Mathematical foundations of neural network weight optimization
*Madhuri B. ThoratCorresponding authorthoratmadhuri31@gmail.comDepartment of Computer Science and EngineeringBharti Vidyapeeth (Deemed to be University)College of EngineeringPune, Maharashtra, 411043, IndiaView full profile → , Vaishali Pawan Wawagevaishali.wawage@vit.eduDepartment of Engineering Science and HumanitiesVishwakarma Institute of TechnologyPune, Maharashtra, 411037, IndiaView full profile → , Durga Prasad Yadavdurga.prasad@niu.edu.inSchool of Engineering & TechnologyNoida International UniversityGreater Noida, Uttar Pradesh, 203201, IndiaView full profile → , P. Pushpalathapushpalatha@gmail.comDepartment of Computer ScienceMeenakshi College of Arts and ScienceMeenakshi Academy of Higher Education and ResearchChennai, Tamil Nadu, 600078, IndiaView full profile → , Yatin Gandhigyatin33@gmail.comCompetent SoftwaresPune, Maharashtra, 411069, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Apr 2025
- Published Online:
- 23 Apr 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2297
- Pages:
- 2065–2073
Abstract
Keywords
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References
[1] J. P. Selvan and G. P. Potdar, “Calculation of neural network weights and biases using particle swarm optimization,” Engineering Proceedings, vol. 59, p. 190 (2023), doi: 10.3390/engproc2023059190.
[2] J. Bedi, A. Anand, S. Godara, R. S. Bana, M. A. Faiz, S. Marwaha, and R. Parsad, “Effective weight optimization strategy for precise deep learning forecasting models using EvoLearn approach,” Scientific Reports, vol. 14, p. 20139 (2024), doi: 10.1038/s41598-024-69325-3.
[3] F. Marchetti, S. Guastavino, C. Campi, F. Benvenuto, and M. Piana, “A comprehensive theoretical framework for the optimization of neural networks classification performance with respect to weighted metrics,” Optimization Letters, vol. 19, pp. 169–192 (2025), doi: 10.1007/s11590-024-02112-1.
[4] D. Chung and I. Sohn, “Neural network optimization based on complex network theory: A survey,” Mathematics, vol. 11, p. 321 (2023), doi: 10.3390/math11020321.
[5] R. Agarwal, R. P. Chaturvedi, A. Mishra, S. Asthana, and M. Parashar, “An approach for determining the best solution for intuitionistic fuzzy transportation problem,” Journal of Information and Optimization Sciences, vol. 45, no. 7, pp. 1867–1879 (2024), doi: 10.47974/JIOS-1739.
[6] F. Cao, X. Guo, X. Dong, and D. Yuan, “wbPINN: Weight balanced physics-informed neural networks for multi-objective learning,” Applied Soft Computing, vol. 170, p. 112632 (2025), doi: 10.1016/j.asoc.2024.112632.
[7] U. Waqas, M. F. Ahmed, H. M. A. Rashid, and M. E. Al-Atroush, “Optimization of neural-network model using a meta-heuristic algorithm for the estimation of dynamic Poisson’s ratio of selected rock types,” Scientific Reports, vol. 13, p. 11089 (2023), doi:10.1038/s41598-023-38163-0.
[8] L. Gonbadi, H. Rostami, E. Sahafizadeh, S. Rostami, M. M. Nejad, and A. Shirzadi, “Input driven optimization of echo state network parameters for prediction on chaotic time series,” Scientific Reports, vol. 15, p. 33005 (2025), doi: 10.1038/s41598-025-18261-x.
[9] D. Goyal, A. Kumar, Y. Gandhi, and V. Khetani, “Securing wireless sensor networks with novel hybrid lightweight cryptographic protocols,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 27, no. 2-B, pp. 703–714 (2024).
[10] S. Anjum, A. Ahmed, R. Kurup, S. Kidiya, and S. Kureshi, “Blockchain based image steganography,” International Journal of Advanced Computer Theory and Engineering (IJACTE), vol. 14, no. 1, pp. 147–152 (May 2025).




