搜索资源列表
4378347348348
- 基于遗传算法的BP神经网络气象预报建模,20世纪90年代以来，国内外在大气学科中开展了很多有关神经网络预报建模和气候分析等应用研究。然而随着神经网络方法在大气科学领域研究的不断深入，研究人员发现神经网络方法在实际业务天气预报应用中存在一个重要的问题-BP neural network modeling of weather forecasting, in the 20th century since the 1990s, domestic and international discipline
Commonly_used_meteorologica_package
- 气象保障常用软件包:本书分为10章，包括客观分析、诊断分析、多元统计分析、主分量分析、自适应统计天气预报方法、时间序列分析、谱分析、人工神经网络天气预报方法、灰色系统及气象绘图软件等内容。 Fortran代码写在word文档中。-Commonly used meteorological package: This book is divided into 10 chapters, including an objective analysis, diagnostic analysis, mult
cllib
- CLLIB is a varied collection of Common lisp tools and routines in CLOCC. -CLLIB is a varied collection of Common lisp tools and routines in CLOCC. Includes: ■ "guess the animal" game simple neural net (AI) ■ autoload function and snarfi
prediction-of-weather-data
- 用BP神经网络和rbf神经网络预测风电功率-BP neural network and rbf neural network forecasting wind power
BP-wind-prediction
- 含NWP数值天气预报和不含NWP数值天气预报的BP神经网络预测风电功率两种方法进行比较，含数据，实际案例。-With and without NWP NWP Numerical Weather Prediction NWP BP neural network prediction of wind power are two methods were compared with the data, the actual case.
Forecasting-wind-power
- 这是一篇关于利用改进的粒子群优化算法来构造多层人工神经网络的文章，可用于预测风力和天气。-This is an article on the use of improved particle swarm optimization algorithm to construct a multilayer artificial neural network of the article, can be used to predict the wind and weather.
PV_BP_forest_qingtian
- 实现光伏预测，通过当天的光伏出力和天气指数加上预测日的天气指数预测明天的光伏出力，基于BP神经网络对光伏出力进行预测-Realization of photovoltaic forecast photovoltaic output through the day and the weather forecast daily index plus weather forecast for tomorrow s PV output index, BP neural network to predic
neural-network
- 难得的人工神经网络用于智能气象预报建模的资料-neural network for intelligent weather forecasting modeling
NeuralNetwork
- this file contains code for neural network to predict weather and diseases according to input data.
BP神经网络
- 简单的BP神经网络预测天气例程，包括训练数据集和天气数据来源(Simple BP neural network weather prediction routine, including training data set and weather data source)
MATLAB雾霾交通标志shibie[GUI]
- 该课题为基于MATLAB bp神经网络的雾霾天气下交通标志的识别系统。主要分两步骤，一是进行图像去雾，采用暗通道的方法获取光透射率，从而去除雾霾。得到清晰的图片后，利用颜色的方法进行交通标志的定位，众所周知，交通标志基本是红，蓝，黄三色组成，根据RGB不同组合可以定位到不同颜色，因为存在误差，所以需要借助形态学相关知识，将得到的误干扰面积去除，从而实现精准定位。定位后，在原图基础上进行分割出彩色图标，利用bp神经网络方法，进行训练，识别，从而得出结果。本设计配有一个GUI可视化界面，操作简单容易