Читать книгу Agricultural Informatics - Группа авторов - Страница 23

There exist a number of applications in agriculture that use machine learning techniques for prediction and analysis. The article discusses some of the commonly used approaches in research. Large amount of data can be collected from various resources for performing analysis on crop yield forecast. Integrating machine learning into agricultural processes is a vastly growing research area these days. The collaborative model of computer science with agriculture can help in exploring various domains of agronomics and forecasting agricultural crops. The merger of the two approaches can be helpful in pre-harvest crop forecasting and the traditional forecasting method can be out ruled by using computational statistical approaches.