Yield prediction system – a systematic approach for predicting agricultural commodity
Vikranth, K.
Yield prediction system – a systematic approach for predicting agricultural commodity - Vol.14(4), - Chennai ICT Academy 2024 - 3368-3372p.
In India, the agriculture is main profession for more than sixty percent
of the population. The stakeholders of agriculture in India, facing
plenty of problems that leads the people of the country to shift their
profession and lets them migrate towards urban area. So, need of
implementing technology in agriculture is must in future days because
as population is increasing in exponential form as the result huge
requirement of food and agricultural product. The data analytics will
play a significant role in agricultural dataset for implementing
prediction and recommendation system in the sector. Yield is one of the
factors to be considered in the agriculture that determines the wellness
and prosperity of the farmer. In this paper deals with prediction system
to predict yield of areca nut product in Puttur taluk, Dakshin Kannda
District, Karnataka state in India. The time series data analytics model
known as Auto Regressive Integrated Moving Average (ARIMA) model
is used for yield prediction system. The research is mainly focused on
forecasting of areca nut production for next four or five years in Puttur
taluk. It compares various ARIMA models with performance criteria
and selects best model for prediction purpose. The diagnostic check is
carried out to test the system performance After the prediction, then the
actual values and predicted values are compared and presented in the
form graphical representation.
Computer Engineering
Yield prediction system – a systematic approach for predicting agricultural commodity - Vol.14(4), - Chennai ICT Academy 2024 - 3368-3372p.
In India, the agriculture is main profession for more than sixty percent
of the population. The stakeholders of agriculture in India, facing
plenty of problems that leads the people of the country to shift their
profession and lets them migrate towards urban area. So, need of
implementing technology in agriculture is must in future days because
as population is increasing in exponential form as the result huge
requirement of food and agricultural product. The data analytics will
play a significant role in agricultural dataset for implementing
prediction and recommendation system in the sector. Yield is one of the
factors to be considered in the agriculture that determines the wellness
and prosperity of the farmer. In this paper deals with prediction system
to predict yield of areca nut product in Puttur taluk, Dakshin Kannda
District, Karnataka state in India. The time series data analytics model
known as Auto Regressive Integrated Moving Average (ARIMA) model
is used for yield prediction system. The research is mainly focused on
forecasting of areca nut production for next four or five years in Puttur
taluk. It compares various ARIMA models with performance criteria
and selects best model for prediction purpose. The diagnostic check is
carried out to test the system performance After the prediction, then the
actual values and predicted values are compared and presented in the
form graphical representation.
Computer Engineering