Advances in Mathematical and Statistical Modeling
Enrique Castillo is a leading figure in several mathematical, statistical, and engineering fields, having contributed seminal work in such areas as statistical modeling, extreme value analysis, multivariate distribution theory, Bayesian networks, neural networks, functional equations, artificial intelligence, linear algebra, optimization methods, numerical methods, reliability engineering, as well as sensitivity analysis and its applications. Organized to honor Castillo's significant contributions, this volume is an outgrowth of the International Conference on Mathematical and Statistical Modeling and covers recent advances in the field. Also presented are applications to safety, reliability and life-testing, financial modeling, quality control, general inference, as well as neural networks and computational techniques.
Advances in Information Technologies for Electromagnetics
Simple tutorial chapters introduce the reader to cutting edge technologies, such as parallel and distributed computing, object-oriented technologies, grid computing, semantic grids, agent based computing and service-oriented architectures. On such bases, a variety of EM applications is proposed: 1) parallel FDTD codes (both for antenna analysis and for metamaterial applications), 2) grid computing for computational EM (CEM) (with applications to antenna arrays, wireless and remote-sensing systems) 3) mobile agents for parametric CEM modeling 4) complex/hybrid EM software environments (with applications to planar circuits, quasi-optical systems,…) 5) semantic grids for CAE of antennas arrays.
Advances in Evolutionary Computing for System Design
Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book includes thirteen chapters covering a wide area of topics in evolutionary computing and applications including: -Introduction to evolutionary computing in system design - Evolutionary neuro-fuzzy systems - Evolution of fuzzy controllers - Genetic algorithms for multi-classifier design -Evolutionary grooming of traffic -Evolutionary particle swarms -Fuzzy logic systems using genetic algorithms - Evolutionary algorithms and immune learning for neural network-based controller design - Distributed problem solving using evolutionary learning -Evolutionary computing within grid environment -Evolutionary game theory in wireless mesh networks - Hybrid multiobjective evolutionary algorithms for the sailor assignment problem - Evolutionary techniques in hardware optimization
Advances in Evolutionary Algorithms : Theory, Design and Practice
The goal of this book is to provide effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms. In this regard, five significant issues have been investigated: Bridging the gap between theory and practice of GEAs, thereby providing practical design guidelines. Demonstrating the practical use of the suggested road map. Offering a useful tool to significantly enhance the exploratory power in time-constrained and memory-limited applications. Providing a class of promising procedures that are capable of scalably solving hard problems in the continuous domain. Opening an important track for multiobjective GEA research that relies on decomposition principle.
Advances in Discrete Tomography and its Applications
Advances in Discrete Tomography and Its Applications is a unified presentation of new methods, algorithms, and select applications that are the foundations of multidimensional image reconstruction by discrete tomographic methods. The self-contained chapters, written by leading mathematicians, engineers, and computer scientists, present cutting-edge research and results in the field.Three main areas are covered: foundations, algorithms, and practical applications. Following an introduction that reports the recent literature of the field, the book explores various mathematical and computational problems of discrete tomography including new applications.
Advances in Differential Evolution
Differential evolution is arguably one of the hottest topics in today's computational intelligence research. This book seeks to present a comprehensive study of the state of the art in this technology and also directions for future research.
Advances in Computational Multibody Systems
Contains versions of selected communications presented at the ECCOMAS Thematic Conference in Multibody Dynamics 2003 that took place in Lisbon, Portugal, which have been enhanced in their self-containment and tutorial aspects by the authors. This comprehensive text constitutes a useful reference for researchers and design engineers.
Advances in Computational Intelligence in Transport, Logistics, and Supply Chain Management
Presents a careful selection of relevant applications of CI methods for transport, logistics, and supply chain management problems. The chapters illustrate the current state-of-the-art in the application of CI methods in these fields and should help and inspire researchers and practitioners to apply and develop efficient methods.
Advances in Automatic Differentiation
Covers advances in automatic differentiation theory and practice. Computer scientists and mathematicians will learn about recent developments in automatic differentiation theory as well as mechanisms for the construction of robust and powerful automatic differentiation tools. Computational scientists and engineers will benefit from the discussion of various applications, which provide insight into effective strategies for using automatic differentiation for inverse problems and design optimization.
Advanced Quantum Mechanics
Discusses nonrelativistic multi-particle systems, relativistic wave equations and relativistic quantum fields. Characteristic of the author´s work are the comprehensive mathematical discussions in which all intermediate steps are derived and where numerous examples of application and exercises help the reader gain a thorough working knowledge of the subject. The topics treated in the book lay the foundation for advanced studies in solid-state physics, nuclear and elementary particle physics. This text both extends and complements Schwabl´s introductory Quantum Mechanics, which covers nonrelativistic quantum mechanics and offers a short treatment of the quantization of the radiation field. The fourth edition has been thoroughly revised with new material having been added. Furthermore, the layout of the figures has been unified, which should facilitate comprehension.
Advanced Intelligent Paradigms in Computer Games
This book presents a sample of the most recent research concerning the application of computational intelligence techniques and internet technology in computer games. The contents include: - COMMONS GAME in intelligent environment - Adaptive generation of dilemma-based interactive narratives - Computational intelligence in racing games - Evolutionary algorithms for board game players with domain knowledge - The ChessBrain project - Electronic market games - EVE’s entropy - Capturing player enjoyment in computer games This book is directed to researchers, practicing engineers/scientists and students.
Advanced computer simulation approaches for soft matter sciences II
This series presents critical reviews of the present and future trends in polymer and biopolymer science including chemistry, physical chemistry, physics and materials science. It is addressed to all scientists at universities and in industry who wish to keep abreast of advances in the topics covered.The second volume contains four contributions, and has a very strong topical focus on long range interactions.
Advanced computer simulation approaches for soft matter sciences I
Soft matter science is nowadays an acronym for an increasingly important class of materials, which ranges from polymers, liquid crystals, colloids up to complex macromolecular assemblies, covering sizes from the nanoscale up the microscale. Computer simulations have proven as an indispensable, if not the most powerful, tool to understand properties of these materials and link theoretical models to experiments. In this first volume of a small series recognized leaders of the field review advanced topics and provide critical insight into the state-of-the-art methods and scientific questions of this lively domain of soft condensed matter research.
Advanced computational intelligence paradigms in healthcare 2
Computational intelligence paradigms offer many advantages in maintaining and enhancing the field of healthcare. This volume presents seven chapters selected from the rapidly growing application areas of computational intelligence to healthcare systems, including intelligent synthetic characters, man-machine interface, menu generators, analysis of user acceptance, pictures archiving and communication systems.This book will serve as a useful resource for the health professionals, professors, students, and the computer scientists, who are working on or interested in learning healthcare systems, to overview the current stat-of-the-art of diverse applications of computational intelligence to healthcare practice.
Advanced computational intelligence paradigms in healthcare 1
This book presents some of the most recent research results on the applications of computational intelligence in healthcare. The contents include: Information model for management of clinical content State-based model for management of type II diabetes Case-based reasoning in medicine Assessing the quality of care in artificial intelligence environment Electronic medical record to examine physician decisions Multi-agent systems for the management of community healthcare Assistive wheelchair navigation Modelling treatment processes using information extraction Neonatal pain detection using face classification techniques Medical education interfaces using virtual patients The book is directed to the computer scientists, medical practitioners, scientists, professors and students of health science, computer science and related disciplines.
Advanced Computational Intelligence Paradigms in Healthcare - 3
Advanced Computational Intelligence (CI) paradigms are increasingly used for implementing robust computer applications to foster safety, quality and efficacy in all aspects of healthcare. This research book covers an ample spectrum of the most advanced applications of CI in healthcare.
Adaptive Mesh Refinement - Theory and Applications; Proceedings of the Chicago Workshop on Adaptive Mesh Refinement Methods, Sept. 3-5, 2003
Advanced numerical simulations that use adaptive mesh refinement (AMR) methods have now become routine in engineering and science. Originally developed for computational fluid dynamics applications these methods have propagated to fields as diverse as astrophysics, climate modeling, combustion, biophysics and many others. The underlying physical models and equations used in these disciplines are rather different, yet algorithmic and implementation issues facing practitioners are often remarkably similar. Unfortunately, there has been little effort to review the advances and outstanding issues of adaptive mesh refinement methods across such a variety of fields. This book attempts to bridge this gap. The book presents a collection of papers by experts in the field of AMR who analyze past advances in the field and evaluate the current state of adaptive mesh refinement methods in scientific computing.
Accelerator-Driven System at Kyoto University Critical Assembly
This book is a unique compilation of experimental benchmark analyses of the accelerator-driven system (ADS) at the Kyoto University Critical Assembly (KUCA) on the most recent advances in the development of computational methods.
Abstraction Refinement for Large Scale Model Checking
This book describes recent research developments in automatic abstraction refinement techniques. The authors address the main challenge in abstraction refinement, i.e., the ability to efficiently reach or come close to the optimum abstraction (the smallest abstract model that proves or refutes the given property). A suite of fully automatic abstraction techniques are proposed to improve the overall computation efficiency. The suite of algorithms presented in this book has demonstrated significant improvement over the prior art; some of them have already been adopted by the EDA companies in their commercial/in-house verification tools.
A Singular Introduction to Commutative Algebra
Aims to lead a further stage in the computational revolution in commutative algebra. Another feature of the book is its breadth of coverage of theoretical topics in the portions of commutative algebra closest to algebraic geometry, with algorithmic treatments of almost every topic.



















