基于BP神经网络的设备快速估价模型研究
Rapid valuation model for equipment based on BP neural network
吴崇1
作者信息
- 1. 中煤科工集团武汉设计研究院有限公司,湖北 武汉 430064
- 折叠
摘要
文章创新性地提出了利用BP神经网络来进行设备价快速估算模型研究.以带式输送机为例,在对带式输送机价主要影响指标进行分析的基础上,将BP 神经网络应用到带式输送机快速估算模型建立中,并以Z设计院总承包带式输送机采购价为基础,对构建的BP 神经网络设备价格快速估算模型进行检验.研究表明,该模型可以在不失准确性的前提下极大地提高设备价报算效率,尤其对询价周期长的多参数、复杂通用设备快速报价问题的解决具有适用性,可将设备报价时间由需数天节省到几分钟,通过建立设备价快速报价模型,可以摆脱工程造价人员在设备价询价过程中因询价厂家数量过少、缺乏对比性或报价厂家报价故意偏离正常价等主客观因素对设备价定价精度的影响.
Abstract
It was proposed to build a rapid valuation model of equipment based on BP neural network.Taking the belt conveyor as an example,based on the analysis of the main influencing indicators of the belt conveyor price,the BP neural network was applied to establish the valuation model.Based on the purchase price of the general contracting belt conveyor of Z design institute,the BP neural network equipment price rapid valuation model was tested.The research shows that the model can greatly improve the efficiency of equipment price quotation without losing accuracy,especially for the solution of multi-parameter and complex general equipment quick quotation problem with long inquiry period.It can save the equipment quotation time from several days to several minutes.By establishing the quick quotation model of equipment price,it can get rid of the influence of subjective and objective factors such as too few inquiry manufacturers,lack of contrast or intentional deviation of quotation manufacturers'quotation from normal price on the pricing accuracy of equipment price in the process of equipment price inquiry.
关键词
BP神经网络/设备价/带式输送机/快速估价Key words
BP neural network/equipment price/belt conveyor/rapid valuation引用本文复制引用
出版年
2024
NETL
NSTL
万方数据