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This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. These methods have become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics. The coverage is comprehensive, ranging from the underlying theory to computational implementation, methodology, and diverse applications in various areas of science. This is achieved by describing SMC algorithms as particular cases of a general framework, which involves concepts such as Feynman-Kac distributions, and tools such as importance sampling and resampling. This general framework is used consistently throughout the book. Extensive coverage is provided on sequential learning (filtering, smoothing) of state-space (hidden Markov) models, as this remains an important application of SMC methods. More recent applications, such as parameter estimation of these models (through e.g. particle Markov chain Monte Carlo techniques) and the simulation of challenging probability distributions (in e.g. Bayesian inference or rare-event problems), are also discussed. The book may be used either as a graduate text on Sequential Monte Carlo methods and state-space modeling, or as a general reference work on the area. Each chapter includes a set of exercises for self-study, a comprehensive bibliography, and a “Python corner,” which discusses the practical implementation of the methods covered. In addition, the book comes with an open source Python library, which implements all the algorithms described in the book, and contains all the programs that were used to perform the numerical experiments.

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The book comprehensively investigates the relationship between critical urban form and fabric parameters and urban microclimate in the high-rise urban environment that prevails in Asian megacitiessuch as Shanghai. It helps readers gain a deeper understanding ofclimate-responsive urban design strategies and tactics for effectively mitigating the negative impacts of deteriorating urban thermal environments on pedestrian thermal comfort, outdoor air quality and building energy consumption. It also reviews the latest advances in urban climate research, with a focus on the challenges in terms of outdoor space comfort, health, and livability posed by the high-rise and high-density development in emerging Asian megacities, and proposes an integrated framework in response to the pressing need for microclimate research. It then presents a series of studies on high-rise residential and non-residential urban neighborhoods and districtsbased on instrumented field study, validated numerical simulation, and spatial analysis using a GIS platform. The book includes extensive, valuable experimental data presented in a clear and concise manner. The thermal atlas methodology based on empirical modeling and spatial analysis described is a useful climate-responsive design tool for both urban designer and architects. As such, the book is of particular interest to researchers, professionals, and graduate students in the fields of urban planning and design, building science and urban climatology.

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