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Advanced Computational Intelligence for Climate Change Adaptation
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Author(s): Imdad Ali Shah (FEST Department, Iqra University, Karachi, Pakistan)and N. Z. Jhanjhi (School of Computing Science and Engineering, Taylor's University, Malaysia)
Copyright: 2026
Pages: 12
Source title:
Advances in Computational Intelligence for Climate Change Security and Sustainability
Source Author(s)/Editor(s): Imdad Ali Shah (School of Computing Science, Taylor’s University, Malaysia)and N.Z. Jhanjhi (School of Computing Science, Taylor’s University, Malaysia)
DOI: 10.4018/979-8-3693-9132-7.ch002
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Abstract
Climate change poses an unprecedented threat to ecosystems, human livelihoods, and global sustainability. Addressing this challenge requires innovative approaches that go beyond traditional methods. This chapter also focuses on the role of advanced Computational Intelligence encompassing Machine Learning, deep learning, evolutionary algorithms, and fuzzy systems in facilitating effective climate change adaptation strategies. By integrating large-scale climate data, environmental models, and socioeconomic parameters, ACI enables predictive analytics, risk assessment, and decision-support systems tailored to dynamic climate conditions. Furthermore, this chapter also highlights recent advancements from the past five years, showcasing how computational intelligence is being leveraged across disciplines to build resilience and support sustainable adaptation pathways. Challenges such as data uncertainty, model interpretability, and ethical considerations are discussed, along with future research directions.
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