A Wavelet Basis ANN and 5-Class Decision Factor AI Algorithm

Author:

Liu Xuepeng1,Zhao Dongmei2,Peng Yihang1,Li Jianping3

Affiliation:

1. School of Mechanical Engineering, Foshan Polytechnic, City Foshan, 528137, China

2. School of Information Engineering, Zhongshan Polytechnic, City Zhnongshan, 528400, China

3. School of Automobile Engineering, Shenzhen Polytechnic, City Shenzhen 518055, China

Abstract

The accuracy and reliability of continuous space curve estimation is the key to global exploration. An improved artificial intelligence algorithm is proposed for continuous space analysis. First, a wavelet basis ANN algorithm is proposed to determine the discretization strategy in continuous space. The hidden layer node transfer function in a BP neural network is replaced by a wavelet basis function, and the modified BP neural network is composed of a wavelet neural network. Second, an improved wolf algorithm is established. The core wolf system ensures the precision of the whole exploration task. Finally, main and auxiliary double cores and a five-class decision factor are used to establish a population classification model to solve the convergence of the algorithm.

Funder

National Natural Science Foundation of China

Foshan polytechnic project

Zhongshan polytechnic project

Guangdong Provincial First-class Post-Course Funding Program

Guangdong Provincial Education Science Planning Project

Supporting scientific research funds for high-level talents in Foshan City

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

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