摘要
采用非线性PSO-BP神经网络对天气预测,可以有效地预测出多云、晴天和下雨3种不同天气。非线性PSO-BP算法提高了天气预测的准确度和精度,加快了网络收敛速度,为智能化天气预报提供了基础。
Three kind of different weathers,including clear day, cloudy day and rainy day can be predicted by using a neural network trained by the hybrid algorithm combining nonlinear particle swarm optimization （PSO） algorithm with back propagation （BP）. Nonlinear PSO-BP method improved the prediction rate and computing accuracy, promoted the net convergence speed, and provided an effective and feasible method for intelligent weather forecast.
出处
《现代农业科技》
2013年第11期265-266,268,共3页
Modern Agricultural Science and Technology
关键词
非线性
粒子群算法
BP神经网络
天气预测
nonlinear
particle swarm optimization algorithm
BP neutral network
weather forecast
