Fuzzy Logic for Modeling Climate Changes: Overcoming Uncertainty in Environmental Forecasts

Abdullayeva S., Hacızadə S., Məmmədova A., Bədəlova S., Kərimova S.

JOURNAL OF INTELLIGENT AND FUZZY SYSTEMS, no.1531, pp.278-285, 2025 (SCI-Expanded, Scopus)

  • Publication Type: Article / Article
  • Publication Date: 2025
  • Doi Number: 10.1007/978-3-031-98304-7_32
  • Journal Name: JOURNAL OF INTELLIGENT AND FUZZY SYSTEMS
  • Journal Indexes: Applied Science & Technology Source, Scopus, Aerospace Database, Science Citation Index Expanded (SCI-EXPANDED), Academic Search Premier, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.278-285
  • Open Archive Collection: Article
  • Azerbaijan State University of Economics (UNEC) Affiliated: Yes

Abstract

Climate change modeling is inherently complex and is often characterized by significant uncertainties due to dynamic and nonlinear interactions within environmental systems. Traditional modeling techniques struggle to control the inaccuracy and uncertainty about predicting climate change events. This article examines the application of fuzzy logic as an effective tool to address uncertainties in climate change modeling. Fuzzy logic provides a framework that can accommodate the uncertainty inherent in environmental data, allowing for more flexible and reliable predictions. By incorporating fuzzy logic into climate models, we improve the interpretability and reliability of predictions, especially in scenarios where there is incomplete or inaccurate data. The study demonstrates how fuzzy logic can improve the accuracy of environmental predictions, offering insights into temperature changes, greenhouse gas emissions, and extreme weather events. The results highlight the potential of fuzzy logic to contribute to more informed decision-making and policy development in the context of climate change.