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This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation. He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability. Python labs enable the readers to experiment and consolidate their understanding. The book includes homework, solutions, and Jupyter notebooks. This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks. For ancillaries related to this book, including examples of Python demos and also Python labs used in Berkeley, please email Mary James at mary.james@springer.com. This is an open access book.

Maths for computer scientists --- Communications engineering / telecommunications --- Maths for engineers --- Probability & statistics --- Probability and Statistics in Computer Science --- Communications Engineering, Networks --- Mathematical and Computational Engineering --- Probability Theory and Stochastic Processes --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences --- Mathematical and Computational Engineering Applications --- Probability Theory --- Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences --- Applied probability --- Hypothesis testing --- Detection theory --- Expectation maximization --- Stochastic dynamic programming --- Machine learning --- Stochastic gradient descent --- Deep neural networks --- Matrix completion --- Linear and polynomial regression --- Open Access --- Mathematical & statistical software --- Stochastics

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During the past five decades, we have witnessed a tremendous evolution in water resource system management. Three characteristics of this evolution are of particular note: First, the application of the systems approach to complex water management problems has been established as one of the most important advances in the field of water resource management. Second, the past five decades have brought a remarkable transformation of attitude in the water resource management community towards environmental concerns and action to address these concerns. Third, applying the principles of sustainability to water resource decision-making requires major changes in the objectives on which decisions are based, and an understanding of the complicated inter-relationships between existing ecological, economic, and social factors. The Special Issue includes 15 contributions that offer insights into contemporary problems, approaches, and issues related to the management of complex water resources systems. It will be presumptuous to say that these 15 contributions characterize the success or failure of the systems approach to support water resources decision-making. However, these contributions offer interesting lessons from current experiences and highlight possible future work.

History of engineering & technology --- system dynamics --- system analysis --- complex water system --- uncertainty assessment --- climate change --- regional climate models --- averaging procedures --- HEC-HMS --- Lim river --- Lim water systems --- artificial recharge --- groundwater --- treated wastewater --- freshwater resources --- water footprint --- water management --- wine production --- winemaking sector --- Italy --- SuDS --- decision-making --- Soft Systems --- ANP --- modelling --- stakeholder --- systems analyses --- water resources --- planning --- management --- implementation --- political processes --- innovation --- impact --- multi-purpose dam --- water resources systems --- performance-based engineering --- simulation --- resilience --- disaster --- risk --- perception --- community --- Canada --- integrated urban watershed management --- group decision-support system --- risk analysis --- group consensus --- Kashafroud watershed --- water policy --- water portfolio planning --- water resources management --- systems assessment --- adaptive capacity --- coupled human-natural systems --- integrated water resources management --- sociohydrology --- modeling perspectives --- agent-based modeling --- differential equations --- uncertainty --- artificial intelligence --- machine learning --- water resource modelling --- multiobjective optimisation --- river abstraction --- reservoir operation --- stochastic dynamic programming --- fuzzy optimization --- reservoir-river system --- water quantity-quality management --- socio-hydrology --- hydro-sociology --- human-water systems --- human-nature systems --- social-ecological systems --- CHANS --- SES --- socio-hydrologic modeling --- IWRM --- hydrology --- multireservoir operations --- optimization --- multi-agent reinforcement learning --- aggregation-decomposition --- neural networks --- systems --- complexity --- system dynamics --- system analysis --- complex water system --- uncertainty assessment --- climate change --- regional climate models --- averaging procedures --- HEC-HMS --- Lim river --- Lim water systems --- artificial recharge --- groundwater --- treated wastewater --- freshwater resources --- water footprint --- water management --- wine production --- winemaking sector --- Italy --- SuDS --- decision-making --- Soft Systems --- ANP --- modelling --- stakeholder --- systems analyses --- water resources --- planning --- management --- implementation --- political processes --- innovation --- impact --- multi-purpose dam --- water resources systems --- performance-based engineering --- simulation --- resilience --- disaster --- risk --- perception --- community --- Canada --- integrated urban watershed management --- group decision-support system --- risk analysis --- group consensus --- Kashafroud watershed --- water policy --- water portfolio planning --- water resources management --- systems assessment --- adaptive capacity --- coupled human-natural systems --- integrated water resources management --- sociohydrology --- modeling perspectives --- agent-based modeling --- differential equations --- uncertainty --- artificial intelligence --- machine learning --- water resource modelling --- multiobjective optimisation --- river abstraction --- reservoir operation --- stochastic dynamic programming --- fuzzy optimization --- reservoir-river system --- water quantity-quality management --- socio-hydrology --- hydro-sociology --- human-water systems --- human-nature systems --- social-ecological systems --- CHANS --- SES --- socio-hydrologic modeling --- IWRM --- hydrology --- multireservoir operations --- optimization --- multi-agent reinforcement learning --- aggregation-decomposition --- neural networks --- systems --- complexity

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

During the past five decades, we have witnessed a tremendous evolution in water resource system management. Three characteristics of this evolution are of particular note: First, the application of the systems approach to complex water management problems has been established as one of the most important advances in the field of water resource management. Second, the past five decades have brought a remarkable transformation of attitude in the water resource management community towards environmental concerns and action to address these concerns. Third, applying the principles of sustainability to water resource decision-making requires major changes in the objectives on which decisions are based, and an understanding of the complicated inter-relationships between existing ecological, economic, and social factors. The Special Issue includes 15 contributions that offer insights into contemporary problems, approaches, and issues related to the management of complex water resources systems. It will be presumptuous to say that these 15 contributions characterize the success or failure of the systems approach to support water resources decision-making. However, these contributions offer interesting lessons from current experiences and highlight possible future work.

system dynamics --- system analysis --- complex water system --- uncertainty assessment --- climate change --- regional climate models --- averaging procedures --- HEC-HMS --- Lim river --- Lim water systems --- n/a --- artificial recharge --- groundwater --- treated wastewater --- freshwater resources --- water footprint --- water management --- wine production --- winemaking sector --- Italy --- SuDS --- decision-making --- Soft Systems --- ANP --- modelling --- stakeholder --- systems analyses --- water resources --- planning --- management --- implementation --- political processes --- innovation --- impact --- multi-purpose dam --- water resources systems --- performance-based engineering --- simulation --- resilience --- disaster --- risk --- perception --- community --- Canada --- integrated urban watershed management --- group decision-support system --- risk analysis --- group consensus --- Kashafroud watershed --- water policy --- water portfolio planning --- water resources management --- systems assessment --- adaptive capacity --- coupled human–natural systems --- integrated water resources management --- sociohydrology --- modeling perspectives --- agent-based modeling --- differential equations --- uncertainty --- artificial intelligence --- machine learning --- water resource modelling --- multiobjective optimisation --- river abstraction --- reservoir operation --- stochastic dynamic programming --- fuzzy optimization --- reservoir-river system --- water quantity-quality management --- socio-hydrology --- hydro-sociology --- human-water systems --- human-nature systems --- social-ecological systems --- CHANS --- SES --- socio-hydrologic modeling --- IWRM --- hydrology --- multireservoir operations --- optimization --- multi-agent reinforcement learning --- aggregation–decomposition --- neural networks --- systems --- complexity --- coupled human-natural systems --- aggregation-decomposition