DocumentCode :
1884607
Title :
Crop Selection Method to maximize crop yield rate using machine learning technique
Author :
Kumar, Rakesh ; Singh, M.P. ; Kumar, Prabhat ; Singh, J.P.
Author_Institution :
Dept. of CSE, NIT, Patna, India
fYear :
2015
fDate :
6-8 May 2015
Firstpage :
138
Lastpage :
145
Abstract :
Agriculture planning plays a significant role in economic growth and food security of agro-based country. Se- lection of crop(s) is an important issue for agriculture planning. It depends on various parameters such as production rate, market price and government policies. Many researchers studied prediction of yield rate of crop, prediction of weather, soil classification and crop classification for agriculture planning using statistics methods or machine learning techniques. If there is more than one option to plant a crop at a time using limited land resource, then selection of crop is a puzzle. This paper proposed a method named Crop Selection Method (CSM) to solve crop selection problem, and maximize net yield rate of crop over season and subsequently achieves maximum economic growth of the country. The proposed method may improve net yield rate of crops.
Keywords :
crops; economics; learning (artificial intelligence); optimisation; pattern classification; production planning; soil; CSM; agriculture planning; agro-based country; crop classification; crop selection method; crop yield rate maximization; economic growth; food security; government policies; land resource; machine learning technique; market price; production rate; soil classification; statistics; weather prediction; Agriculture; Decision trees; Prediction algorithms; Predictive models; Production; Support vector machines; Vegetation; CSM (Crop Selection Method); Climate; GBDT (Gradient Boosted Decision Tree); RGF (Regularized Greedy Forest); Soil composition; regression problem; regularization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), 2015 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-9854-8
Type :
conf
DOI :
10.1109/ICSTM.2015.7225403
Filename :
7225403
Link To Document :
بازگشت