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Open Access Journal Article

Adaptive Neuro-Fuzzy Inference Systems for Predicting Crop Yield in Changing Climate

by David White 1,*
1
David White
*
Author to whom correspondence should be addressed.
TASC  2019, 3; 1(1), 3; https://doi.org/10.69610/j.tasc.20191030
Received: 28 August 2019 / Accepted: 26 September 2019 / Published Online: 30 October 2019
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Abstract

The paper explores the application of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) in predicting crop yield under the evolving climatic conditions. The study aims to develop a robust predictive model that can effectively account for the complexities of climate variability and its impact on agricultural productivity. By integrating artificial neural networks and fuzzy logic, ANFIS provides a flexible framework that can handle both numerical and qualitative data, making it particularly suitable for agricultural scenarios where precision is crucial. The empirical analysis involves a dataset encompassing various climatic parameters, soil characteristics, and historical crop yield data. The results indicate that ANFIS demonstrates significant accuracy and reliability in forecasting crop yields, thereby offering valuable insights for farmers and policymakers in making informed decisions about crop management and adaptation strategies in response to climate change. The findings underscore the potential of ANFIS as a powerful tool for sustainable agriculture and resource management in a dynamically altering environment.

Keywords: Adaptive Neuro-Fuzzy Inference Systems, ANFIS, Crop Yield Prediction, Climate Change, Agriculture, Sustainable Resource Management..;
Copyright: © 2019 by White. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
White, D. Adaptive Neuro-Fuzzy Inference Systems for Predicting Crop Yield in Changing Climate. Transactions on Applied Soft Computing, 2019, 1, 3. https://doi.org/10.69610/j.tasc.20191030
AMA Style
White D. Adaptive Neuro-Fuzzy Inference Systems for Predicting Crop Yield in Changing Climate. Transactions on Applied Soft Computing; 2019, 1(1):3. https://doi.org/10.69610/j.tasc.20191030
Chicago/Turabian Style
White, David 2019. "Adaptive Neuro-Fuzzy Inference Systems for Predicting Crop Yield in Changing Climate" Transactions on Applied Soft Computing 1, no.1:3. https://doi.org/10.69610/j.tasc.20191030
APA style
White, D. (2019). Adaptive Neuro-Fuzzy Inference Systems for Predicting Crop Yield in Changing Climate. Transactions on Applied Soft Computing, 1(1), 3. https://doi.org/10.69610/j.tasc.20191030

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