Computational Intelligence in Sustainable Computing and Optimization

Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resources. Computational intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, Cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. Data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modelling, data analysis and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable. The field of optimization is well-known and has a diverse range of applications, including route finding problems, medical treatment, construction, finance, accounting, engineering, and maintenance schedules. Optimizing real-world problems requires understanding their nature, grouping them properly, and employing appropriate techniques that can resolve them efficiently. Nature-inspired computational algorithms have been shown to provide robust solutions for emerging and substantiated problems by utilizing heuristic algorithms. Heuristic techniques aim to find the optimal solution to the query in a timely manner. There are several categories of computational intelligence based on nature, including artificial immune systems, evolutionary algorithms, swarm intelligence, artificial neural networks, and geoscience-based algorithms, and these are applied by the authors of the book to solve various problems in sustainable computing.

• Presents computational intelligence-based data analysis for sustainable computing applications such as pattern recognition, biomedical imaging, sustainable cities, sustainable transport, sustainable agriculture, and sustainable financial management
• Develops research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resources
• Includes three foundational chapters dedicated to providing an overview of computational intelligence and optimization techniques and how they can be applied to sustainable computing