Forecasting of Demand and Supply of Chemical Fertilizer in Madhya Pradesh Using Expert System

Abstract

The main objective of the application of fertilizers is to predict the demand for and availability of chemical fertilizers in order to keep all farmers happy. An agronomist is an individual who contributes to the decision-making process that requires chemical fertilizers. Various statistical and computer simulations are used to predict fertilizers. Expert methods can make impressive agricultural predictions by applying different types of crop patterns. Expert models can easily explain complex phenomena. A physical and mathematical model to determine the rate of use of fertilizers is developed in this study. The predictive model is developed using the Expert System soft technique and the neural network multilayer model. Farmers use state-of-the-art technology to reduce labor and increase efficiency. newlineThe expert system program is used to estimate the demand for this study. The expert system facilitated a significant improvement in consumption behavior compared to ANN learning. A study was conducted to determine the efficacy of these two techniques. Measurements related to variance in Urea, MOP and Lime fertilizers appear to have high average predictability. It is a method, a set of knowledge, the programming of data exchange specifications and the integration of the Geographic Information System, expert knowledge and analysis programs. With this approach and its basic principle of traditional agriculture, even in hilly or remote areas, it is possible to identify fixed ways of using fertilizers and maximize the benefits of the least quantity, which is very useful in predicting the requirements for agricultural chemicals over smaller and more dispersed farms. The expert advice suggests that better methods should be used in the agricultural system. Our report will allow the government to determine whether or not there is a danger of using unbalanced fertilizers. This is going to be very useful for second-class growers. newlineKeywords: Expert System, Agriculture, Data Aggregation, Artificial Intelligence. Support Vector Machi