Computational Intelligence for a Greener Future: Innovations in Renewable Energy Systems (eBook)

Integrating AI and Behavioral Insights to Drive Economic Efficiency and Sustainability
Artikelnummer: 978-3-032-06732-6
Einband: PDF
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
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This book aims to explore the intersection of computational intelligence techniques and renewable energy technologies, serving as a valuable resource for researchers, engineers, and policymakers. By compiling cutting-edge research and innovative applications, it seeks to demonstrate how CI can contribute to a more sustainable future, highlighting both theoretical advancements, practical implementations, and future directions.

Nowadays, as the world faces the pressing challenges of climate change and the depletion of fossil fuel resources, the shift toward decarbonization and renewable energy systems has become a vital priority. Innovations in computational intelligence (CI) offer promising opportunities to optimize and manage energy production, distribution, and consumption. By leveraging techniques like nature-inspired optimization algorithms, fuzzy methods, machine learning, and clustering, researchers and practitioners can enhance the efficiency and management of renewable energy systems.

This book aims to explore the intersection of computational intelligence techniques and renewable energy technologies, serving as a valuable resource for researchers, engineers, and policymakers. By compiling cutting-edge research and innovative applications, it seeks to demonstrate how CI can contribute to a more sustainable future, highlighting both theoretical advancements, practical implementations, and future directions.

Nowadays, as the world faces the pressing challenges of climate change and the depletion of fossil fuel resources, the shift toward decarbonization and renewable energy systems has become a vital priority. Innovations in computational intelligence (CI) offer promising opportunities to optimize and manage energy production, distribution, and consumption. By leveraging techniques like nature-inspired optimization algorithms, fuzzy methods, machine learning, and clustering, researchers and practitioners can enhance the efficiency and management of renewable energy systems.

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VerlagSpringer International Publishing
EinbandPDF
Erscheinungsjahr2026
Seitenangabe533 S.
AusgabekennzeichenEnglisch
AbbildungenVII, 533 p. 131 illus., 111 illus. in color.
Masse22'847 KB
PlattformPDF
ReiheStudies in Computational Intelligence; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics
AutorMellal, Mohamed Arezki (Hrsg.) / Nojima, Yusuke (Hrsg.) / Masuyama, Naoki (Hrsg.)

Alle Bände der Reihe "Studies in Computational Intelligence; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics (R0)"

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