Sustainability Analysis and Environmental Decision-Making Using Simulation, Optimization, and Computational Analytics

• Autore: Yeomans Julian Scott
• Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 electronic resource (248 p.)
• Soggetto topico: Research & information: general; Mathematics & science
• Soggetto non controllato: streamflow forecasting; C-vine copula; quantile regression; joint dependencies; water resource management; ecological relationship; factorial analysis; input-output analysis; optimal path; reduction; urban solid waste system; desalination; reverse osmosis; modelling; simulation; parameter estimation; seawater; boron; watershed management; nonpoint source pollution; point source pollution; water quality; pollutant loadings; South Texas; eco-efficiency; DEA; CO2 emissions; forecasting; ecological indicators; biomass gasification; machine learning; computer modeling; computer simulation; regression; model reduction; LASSO; classification; feature selection; financial market; investing; sustainability; renewable energy support; energy modeling; energy system design; generation profile; environmental footprint; renewable energy; electricity production; unlisted companies; Germany; feed-in tariff; biofuel policy; investment profitability analysis; the pay-off method; simulation decomposition; sourcing; operational flexibility; business aviation; turboprop; electric motor; specific power; Monte Carlo simulation; Iowa food-energy-water nexus; nitrogen export; system modeling; weather modeling; optimal allocation; interval; fuzzy; dynamic programming; water resources
• Persona (resp. second.): KozlovaMariia; YeomansJulian Scott
• Sommario/riassunto: Effective environmental decision-making is often challenging and complex, where final solutions frequently possess inherently subjective political and socio-economic components. Consequently, complex sustainability applications in the “real world” frequently employ computational decision-making approaches to construct solutions to problems containing numerous quantitative dimensions and considerable sources of uncertainty. This volume includes a number of such applied computational analytics papers that either create new decision-making methods or provide innovative implementations of existing methods for addressing a wide spectrum of sustainability applications, broadly defined. The disparate contributions all emphasize novel approaches of computational analytics as applied to environmental decision-making and sustainability analysis – be this on the side of optimization, simulation, modelling, computational solution procedures, visual analytics, and/or information technologies.
• Titolo autorizzato: Sustainability Analysis and Environmental Decision-Making Using Simulation, Optimization, and Computational Analytics
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557620403321
• Lo trovi qui: Univ. Federico II