文章基本信息

标题：Forecasting Electrical Load for Home Appliances using Genetic Algorithm based Back Propagation Neural Network
本地全文：下载
作者：Gaurang Panchal ; Devyani Panchal
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2015
卷号：4
期号：4
页码：1503-1506
出版社：Shri Pannalal Research Institute of Technolgy
摘要：The combining usage of genetic algorithms and artificial neural networks, were originally motivated by the astonishing success of these concepts in their biological counterparts. Despite their totally deferent approaches, both can merely be seen as optimization methods, which are used in a wide range of applications. "Genetic algorithms (GA) are good at taking large, potentially huge search spaces and navigating them, looking for optimal combinations of things, solutions you would find difficult to accomplish." A genetic algorithm (GA) is an iterative search, optimization and adaptive machine learning technique premised on the principles of Natural selection. They are capable to finding solution to NP hard Problems. Neural Networks utilizing back propagation based learning have promisingly showed results to a vast variety of function and problems. Electrical load forecasting is one such classical problem for computation. This paper presents the application of GA based Back propagation Network for long term load forecasting in power system. This problem is formulated as optimization problem. Advantages and disadvantages of this algorithm are reported and discussed.
关键词：Genetic Algorithm; Neural Network; ; Electrical Load Forecasting; Neural Network Parameter