基于IAFA-BP的门式起重机技术特性权重预测  

Weight prediction of technical characteristics of gantry crane based on IAFA-BP

作　　者：刘畅[1] 何丽娜 Liu Chang;He Lina

机构地区：[1]西南交通大学机械工程学院,成都610031

出　　处：《起重运输机械》2024年第10期26-32,共7页Hoisting and Conveying Machinery

基　　金：国家自然科学基金资助项目(51705436);国家科技重大资助项目(2017-I-0011-0012);四川省科技计划资助项目(2021JDRC0174)。

摘　　要：鉴于现有研究对门式起重机设计过程中功能需求与技术特性之间关系的挖掘尚有欠缺,文中提出了基于改进自适应萤火虫算法优化BP神经网络的门式起重机技术特性权重预测模型。通过分析门式起重机功能需求和技术特性之间的关系,根据功能需求重要度预测技术特性的权重,从而实现门式起重机的产品适应性设计。此外,为了提高门式起重机技术特性预测精度,针对萤火虫算法及BP神经网络存在的缺陷,设计了改进的自适应萤火虫算法,用于优化BP神经网络的权值和阈值,验证该模型的有效性。与传统模型进行对比分析,表明该模型具有更高的预测精度。Considering the lack of discussion on the relationship between functional requirements and technical characteristics in the design process of gantry crane in existing researches,in this paper,a weight prediction model of technical characteristics of gantry crane based on improved adaptive firefly algorithm and optimized BP neural network is proposed.By analyzing the relationship between functional requirements and technical characteristics of gantry crane,the weight of technical characteristics is predicted according to the importance of functional requirements,and the product adaptability design of gantry crane is realized.In addition,in order to improve the accuracy of the technical characteristics prediction of the gantry crane,an improved adaptive firefly optimization algorithm(IAFA)is proposed to optimize the weights and thresholds of the BP neural network and verify the effectiveness of the model.The comparison with the traditional model shows that this model has higher prediction accuracy.

关 键 词：门式起重机 功能需求 技术特性 自适应萤火虫算法 BP神经网络 

分 类 号：TH213.5[机械工程—机械制造及自动化] TP391.72[自动化与计算机技术—计算机应用技术]