Applications of Machine Learning Techniques in Agricultural Crop Production: A Review Paper

Subhadra Mishra, Debahuti Mishra, Gour Hari Santra
2016 Indian Journal of Science and Technology  
Objective: This paper has been prepared as an effort to reassess the research studies on the relevance of machine learning techniques in the domain of agricultural crop production. Methods/Statistical Analysis: This method is a new approach for production of agricultural crop management. Accurate and timely forecasts of crop production are necessary for important policy decisions like import-export, pricing marketing distribution etc. which are issued by the directorate of economics and
more » ... cs. However one has understand that these prior estimates are not the objective estimates as these estimate requires lots of descriptive assessment based on many different qualitative factors. Hence there is a requirement to develop statistically sound objective prediction of crop production. That development in computing and information storage has provided large amount of data. Findings: The problem has been to intricate knowledge from this raw data , this has lead to the development of new approach and techniques such as machine learning that can be used to unite the knowledge of the data with crop yield evaluation. This research has been intended to evaluate these innovative techniques such that significant relationship can be found by their applications to the various variables present in the data base. Application / Improvement: The few techniques like artificial neural networks, Information Fuzzy Network, Decision Tree, Regression Analysis, Bayesian belief network. Time series analysis, Markov chain model, k-means clustering, k nearest neighbor, and support vector machine are applied in the domain of agriculture were presented. ISSN (Print) : 0974-6846 ISSN (Online) : 0974-5645 strongly declining growth still agriculture is statistically the broadest economic background and plays a significant role in the various socio economic frame work of India. Indian agriculture is affected by various factors such as climate, due to topography, historical, geographical, biological, political, and institutional and socio economic factors. As time passed there are variations in natural factors and nature of technology so policies also changed. So agriculture production performance also changes in drastic path and large gaps in different geographic loca-
doi:10.17485/ijst/2016/v9i38/95032 fatcat:wssmaerlavhk7eiymp23uzxvge