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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title:	DEVELOPMENT OF RICE CROP YIELD FORECASTING USING DIFFERENT REGRESSION TECHNIQUE AND ARTIFICIAL NEURAL NETWORK APPROACH FOR JALPAIGURI, WEST BENGAL
Authors Name:	SHYAMAL MAHADANI , Dr. Abhishek James
Unique Id:	IJSDR2210154
Published In:	Volume 7 Issue 10, October-2022
Abstract:	Crop yield forecasting under the present climate change scenario needs an effective model and its parameter that how crop respond to the weather variable. By incorporating regression models and Artificial Neural Networks (ANN), one can make highly satisfactory predictions of rice crop yield. Crop yield forecasting using regression and artificial neural network is developed through SPSS package software which will help agronomists and farmers to get accurate crop yield reports from various agricultural sources. In this study, the focus is on the development of regression techniques and artificial neural network in agricultural field. Historical rice crop yield data and weather data of past fifteen years (2005-2019) were collected for Jalpaiguri District of West Bengal. Analysis was carried out by fixing 15 years of dataset for calibration (80%) and remaining dataset for the validation (20%). Stepwise linear regression technique and neural network used for predicting the yield of rice crop. Performance analysis
Keywords:	Yield forecasting, weather variable, ANN, nRMSE, kharif rice
Cite Article:	"DEVELOPMENT OF RICE CROP YIELD FORECASTING USING DIFFERENT REGRESSION TECHNIQUE AND ARTIFICIAL NEURAL NETWORK APPROACH FOR JALPAIGURI, WEST BENGAL", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 10, page no.912 - 916, October-2022, Available :http://www.ijsdr.org/papers/IJSDR2210154.pdf
Downloads:	000338719
Publication Details:	Published Paper ID: IJSDR2210154 Registration ID:202229 Published In: Volume 7 Issue 10, October-2022 DOI (Digital Object Identifier): Page No: 912 - 916 Publisher: IJSDR \| www.ijsdr.org ISSN Number: 2455-2631

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