga, O. E., et al. “Review of Channel Estimation for Candidate Waveforms of Next Generation Networks.” Electronics, vol. 8, no. 8, 2019, p. 956. 10.3390/electronics8080956.
XIII. Jangir, D., et al. “Performance Analysis of LTE System for 2×2 Rayleigh and Rician Fading Channel.” 2020 International Conference on Smart Electronics and Communication (ICOSEC), 2020, pp. 961–966. 10.1109/ICOSEC49089.2020.9215423.
XIV. Shereen, M. Kamran, et al. “A Brief Review of Frequency, Radiation Pattern, Polarization, and Compound Reconfigurable Antennas for 5G Applications.” Journal of Computational Electronics, vol. 18, 2019, pp. 1065–1102. 10.1007/s10825-019-01369-y.
XV. Liu, Fan, et al. “Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead.” IEEE Transactions on Communications,2020. 10.1109/TCOMM.2020.2973976.
XVI. Luther, Erik. 5G Massive MIMO Testbed: From Theory to Reality. National Instruments, 2014. URL: https://www.ni.com/en-rs/innovations/white-papers/14/5g-massive-mimo-testbed–from-heory-to-reality–.html.
XVII. Malkowsky, Steffen, et al. “The World’s First Real-Time Testbed for Massive MIMO: Design, Implementation, and Validation.” IEEE Access, vol. 5, 2017, pp. 9073–9088. 10.1109/ACCESS.2017.2707539.
XVIII. Mokhtari, Zahra, et al. “A Survey on Massive MIMO Systems in Presence of Channel and Hardware Impairments.” Sensors, vol. 19, no. 1, 2019, p. 164. 10.3390/s19010164.
XIX. Paul, B. S., and R. Bhattacharjee. “MIMO Channel Modeling: A Review.” IETE Technical Review, vol. 25, no. 6, 2008, pp. 315–319. 10.4103/0256-4602.46478.
XX. Qiao, Guangjian, et al. “Channel Estimation and Equalization of Underwater Acoustic MIMO-OFDM Systems: A Review.” Canadian Journal of Electrical and Computer Engineering, vol. 42, no. 4, 2019, pp. 199–208. 10.1109/CJECE.2019.2931177.
XXI. Roger, S., et al. “Fully Parallel GPU Implementation of a Fixed-Complexity Soft-Output MIMO Detector.” IEEE Transactions on Vehicular Technology, vol. 61, no. 8, 2012, pp. 3796–3800. 10.1109/TVT.2012.2203925.
XXII. Saad, Walid, et al. “A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems.” IEEE Network, vol. 34, no. 3, 2020, pp. 134–142. 10.1109/MNET.001.1900287.
XXIII. Sethi, Abhishek, et al. “Mobility and QoS Based Cross Network for ICN Vehicular Communication.” Procedia Computer Science, vol. 171, 2020, pp. 897–906. 10.1016/j.procs.2020.04.097.
XXIV. Sharief, A. H., and M. S. Sairam. “Performance Analysis of MIMO-RDWT-OFDM System with Optimal Genetic Algorithm.” AEU – International Journal of Electronics and Communications, vol. 111, 2019, 152912. 10.1016/j.aeue.2019.152912.
XXV. Singh, H., et al. “Performance Analysis and BER Comparison of OFDM System for 4×4 MIMO Fading Channel in Different Modulation Scheme.” 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), 2020, pp. 255–259. 10.1109/ICSSIT48917.2020.9214109.
XXVI. Wen, Feng, et al. “A Survey on 5G Massive MIMO Localization.” Digital Signal Processing, vol. 94, 2019, pp. 21–28. 10.1016/j.dsp.2019.06.004.
XXVII. Y. S. Mezaal, H. T. Eyyuboglu, and J. K. Ali, “Wide Bandpass and Narrow Bandstop Microstrip Filters based on Hilbert fractal geometry: design and simulation results,” PLoS One, vol. 9, no. 12, p. e115412, 2014.
XXVIII. Yang, Shuai, and Lajos Hanzo. “Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs.” IEEE Communications Surveys & Tutorials, vol. 17, no. 4, 2015, pp. 1941–1988. 10.1109/COMST.2015.2459053.
XXIX. You, Xiaohu, et al. “Towards 6G Wireless Communication Networks: Vision, Enabling Technologies, and New Paradigm Shifts.” Science China Information Sciences, vol. 64, no. 1, 2021, pp. 1–74. 10.1007/s11432-020-2955-6.
XXX. Y. S. Mezaal, H. T. Eyyuboglu, and J. K. Ali, “New dual band dual-mode microstrip patch bandpass filter designs based on Sierpinski fractal geometry,” in 2013 Third International Conference on Advanced Computing and Communication Technologies (ACCT), 2013. 10.1109/ACCT.2013.55
XXXI. Y. S. Mezaal and K. Al-Majdi and , “New miniature narrow band microstrip diplexer for recent wireless communications,” Electronics, vol. 12, no. 3, p. 716, 2023. 10.3390/electronics12030716.
XXXII. Zhang, C., and R. C. Qiu. “Massive MIMO Testbed—Implementation and Initial Results in System Model Validation.” arXiv, 2014. arXiv:1501.00035. URL: https://arxiv.org/abs/1501.00035.
XXXIII. Zhang, J. A., et al. “Multibeam for Joint Communication and Radar Sensing Using Steerable Analog Antenna Arrays.” IEEE Transactions on Vehicular Technology, vol. 68, no. 1, 2019, pp. 671–685. 10.1109/TVT.2018.2888708.
XXXIV. Zheng, Kan, et al. “Survey of Large-Scale MIMO Systems.” IEEE Communications Surveys & Tutorials, vol. 17, no. 3, 2015, pp. 1738–1760. 10.1109/COMST.2015.2425294.

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Abstract:

This study investigates the magnetohydrodynamic (MHD) natural convection flow of micropolar fluid in a semi-circular enclosure, incorporating the effects of thermal radiation. The analysis encompasses the interaction between buoyancy-driven flow, magnetic fields, radiative heat transfer, and the unique properties of micropolar fluids, which include microrotation and microstructure effects. The fundamental relations describing motion, thermal behavior, and rotational dynamics are established, incorporating the effects of the Lorentz force and radiative energy transfer. The Rosseland approximation is employed to model thermal radiation, and boundary conditions appropriate for a semi-circular geometry are applied. The governing relations are expressed in dimensionless form through characteristic parameters including the Rayleigh number (Ra), Prandtl number (Pr), Hartmann number (Ha), micropolar parameter (K), and radiation parameter (Rd). The modelled partial differential equations were carried out with a vorticity stream function algorithm to explore the influence of magnetic field strength, orientation, micropolar fluid properties, and radiative heat transfer on the flow and thermal characteristics. Results indicate significant alterations in flow patterns, temperature distribution, and microrotation behavior under varying magnetic field and radiative conditions. This comprehensive analysis provides insights into the complex dynamics of MHD natural convection in micropolar fluids with thermal radiation, with implications for advanced thermal management systems and materials processing applications.

Keywords:

Semi-circular enclosure,Micropolar fluid,Stream function–vorticity formulation,Magneto-hydrodynamic,Finite differences,

Refference:

I. Ababaei, A., M. Abbaszadeh, A. Arefmanesh, and A. J. Chamkha. “Numerical Simulation of Double-Diffusive Mixed Convection and Entropy Generation in a Lid-Driven Trapezoidal Enclosure with a Heat Source.” Numerical Heat Transfer, Part A: Applications, vol. 73, no. 10, 2018, pp. 702–720. 10.1080/10407782.2018.1459139.
II. Abd-El Aziz, M. “Thermal Radiation Effects on Magnetohydrodynamic Mixed Convection Flow of a Micropolar Fluid Past a Continuously Moving Semi-Infinite Plate for High Temperature Differences.” Acta Mechanica, vol. 187, 2006, pp. 113–127. 10.1007/s00707-006-0377-9.
III. Bhadauria, B. S., A. Kumar, S. K. Rawat, and M. Yaseen. “Thermal Instability of Tri-Hybrid Casson Nanofluid with Thermal Radiation Saturated Porous Medium in Different Enclosures.” Chinese Journal of Physics, vol. 87, 2024, pp. 710–727. 10.1016/j.cjph.2023.12.032.
IV. .Bejawada, S. G., and M. M. Nandeppanavar. “Effect of Thermal Radiation on Magnetohydrodynamics Heat Transfer Micropolar Fluid Flow over a Vertical Moving Porous Plate.” Experimental and Computational Multiphase Flow, vol. 5, 2023, pp. 149–158. 10.1007/s42757-021-0131-5.
V. Devi, T. S., C. V. Lakshmi, K. Venkatadri, V. R. Prasad, O. A. Bég, and M. S. Reddy. “Simulation of Unsteady Natural Convection Flow of a Casson Viscoplastic Fluid in a Square Enclosure Utilizing a MAC Algorithm.” Heat Transfer, vol. 49, no. 4, 2020, pp. 1769–1787. 10.1002/htj.21690.
VI. Eringen, A. C. “Theory of Micropolar Fluids.” Journal of Mathematics and Mechanics, vol. 16, 1966, pp. 1–18.
VII. Eringen, A. C. “Theory of Thermomicrofluids.” Journal of Mathematical Analysis and Applications, vol. 38, 1972, pp. 480–496. 10.1016/0022-247X(72)90106-0.
VIII. Hajatzadeh Pordanjani, A., S. Aghakhani, A. Karimipour, et al. “Investigation of Free Convection Heat Transfer and Entropy Generation of Nanofluid Flow Inside a Cavity Affected by Magnetic Field and Thermal Radiation.” Journal of Thermal Analysis and Calorimetry, vol. 137, 2019, pp. 997–1019. 10.1007/s10973-018-7982-4.
IX. Hussain, S. H., and A. K. Hussein. “Numerical Investigation of Natural Convection Phenomena in a Uniformly Heated Circular Cylinder Immersed in Square Enclosure Filled with Air at Different Vertical Locations.” International Communications in Heat and Mass Transfer, vol. 37, no. 8, 2010, pp. 1115–1126. 10.1016/j.icheatmasstransfer.2010.05.016.
X. Hussam, W. K., K. Khanafer, H. J. Salem, and G. J. Sheard. “Natural Convection Heat Transfer Utilizing Nanofluid in a Cavity with a Periodic Side-Wall Temperature in the Presence of a Magnetic Field.” International Communications in Heat and Mass Transfer, vol. 104, 2019, pp. 127–135. 10.1016/j.icheatmasstransfer.2019.02.018.
XI. Javed, T., Z. Mehmood, and M. A. Siddiqui. “Mixed Convection in a Triangular Cavity Permeated with Micropolar Nanofluid-Saturated Porous Medium under the Impact of MHD.” Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 39, 2017, pp. 3897–3909. 10.1007/s40430-017-0850-5.
XII. Kathyayani, G., and Venkata Ramudu G. “MHD Double-Diffusive Convection of Casson Fluid in a Triangular Enclosure with Thermal Radiation and Chemical Reactions.” Multiscale and Multidisciplinary Modeling, Experiments and Design, vol. 8, 2025, p. 289. 10.1007/s41939-025-00874-4.
XIII. Kim, B. S., D. S. Lee, M. Y. Ha, and H. S. Yoon. “A Numerical Study of Natural Convection in a Square Enclosure with a Circular Cylinder at Different Vertical Locations.” International Journal of Heat and Mass Transfer, vol. 51, no. 7, 2008, pp. 1888–1906. 10.1016/j.ijheatmasstransfer.2007.06.033.
XIV. Lee, J. M., M. Y. Ha, and H. S. Yoon. “Natural Convection in a Square Enclosure with a Circular Cylinder at Different Horizontal and Diagonal Locations.” International Journal of Heat and Mass Transfer, vol. 53, no. 25-26, 2010, pp. 5905–5919. 10.1016/j.ijheatmasstransfer.2010.07.043.
XV. Mahmoud, M. A. “Thermal Radiation Effects on MHD Flow of a Micropolar Fluid over a Stretching Surface with Variable Thermal Conductivity.” Physica A: Statistical Mechanics and Its Applications, vol. 375, no. 2, 2007, pp. 401–410. 10.1016/j.physa.2006.09.010.
XVI. Mojumder, S., S. Saha, S. Saha, and M. A. H. Mamun. “Effect of Magnetic Field on Natural Convection in a C-Shaped Cavity Filled with Ferrofluid.” Procedia Engineering, vol. 105, 2015, pp. 96–104. 10.1016/j.proeng.2015.05.012.
XVII. Nia, S. N., F. Rabiei, M. M. Rashidi, and T. M. Kwang. “Lattice Boltzmann Simulation of Natural Convection Heat Transfer of a Nanofluid in a L-Shape Enclosure with a Baffle.” Results in Physics, vol. 19, 2020, p. 103413. 10.1016/j.rinp.2020.103413.
XVIII. Parvin, S., and A. J. Chamkha. “An Analysis on Free Convection Flow, Heat Transfer and Entropy Generation in an Odd-Shaped Cavity Filled with Nanofluid.” International Communications in Heat and Mass Transfer, vol. 54, 2014, pp. 8–17. 10.1016/j.icheatmasstransfer.2014.02.031.
XIX. Park, J., M. Kim, G. S. Mun, et al. “Natural Convection in a Square Enclosure with a Circular Cylinder with Adiabatic Side Walls According to Bottom Wall Temperature Variation.” Journal of Mechanical Science and Technology, vol. 32,pp. 3201–3211. 10.1007/s12206-018-0623-9.
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XXI. Pop, I., and M. Sheremet. “Free Convection in a Square Cavity Filled with a Casson Fluid under the Effects of Thermal Radiation and Viscous Dissipation.” International Journal of Numerical Methods for Heat & Fluid Flow, vol. 27, no. 10, 2017, pp. 2318–2332. 10.1108/HFF-09-2016-0352.
XXII. Raja Rajeswari, V., K. Venkatadri, and V. Ramachandra Prasad. “Nanoparticle Shape Factor Impact on Double Diffusive Convection of Cu-Water Nanofluid in Trapezoidal Porous Enclosures: A Numerical Study.” Numerical Heat Transfer, Part A: Applications, 2024, pp. 1–20. 10.1080/10407782.2024.2380814.
XXIII. Singhal, R., S. Dutta, and J. C. Kalita. “Comprehensive Study of Forced Convection over a Heated Elliptical Cylinder with Varying Angle of Incidences to Uniform Free Stream.” International Journal of Thermal Sciences, vol. 194, 2023, p. 108588. 10.1016/j.ijthermalsci.2023.108588.
XXIV. Varol, Y., H. F. Oztop, and T. Yilmaz. “Natural Convection in Triangular Enclosures with Protruding Isothermal Heater.” International Journal of Heat and Mass Transfer, vol. 50, no. 13–14, 2007, pp. 2451–2462. 10.1016/j.ijheatmasstransfer.2006.12.027.
XXV. Venkatadri, K., O. A. Bég, P. Rajarajeswari, and V. R. Prasad. “Numerical Simulation of Thermal Radiation Influence on Natural Convection in a Trapezoidal Enclosure: Heat Flow Visualization through Energy Flux Vectors.” International Journal of Mechanical Sciences, vol. 171, 2020, p. 105391. 10.1016/j.ijmecsci.2019.105391.
XXVI. Venkatadri, K., V. Ramachandra Prasad, O. Anwar Bég, S. Kuharat, and T. A. Bég. “Magneto-Thermo-Gravitational Rayleigh–Bénard Convection of an Electro-Conductive Micropolar Fluid in a Square Enclosure: Finite Volume Computation.” Numerical Heat Transfer, Part A: Applications, 2024, pp. 1–26. 10.1080/10407782.2023.2299290.
XXVII. Venkatadri, K., Fazuruddin, S., O. Anwar Bég, and O. Ramesh. “Natural Convection of Nanofluid Flow in a Porous Medium in a Right-Angle Trapezoidal Enclosure: A Tiwari and Das’ Nanofluid Model.” Journal of Taibah University for Science, vol. 17, no. 1, 2023. 10.1080/16583655.2023.2263224.
XXVIII. Venkatadri, K., K. V. Narasimha Murthy, T. A. Bég, O. Anwar Bég, and S. Kuharat. “Numerical Simulation of Natural Convection in a Rectangular Enclosure Filled with Porous Medium Saturated with Magnetic Nanofluid Using Buongiorno’s Two-Component Model.” Canadian Journal of Chemical Engineering, 2024, pp. 1–22. 10.1002/cjce.25300.
XXIX. Venkatadri, K., T. S. Devi, A. Shobha, K. R. Sekhar, and V. R. Rajeswari. “Numerical Study of Natural Convection Flow in a Square Porous Enclosure Filled with Casson Viscoelastic Fluid.” Contemporary Mathematics, vol. 4, no. 3, 2023, pp. 379–391. https://ojs.wiserpub.com/index.php/CM/article/view/2913.
XXX. Vedavathi, N., K. S. Mozhi, K. Venkatadri, et al. “Numerical Analysis of Cu–H2O Nanofluid Natural Convection in a Trapezoidal Enclosure Filled with Porous Medium.” International Journal of Applied and Computational Mathematics, vol. 9, 2023, p. 121. 10.1007/s40819-023-01602-7.

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Abstract:

The growing complexity of reservoir management driven by hydrological uncertainty and sedimentation has led to increased reliance on advanced optimization techniques. This review critically examines the recent application of the Charged System Search (CSS) algorithm in addressing nonlinear, multi-constraint challenges within water resource systems. Across the literature, CSS is recognized as an effective method for optimizing operations related to hydropower, water supply, and sediment management. Most studies adopt scenario-based modeling with stochastic hydrological inputs to enhance system resilience under climate variability. A key distinction among studies lies in algorithm customization. While some apply standard CSS, others hybridize it with techniques like Particle Swarm Optimization (PSO), Sequential Quadratic Programming (SQP), and Genetic Algorithms (GA) to improve convergence and solution quality. Comparisons with other metaheuristics such as Differential Evolution (DE), Ant Colony Optimization (ACO), and NSGA-II further contextualize CSS’s relative performance. The reviewed works vary in modeling scale and objectives: some aim to maximize water or energy yield, others to minimize sedimentation or manage operational trade-offs. Models span single- and multi-reservoir systems, with temporal scopes ranging from short-term operations to long-term sediment dynamics. Implementation environments include MATLAB, Python, and specialized hydrological platforms, reflecting methodological diversity. Additionally, researchers employ both single- and multi-objective optimization, often utilizing Pareto fronts for trade-off analysis. By synthesizing these methodological trends and algorithmic adaptations, the review underscores CSS’s flexibility and effectiveness within metaheuristic-based reservoir optimization. However, it also identifies key limitations, including a lack of standardization, minimal real-world application, and weak integration with real-time forecasting tools. The paper concludes with suggestions for future research aimed at enhancing computational efficiency, operational relevance, and decision-support capability in the context of increasing water resource challenges under climate change.

Keywords:

Charged System Search (CSS),Reservoir Management,Optimization Algorithms,Sediment Accumulation,Multi-objective Modeling,

Refference:

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III. Almubaidin, Mohammad Abdullah Abid, et al. “Enhancing Reservoir Operations with Charged System Search (CSS) Algorithm: Accounting for Sediment Accumulation and Multiple Scenarios.” Agricultural Water Management, vol. 293, no. February, 2024, p. 108698. 10.1016/j.agwat.2024.108698.
IV. Asadieh, Behzad, and Abbas Afshar. “Optimization of water-supply and hydropower reservoir operation using the charged system search algorithm.” Hydrology 6.1(2019):5. 10.3390/hydrology6010005
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VIII. Goharian, Erfan, et al. “Developing an Optimized Policy Tree-Based Reservoir Operation Model for High Aswan Dam Reservoir, Nile River.” Water (Switzerland), vol. 14, no. 7, Apr. 2022. 10.3390/w14071061.
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Abstract:

This study showcases a novel insight into the growth rate of Bangladeshi, Indian, and Nepali people, focusing on historical population patterns, contemporary demographic trends, and future population projections. Asia, home to over 4.5 billion people, accounts for approximately 70% of the global population, with Bangladesh, India, and Nepal being the most populous countries in South Asia. To facilitate chances for more significant policymaking in these nations, this study will examine the growth rate and its effects in the years to come. The demographic shifts in Bangladesh are creating new economic opportunities, with insights that can guide policymakers in refining population strategies, which are also relevant to India and Nepal. This study thoroughly assesses the precision and relevance of five mathematical models, e.g., the least squares model, Malthusian (exponential growth) model, logistic growth model, hyperbolic growth model, and discrete logistic growth model, in forecasting demographic changes in Bangladesh, India, and Nepal from 1950 to 2100. Furthermore, the study offers a speculative analysis of how these countries have previously handled population growth and the strategies they may adopt in the future.

Keywords:

Bangladesh,Growth Rate Comparison,India,Mean Absolute Percentage Error,Nepal,South Asian Countries,

Refference:

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XIII. R. Islam, K. Chandra Roy, N. Uddin, R. Karim, S. Sarker, and P. Dey, “DEMOGRAPHIC ANALYSIS AND COMPARISON WITH THE POPULATION OF BANGLADESH AND PAKISTAN”. 10.5281/zenodo.8241173.
XIV. R. Karim, M. A. Akbar, M. A. B. Pk, and P. Dey, “A study on fractional-order mathematical and parameter analysis for CAR T-cell therapy for leukemia using homotopy perturbation method,” Partial Differential Equations in Applied Mathematics, vol. 14, Jun. 2025. 10.1016/j.padiff.2025.101152.
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