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Prediction of Crop Yield Using Fuzzy-Neural System

  • Bindu GargEmail author
  • Tanya Sah
Conference paper
Part of the EAI/Springer Innovations in Communication and Computing book series (EAISICC)

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.

Keywords

Fuzzy logic Rice yield forecasting Neural network Back propagation 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer Engineering DepartmentBharati Vidyapeeth (Deemed to be University) College of EngineeringPuneIndia
  2. 2.Tanya Sah Senior Software Engineer Globallogic India Pvt. LtdNoidaIndia

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