Multi-objective optimization of water treatment operations for disinfection byproduct control
暂无分享,去创建一个
Joseph R. Kasprzyk | William J. Raseman | R. Scott Summers | Amanda K. Hohner | Fernando L. Rosario-Ortiz | R. Summers | J. Kasprzyk | A. Hohner | F. Rosario‐Ortiz | W. Raseman
[1] Luuk C. Rietveld,et al. Water treatment simulators , 2008 .
[2] A. Gandomi,et al. Coagulation modeling using artificial neural networks to predict both turbidity and DOM-PARAFAC component removal , 2015 .
[3] Dragan Savic,et al. Booster Disinfection of Water Supply Networks: Multiobjective Approach , 2004 .
[4] Patrick M. Reed,et al. An open source framework for many-objective robust decision making , 2015, Environ. Model. Softw..
[5] Amanda Schmidt,et al. Water treatment implications after the High Park Wildfire, Colorado , 2014 .
[6] John Bridgeman,et al. Optimisation of water treatment works performance using genetic algorithms , 2017 .
[7] J. Sohn,et al. Extensions and Verification of the Water Treatment Plant Model for Disinfection By-Product Formation. , 2000 .
[8] Joseph R. Kasprzyk,et al. An iterative approach to multi-objective engineering design: Optimization of engineered injection and extraction for enhanced groundwater remediation , 2015, Environ. Model. Softw..
[9] I. Delpla,et al. Impacts of climate change on surface water quality in relation to drinking water production. , 2009, Environment international.
[10] T. Devi Prasad,et al. Multiobjective Genetic Algorithms for Design of Water Distribution Networks , 2004 .
[11] Trevor Hastie,et al. An Introduction to Statistical Learning , 2013, Springer Texts in Statistics.
[12] P. Reed,et al. Managing population and drought risks using many‐objective water portfolio planning under uncertainty , 2009 .
[13] S. Schneider,et al. Climate Change 2001: Synthesis Report: A contribution of Working Groups I, II, and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change , 2001 .
[14] Avi Ostfeld,et al. Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions , 2014, Environ. Model. Softw..
[15] D. Burn,et al. Improved K-Nearest Neighbor Weather Generating Model , 2007 .
[16] Assela Pathirana,et al. Modelling formation of disinfection by-products in water distribution: optimisation using a multi-objective evolutionary algorithm , 2012 .
[17] Patrick M. Reed,et al. Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework , 2013, Evolutionary Computation.
[18] R. Wilby,et al. A review of the potential impacts of climate change on surface water quality , 2009 .
[19] Avi Ostfeld,et al. Optimal design and operation of booster chlorination stations layout in water distribution systems. , 2014, Water research.
[20] B. Rajagopalan,et al. Simulating ensembles of source water quality using a K-nearest neighbor resampling approach. , 2009, Environmental science & technology.
[21] R. Summers,et al. Drinking water treatment response following a Colorado wildfire. , 2016, Water research.
[22] M. Edwards. Predicting DOC removal during enhanced coagulation , 1997 .
[23] Joseph R. Kasprzyk,et al. Evolutionary multiobjective optimization in water resources: The past, present, and future , 2012 .
[24] B. Rajagopalan,et al. Nearest neighbor time series bootstrap for generating influent water quality scenarios , 2020, Stochastic Environmental Research and Risk Assessment.
[25] Upmanu Lall,et al. A k‐nearest‐neighbor simulator for daily precipitation and other weather variables , 1999 .
[26] Luuk C. Rietveld,et al. Modelling of drinking water treatment processes within the Stimela environment , 2000 .
[27] Philip C. Singer,et al. Performance and analysis of tracer tests to determine compliance of a disinfection scheme with the SWTR , 1990 .
[28] Wenyan Wu,et al. Accounting for Greenhouse Gas Emissions in Multiobjective Genetic Algorithm Optimization of Water Distribution Systems , 2010 .
[29] P. Westerhoff,et al. Predicting disinfection by-product formation potential in water. , 2010, Water research.
[30] Joseph R. Kasprzyk,et al. Parasol: an open source, interactive parallel coordinates library for multi-objective decision making , 2019, Environ. Model. Softw..
[31] Avi Ostfeld,et al. The Battle of the Water Sensor Networks (BWSN): A Design Challenge for Engineers and Algorithms , 2008 .
[32] Mark Sterling,et al. An assessment of static and dynamic models to predict water treatment works performance , 2016 .
[33] Stephen J. Stanley,et al. Real-Time Water Treatment Process Control with Artificial Neural Networks , 1999 .
[34] Patrick M. Reed,et al. Many objective visual analytics: rethinking the design of complex engineered systems , 2013 .
[35] R. Farmani,et al. Evolutionary multi-objective optimization in water distribution network design , 2005 .
[36] Kalyanmoy Deb,et al. Multi-objective Optimization , 2014 .
[37] Patrick M. Reed,et al. A framework for Visually Interactive Decision-making and Design using Evolutionary Multi-objective Optimization (VIDEO) , 2007, Environ. Model. Softw..
[38] Marios M. Polycarpou,et al. Optimal Scheduling of Booster Disinfection in Water Distribution Systems , 1998 .
[39] S. Lele,et al. The association between extreme precipitation and waterborne disease outbreaks in the United States, 1948-1994. , 2001, American journal of public health.
[40] Upmanu Lall,et al. A Nearest Neighbor Bootstrap For Resampling Hydrologic Time Series , 1996 .
[41] David E. Rosenberg,et al. Blended near‐optimal alternative generation, visualization, and interaction for water resources decision making , 2015 .
[42] Z. Chowdhury,et al. Developing a Computer Model to Simulate DBP Formation During Water Treatment , 1992 .
[43] J. Kasprzyk,et al. Emerging investigators series: a critical review of decision support systems for water treatment: making the case for incorporating climate change and climate extremes , 2017 .
[44] Stuart J. Khan,et al. Extreme weather events: Should drinking water quality management systems adapt to changing risk profiles? , 2015, Water research.