Research on particle swarm optimization and neural network ensemble learning algorithm for weather forecast

Hui Feng

doi:10.1117/12.2671207

1 June 2023 Research on particle swarm optimization and neural network ensemble learning algorithm for weather forecast

Hui Feng

Proceedings Volume 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022); 126252X (2023) https://doi.org/10.1117/12.2671207
Event: International Conference on Mathematics, Modeling and Computer Science (MMCS2022),, 2022, Wuhan, China

Abstract

In the development of modern economy and society, with the continuous improvement of science and technology, people have higher and higher requirements for the prediction accuracy of catastrophic climate. International scholars in the integration on the basis of previous research experience, found that although the BP neural network is applied in the apocalypse meteorological forecast has achieved excellent results, but the actual network structure is difficult to solve the problem of network into a local solution, so some people put forward neural network as the core of the particle swarm integrated learning algorithm, mainly to the BP neural network algorithm as the basic framework, In the process of learning, the particle swarm optimization algorithm is introduced to optimize the network structure and the initial connection weight. The independent network individuals are obtained in the iterative training of the network, and the linear programming method is used to obtain the weight coefficient. Finally, the output conclusion of the neural network is obtained, and the short-term climate prediction model is constructed. The experimental results show that the particle swarm ensemble learning algorithm with neural network as the core has strong learning ability in the current weather forecast work, and can ensure the accuracy of system prediction is effectively improved.

Citation Download Citation

Hui Feng "Research on particle swarm optimization and neural network ensemble learning algorithm for weather forecast", Proc. SPIE 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022), 126252X (1 June 2023); https://doi.org/10.1117/12.2671207

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KEYWORDS

Neural networks

Evolutionary algorithms

Particle swarm optimization

Data modeling

Education and training

Artificial intelligence

Artificial neural networks

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