Application of LDHA-BP in Prediction of Atmospheric PM2.5 Concentration

被引:0
|
作者
Zhao, Jiangiang [1 ,2 ]
Dou, Jianjun [2 ]
Ge, Kao [2 ]
机构
[1] Southeast Univ, Sch Math, Nanjing 210096, Jiangsu, Peoples R China
[2] Xuzhou Univ Technol, Sch Math & Phys Sci, Xuzhou 221111, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Leader of dolphins herd algorithm; BP neural network; LDHA-BP; PM2.5;
D O I
10.1109/itnec.2019.8729040
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
LDHA-BP algorithm is designed for lack of using BP neural networks to predict atmospheric concentrations of PM2.5. In this algorithm, the process of solving the optimal weights and thresholds of BP neural networks will be transformed into the process of finding the optimal location of the dolphin species predator's, by introducing Leader Dolphins Herd Algorithm (LDHA).The algorithm effectively combines the good generalization ability of BP neural network neural and the global optimization ability, local search capability of LDHA. Test data for PM2.5 from a monitoring point in Wuhan to predict the PM2.5 concentrations in future. The experimental results show that LDHA-BP is faster, more accurate to predict the PM2.5 concentrations and it has good practical value.
引用
收藏
页码:2239 / 2245
页数:7
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