MACHINE LEARNED MODELS FOR ITEM PRICE PLANNING

摘要

In an example embodiment, multiple machine learned models are used to continually learn from data to update various prediction models. Prediction of item prices, at the production and distribution point level, and utilizing this information along with other item information, such as crop yield, operational cost, and storage cost in the case of arming, may be used to solve the long- and short-term planning problems of farmers and help in decision making based on daily and the most up-to-date forecasts.