基于遗传算法优化BP神经网络的光伏发电功率预测

Power Prediction of Photovoltaic Power Generation Based on BP Neural Network Optimized by Genetic Algorithm

人工神经网络最基本的单元是人工神经元,其特点是输入无限,输出唯一。通过对信息以及数据的计算和简单化,模型可以将不同的人工神经单元重新分类组合,最终塑造一个新的非线性系统。这样,机器就可以模拟人脑的学习、计算和图像识别等生物学特性,从而产生“类人思维”,更好地为人类服务。目前,神经网络已广泛应用于电力预测、智能控制、行为识别等领域。

The most basic unit of artificial neural network is artificial neuron,which is characterized by infinite input and unique output.Through the calculation and simplification of information and data,the model can reclassify and combine different artificial neural units,and finally shape a new nonlinear system.In this way,the machine can simulate the biological characteristics of human brain,such as learning,computing and image recognition,so as to produce"human like thinking"and better serve human beings.At present,neural network has been widely used in power prediction,intelligent control,behavior recognition and other fields.