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Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities.

, , , , , , , , , , , , , , , , , , and . Environ. Model. Softw., (2019)

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Control Theoretical Modeling of Trust-Based Decision Making in Food-Energy-Water Management., , , , , and . CISIS, volume 1194 of Advances in Intelligent Systems and Computing, page 97-107. Springer, (2020)Fuzzy and deep learning approaches for user modeling in wetland design., , and . SMC, page 2133-2138. IEEE, (2016)Interactive Watershed Optimization in the Presence of Spatially-varying and Uncertain Stakeholder Preferences., , and . ICHMS, page 1-6. IEEE, (2020)Why the 'selfish' optimizing agents could solve the decentralized reinforcement learning problems., , and . AI Commun., 32 (2): 143-159 (2019)Interactive Genetic Algorithm with Mixed Initiative Interaction for multi-criteria ground water monitoring design., and . Appl. Soft Comput., 12 (1): 182-195 (2012)User modeling with limited data: Application to stakeholder-driven watershed design., , and . SMC, page 3855-3860. IEEE, (2014)Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities., , , , , , , , , and 9 other author(s). Environ. Model. Softw., (2019)Trust-Based Game-Theoretical Decision Making for Food-Energy-Water Management., , , , and . BWCCA, volume 97 of Lecture Notes in Networks and Systems, page 125-136. Springer, (2019)Decentralized and partially decentralized reinforcement learning for designing a distributed wetland system in watersheds., , and . SMC, page 271-276. IEEE, (2011)A Case-Based Micro Interactive Genetic Algorithm (CBMIGA) for interactive learning and search: Methodology and application to groundwater monitoring design., and . Environ. Model. Softw., 25 (10): 1176-1187 (2010)