Soft Computing for Sustainability Science - Cruz Corona, Carlos; SpringerLink (Online service) (Cham : Springer International Publishing : Imprint: Springer, 2018)
This book offers a timely snapshot of soft computing methodologies and their applications to various problems related to sustainability, including electric energy consumption; fault diagnosis; vessel fuel consumption; determining the best sites for new malls; maritime port projects; and ad-hoc vehicular networks. Further, it demonstrates how metaheuristics and machine learning methods, fuzzy linear programming, neural networks, computing with words, linguistic models and other soft computing methods can be efficiently used to solve real-world problems. Intended as a practice-oriented guide for students, researchers, and professionals working at the interface between computer science, industrial engineering, naval engineering, agriculture, and sustainable development / climate change research, it provides readers with a set of intelligent solutions, helping them answer a range of emerging questions related to sustainability. .
Soft Computing techniques and Sustainability Science, an introduction -- Vessels Fuel Consumption: a Data Analytics Perspective to Sustainability -- FuzzyCovering: a Spatial Decision Support System for solving fuzzy covering location problems -- A Fuzzy Location Problem based upon Georeferenced Data -- A review of the application to emergent subfields in viticulture of local reflectance and interactance spectroscopy combined with soft computing and multivariate analysis -- Consumer segmentation through multi-instance clustering time-series energy data from smart meters -- A multicriteria group decision model for ranking technology packages in agriculture -- A Linguistic 2-tuple based Environmental Impact Assessment for Maritime Port Projects: Application to Moa Port. .
Keywords: Computational intelligence; Management; Artificial intelligence; Mathematical optimization; Calculus of variations; Sustainability; Computational Intelligence; Management; Artificial Intelligence; Calculus of Variations and Optimization; Sustainability