Abstract
Regression analysis is an important machine learning task used for predictive analytic in business, sports analysis, etc. In regression analysis, optimization algorithms play a significant role in searching the coefficients in the regression model. In this paper, nonlinear regression analysis using a recently developed metaheuristic multi-verse optimizer (MVO) is proposed. The proposed method is applied to 10 well-known benchmark nonlinear regression problems. A comparative study has been conducted with particle swarm optimizer (PSO). The experimental results demonstrate that the proposed method statistically outperforms the PSO algorithm.
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Bagchi, J., Si, T. (2021). Nonlinear Regression Analysis Using Multi-verse Optimizer. In: Gao, XZ., Kumar, R., Srivastava, S., Soni, B.P. (eds) Applications of Artificial Intelligence in Engineering. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-33-4604-8_4
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DOI: https://doi.org/10.1007/978-981-33-4604-8_4
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