基于模糊神经元网络的智能车辆调度策略

Lu Fei, Liu Hongguang
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引用次数: 0

摘要

提出了一种全新的智能车辆调度系统,并应用于以车辆运输为服务的物流公司。该系统的关键技术是复合模糊神经元网络。首先,设想一个综合满足的函数。然后分为三个子功能。每个子函数都基于自己的模糊规则,并由复合模糊神经元网络实现。每个车辆的最终值是每个子函数乘以其自身权利的总和。选取值最高的车辆作为接收调度指令的车辆。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An intelligent strategy of vehicle scheduling based on fuzzy-neuron networks
A brand new intelligent system of vehicle scheduling is proposed and applied to the logistics companies whose service is transportation with vehicle. The key technology of this system is a compound fuzzy-neuron networks. First, a synthetically satisfied function is conceived. Then it is divided into three sub-functions. Each sub-function is each based on its own fuzzy rules and realized by a compound fuzzy-neuron networks. The final value of each vehicle is the sum of each sub-function multiplying its own right. The selective car which has the highest value is the vehicle to receive the scheduling order.
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