Machine Learning-Based Forecasting Technique for Crop Yield: A Study

被引:0
|
作者
Ragunath, R. [1 ]
Narmadha, N. [2 ]
Rathipriya, R. [1 ]
机构
[1] Periyar Univ, Dept Comp Sci, Salem 636011, India
[2] Sri Sarada Coll Women, Dept Comp Sci, Salem 636016, India
关键词
Agriculture; Machine learning; Classification; Clustering; Yield prediction; Ensemble learning; MODEL;
D O I
10.1007/978-981-19-3590-9_21
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Agriculture plays an important role in the global economy and the survival of the species. Agriculture is an important part of the Indian economy, with agriculture providing a living for more than half of the Indian people. Crop yield forecasting is an important agricultural problem. Agricultural yield depends primarily on weather conditions (rainfall, temperature, etc.), pesticides. Machine learning algorithm and methods used for weather forecasting and crop yield prediction very frequently for the better results. Several research for agricultural development has been advocated, with the goal of developing an accurate and efficient model for predicting crop yields. This research investigates the various machine learning approaches used in agricultural yield estimation and gives a complete analysis based on the techniques' accuracy.
引用
收藏
页码:277 / 289
页数:13
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