Abstract
Sustaining the burgeoning population is one of the major concerns of the twenty-first century. In one of its report FAO has clearly mentioned that as more developing countries enter into the developed phase, the purchasing power of the people will increase and there will be a constant increase in the food demand. To suffice the growing needs it is necessary to keep up with the demands. Addressing this situation a lot of research has been conducted in the past towards developing a robust time series forecasting algorithm. We in our research observed that due to the precarious nature of the crop yield Fuzzy time series has been particularly successful in predicting the crop production. In this chapter we propose a method to predict crop yield using fuzzy logic and artificial neural network and established the results by implementing it on rice yield dataset.
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Garg, B., Sah, T. (2020). Prediction of Crop Yield Using Fuzzy-Neural System. In: Haldorai, A., Ramu, A., Mohanram, S., Onn, C. (eds) EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-19562-5_21
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