ENSEMBLE MACHINE LEARNING BASED WIND FORECASTING TO COMBINE NWP OUTPUT WITH WEATHER STATION DATA

Abstract

In the Existing system, Wind generation resources (WGRs) are the fastest growing energy resources throughout the world. An accurate wind forecasting is critical to the integration of a large amount of wind generation units into the grid operations. In the Proposed system,   machine learning based method to forecast wind power production, which uses both the wind generation forecasted by a numerical weather prediction (NWP) model and the meteorological observation data from weather stations. In the Modification process, we implement the application to identify the types of soil, water source of that land whether that land is based on rain or bore water .And suggest what of crop is suitable for that soil. So through this application we provide application for the people to know about the agriculture. We predict the type of crop which one is suitable for that particular soil, weather condition, temperature and so on. So for, we are using machine learning with the set of dataset we are identify the crop for the corresponding soil.