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Networks of Learning Automata
Networks of Learning Automata: Techniques for Online Stochastic Optimization is a comprehensive account of learning automata models with emphasis on multiautomata systems. It considers synthesis of complex learning structures from simple building blocks and uses stochastic algorithms for refining probabilities of selecting actions. Mathematical analysis of the behavior of games and feedforward networks is provided. Algorithms considered here can be used for online optimization of systems based on noisy measurements of performance index. Also, algorithms that assure convergence to the global optimum are presented. Parallel operation of automata systems for improving speed of convergence is described. The authors also include extensive discussion of how learning automata solutions can be constructed in a variety of applications.
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)
This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including adaptive observations, sensitivity analysis, parameter estimation and AI applications. The book is useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
Dynamic Data Assimilation
Publisher description
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III)
This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)
This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
Mathematics for Large Scale Computing
During recent years a great deal of interest has been devoted to large scale computing applications. This has occurred in great part because of the introduction of advanced high performance computer architectures. The book contains survey articles as well as chapters on specific research applications, development and analysis of numerical algorithms, and performance evaluation of algorithms on advanced architectures. The effect of specialized architectural features on the performance of large scale computation is also considered by several authors. Several areas of applications are represented, including the numerical solution of partial differential equations, iterative techniques for large structured problems, the numerical solution of boundary value problems for ordinary differential equations, numerical optimization, and numerical quadrature. Mathematical issues in computer architecture are also presented, including the description of grey codes for generalized hypercubes. The results presented in this volume give, in our opinion, a representative picture of today’s state of the art in several aspects of large scale computing.
Algorithms and Computation
This book constitutes the refereed proceedings of the 16th International Symposium on Algorithms and Computation, ISAAC 2005, held in Sanya, Hainan, China in December 2005. The 112 revised full papers presented were carefully reviewed and selected from 549 submissions. The papers are organized in topical sections on computational geometry, computational optimization, graph drawing and graph algorithms, computational complexity, approximation algorithms, internet algorithms, quantum computing and cryptography, data structure, computational biology, experimental algorithm mehodologies and online algorithms, randomized algorithms, parallel and distributed algorithms.
Air Pollution Modeling and its Application XXV
Current developments in air pollution modelling are explored as a series of contributions from researchers at the forefront of their field. This newest contribution on air pollution modelling and its application is focused on local, urban, regional and intercontinental modelling; long term modelling and trend analysis; data assimilation and air quality forecasting; model assessment and evaluation; aerosol transformation. Additionally, this work also examines the relationship between air quality and human health and the effects of climate change on air quality. This Work is a collection of selected papers presented at the 35th International Technical Meeting on Air Pollution Modeling and its Application, held in Chania (Crete), Greece, Oct 3-7, 2016. The book is intended as reference material for students and professors interested in air pollution modelling at the graduate level as well as researchers and professionals involved in developing and utilizing air pollution models.
