基于GA-BP神经网络的变电站工程造价评估

Ke Lv, Shoupeng Wang, Yan Zhang, Libin Zhang, Yulian Xi, Zhouyue Ling
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引用次数: 0

摘要

本文以变电站工程造价的影响因素为输入变量,以造价评价值为输出结果,利用神经网络算法对变电站工程造价进行评价。针对神经网络算法的不足,采用遗传算法(GA)对神经网络进行优化,实现稳定有效的变电站工程造价评估。在Matlab环境下进行了仿真,并与传统的BP神经网络进行了比较。结果表明,经遗传算法改进的模型在实际应用中效果显著,可以指导工程造价管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cost Evaluation of Substation Project Based on GA-BP Neural Network
This paper takes the influencing factors of substation project cost as the input variable and the cost evaluation value as the output result, and then uses the neural network algorithm to evaluate the cost. Considering the shortcomings of neural network algorithm, genetic algorithm (GA) is used to optimize the neural network to realize a stable and effective evaluation of substation project cost. The simulation is carried out in Matlab environment, and the proposed algorithm is compared with the traditional BP neural network. The results show that the model improved by GA has more remarkable effect in application, and can guide the project cost management.
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