MACHINE LEARNING TECHNIQUES FOR CROP YIELD PREDICTION IN INDIAN AGRICULTURE
Geetesh Challur
, G Ravi Kumar , Pradhan Babu Tammana
neural network, Machine Learning, Time series analysis, Crop yield prediction,
Machine learning techniques contribute an important part in agricultural crop production and this paper analyses to reevaluate the research findings on the application of it. This is a novel approach to agricultural crop production management which is a decision taking tool. Important policy choices, such as import-export, price marketing distribution, etc., require accurate and timely crop production estimates, which are given by the directorate of economics and statistics. However, it is acknowledged that these estimations are not objective since they require a great deal of descriptive evaluation based on several qualitative aspects. Consequently, there is a need for realistic crop output forecasts that are supported by solid statistical evidence. This advancement in computers and data storage has produced vast quantities of data. In this study, a strategy for crop selection based on weather and soil factors is proposed to optimize agricultural output. It also recommends the optimal planting timing for compatible crops based on seasonal weather predictions. For weather forecasting, machine learning systems such as the recurrent neural network and the Random forest classification algorithm are utilized. The results of the suggested approach for weather forecasting are compared to those of a traditional artificial neural network, which demonstrates superior performance for each of the specified weather parameters. Presented are agricultural applications of time series analysis, Markov chain model, k-means clustering, k closest neighbor, and support vector machine.
"MACHINE LEARNING TECHNIQUES FOR CROP YIELD PREDICTION IN INDIAN AGRICULTURE", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 11, page no.475 - 482, November-2022, Available :https://ijsdr.org/papers/IJSDR2211075.pdf
Volume 7
Issue 11,
November-2022
Pages : 475 - 482
Paper Reg. ID: IJSDR_202578
Published Paper Id: IJSDR2211075
Downloads: 000347338
Research Area: Computer Science & Technology
Country: Jharkhand, Jharkhand, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
