Prediction of Vehicle Fuel Consumption Model Based on Artificial Neural Network
Prediction of Vehicle Fuel Consumption Model Based on Artificial Neural Network
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DOI：
10.4028/www.scientific.net/amm.492.3
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发表时间：
2014-01
期刊：
影响因子：
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通讯作者：
A. Amer;A. Abdalla;A. Noraziah;Ainul Azila Che Fauzi
中科院分区：
文献类型：
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作者：
A. Amer;A. Abdalla;A. Noraziah;Ainul Azila Che Fauzi
随着燃料价格的不断上涨，最小化燃料消耗是可持续工程的一个主要问题。显然，为了避免不必要的燃料浪费并最大限度地利用燃料，有效的燃料消耗成本估计技术是必不可少的。2.提出了一种用于汽车燃油消耗模型的优化方法，首先简要介绍了几种估算计算器技术，其次提出了以最小化车辆行驶距离为优化目标的优化方法2路由问题神经网络模型的第一层有5个输入节点，分别代表发动机的大小、距离、燃料类型、速度和乘客，第二层有15个节点，第三层有1个输出节点，分别代表燃料消耗费用.最后将计算结果与其他燃料模型进行了比较，表明该模型可以更准确地估计燃料成本，从而优化燃料消耗使用，准确地优化燃料消耗使用。
With the increasing cost of fuel price minimizing fuel consumption is a major concern as far as sustainable engineering is concerned It is apparent that effective techniques for estimating fuel consumption costs are essential in order to avoid unnecessary fuel wastage and make use the most out of it In this paper an Artificial Neural Network (ANN) 2approach is used to fuel consumption model was proposed First few estimation calculator techniques have2 been briefly described Second the proposed optimization objective is to minimize the travel distance which is the corresponding to vehicle 2routing problem The neural network model has 5 input nodes at layer first which are representing engine size distance fuel type speed and passenger 15 nodes at hidden layer and one output node representing the fuel consumption costs. Finally calculations results are compared with other fuel model which indicate that estimation of fuel cost can be more accurate to optimize the fuel consumption usage accurate to optimize the fuel consumption usage.