Research on Predicting the Processing Time of Approximate Process Workpieces Based on Improved Genetic Algorithm Optimizing BP Neural Network
Authors: 
Wen Dai, Bin Zhao, Yuanyang ZhouAuthors Info & Claims
Wen Dai, Bin Zhao, Yuanyang ZhouAuthors Info & ClaimsPages 504 - 509
Abstract
A modified genetic algorithm optimized BP neural network prediction model for processing time is proposed to address the issue of multiple rounds of measurement required for producing similar process workpieces. By changing the selection operation of genetic algorithm, adaptive optimization of crossover and mutation operations, the BP neural network prediction model has obtained better weight and bias values, and a more accurate workpiece processing time prediction model has been established. The experimental results show that the improved genetic algorithm optimized BP neural network model has stronger prediction ability than traditional prediction models, and is an effective method for predicting the processing time of approximate process workpieces.
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Published In
September 2023
577 pages
ISBN:9798400716362
DOI:10.1145/3660395
Copyright © 2023 ACM.
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Association for Computing Machinery
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Published: 01 June 2024
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AIBDF 2023
AIBDF 2023: 2023 3rd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum
September 22 - 24, 2023
Guangzhou, China
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