Modified Marine Predator Algorithm Based on Multi-strategy Fusion and its Application
NI Yunfeng
ZHANG Dingkun
WANG Jing
GUO Ping
Abstract：In order to solve the problem of local fans adjusting wind speed in advance according to the next time demand vol-ume,a novel Elman neural network algorithm based on modified marine predator algorithm(MMPA)is proposed to predict the de-mand volume.Firstly,the chaotic map is used to initialize the population to improve the inhomogeneity of the population position,reverse learning is introduced to operate the individuals before each iteration,differential operation is introduced to the prey matrix in the middle and late iteration,and several test functions are selected to test it.Secondly,the improved marine predator algorithm is used to optimize the initial weights and thresholds in the Elman neural network to improve the accuracy of the required air volume prediction results.The results show that the prediction accuracy of MMPA-Elman neural network model is higher,and the accurate prediction of air volume is realized,which provides guarantee for the safety production of coal mines.
Keywords：marine predators algorithmElman neural networkair demand prediction
Publication Date：2025-04-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 984-988,1050 )