Fuzzy Logic based Crop Yield Prediction using Temperature and Rainfall parameters predicted through ARMA, SARIMA, and ARMAX models
- Resource Type
- Conference
- Authors
- Bang, Shivam; Bishnoi, Rajat; Chauhan, Ankit Singh; Dixit, Akshay Kumar; Chawla, Indu
- Source
- 2019 Twelfth International Conference on Contemporary Computing (IC3) Contemporary Computing (IC3), 2019 Twelfth International Conference on. :1-6 Aug, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
General Topics for Engineers
Geoscience
Robotics and Control Systems
Signal Processing and Analysis
Predictive models
Agriculture
Data models
Autoregressive processes
Temperature distribution
Mathematical model
ARMA
SARIMA
ARMAX
Temperature prediction
Rainfall prediction
Fuzzy Logic
Crop Yield Prediction
- Language
- ISSN
- 2572-6129
Agriculture plays a significant role in the economy of India. This makes crop yield prediction an important task to help boost India's growth. Crops are sensitive to various weather phenomena such as temperature and rainfall. Therefore, it becomes crucial to include these features when predicting the yield of a crop. Weather forecasting is a complicated process. In this work, three methods are used to forecast- ARMA (Auto Regressive Moving Average), SARIMA (Seasonal Auto Regressive Integrated Moving Average) and ARMAX (ARMA with exogenous variables). The performance of the three is compared and the best model is used to predict rainfall and temperature which are in turn used to predict the crop yield based on a fuzzy logic model.