Condition Monitoring Using Computational Intelligence Methods

Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies

There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention h

An Internet analyst responsible for monitoring the aggregate online research of more than ten million users every day draws on extensive online intelligence to share lesser-known insights into how peo

Unlike existing texts, this book blends for the first time three topics in physics - symmetry, condensed matter physics and computational methods - into one pedagogical textbook. It includes new concepts in mathematical crystallography; experimental methods capitalizing on symmetry aspects; non-conventional applications such as Fourier crystallography, color groups, quasicrystals and incommensurate systems; as well as concepts and techniques behind the Landau theory of phase transitions. Adopting a computational approach to the application of group theoretical techniques to solving symmetry related problems, it dramatically alleviates the need for intensive calculations usually found in the presentation of symmetry. Writing computer programs helps the student achieve a firm understanding of the underlying concepts, and sample programs, based on Mathematica, are presented throughout the book. Containing over 150 exercises, this textbook is ideal for graduate students in condensed matter

Agresti and Finley present statistical methods in a style that emphasizes their concepts and their application to the social sciences rather than the mathematics and computational details behind them.

Agresti and Finley present statistical methods in a style that emphasizes their concepts and their application to the social sciences rather than the mathematics and computational details behind them.

Due to the increase in computational power and new discoveries in propagation phenomena for linear and nonlinear waves, the area of computational wave propagation has become more significant in recent

Monte Carlo Methods in Fuzzy Optimization is a clear and didactic book about Monte Carlo methods using random fuzzy numbers to obtain approximate solutions to fuzzy optimization problems. The book inc

Modern fluid dynamics is a combination of traditional methods of theory and analysis and newer methods of computation and numerical simulation. Fluid Dynamics with a Computational Perspective synthesizes traditional theory and modern computation. It is neither a book on methods of computation, nor a book on analysis; it is about fluid dynamics. The book is ideal for a course on fluid dynamics. Early chapters review the laws of fluid mechanics and survey computational methodology, following chapters study flows in which the Reynolds number increases from creeping flow to turbulence, followed by a thorough discussion of compressible flow and interfaces. Whereas all significant equations and their solutions are presented, their derivations are informal. References for detailed derivations are provided. A chapter on intermediate Reynolds number flows provides illustrative case studies by pure computation. Elsewhere, computations and theory are interwoven.

Electronic structure problems are studied in condensed matter physics and theoretical chemistry to provide important insights into the properties of matter. This 2006 graduate textbook describes the main theoretical approaches and computational techniques, from the simplest approximations to the most sophisticated methods. It starts with a detailed description of the various theoretical approaches to calculating the electronic structure of solids and molecules, including density-functional theory and chemical methods based on Hartree-Fock theory. The basic approximations are thoroughly discussed, and an in-depth overview of recent advances and alternative approaches in DFT is given. The second part discusses the different practical methods used to solve the electronic structure problem computationally, for both DFT and Hartree-Fock approaches. Adopting a unique and open approach, this textbook is aimed at graduate students in physics and chemistry, and is intended to improve communicat

Biological monitoring of running waters is a scientifically and economically valid approach for surveys and monitoring programmes to assess the water quality. Biological Monitoring of Rivers is a time

This is the first comprehensive monograph that features state-of-the-art multigrid methods for enhancing the modeling versatility, numerical robustness, and computational efficiency of one of the most

This is the first book to present both classical and quantum-chemical approaches to computational methods, incorporating the many new developments in this field from the last few years. Written especi

This book shows how wavelets can be used to enhance computational intelligence for chaotic and complex pattern recognition problems. By integrating wavelets with other soft computing techniques such

The quantitative analysis of biological sequence data is based on methods from statistics coupled with efficient algorithms from computer science. Algebra provides a framework for unifying many of the seemingly disparate techniques used by computational biologists. This book, first published in 2005, offers an introduction to this mathematical framework and describes tools from computational algebra for designing new algorithms for exact, accurate results. These algorithms can be applied to biological problems such as aligning genomes, finding genes and constructing phylogenies. The first part of this book consists of four chapters on the themes of Statistics, Computation, Algebra and Biology, offering speedy, self-contained introductions to the emerging field of algebraic statistics and its applications to genomics. In the second part, the four themes are combined and developed to tackle real problems in computational genomics. As the first book in the exciting and dynamic area, it wi

Using discrete dynamical systems, this book introduces powerful mathematical modeling techniques, both standard analytical and modern computational, to students in mathematics, the natural sciences, a

Human health risk assessment involves the measuring of risk of exposure to disease, with a view to improving disease prevention. Mathematical, biological, statistical, and computational methods play a

Innovations in Intelligent Systems is a rare collection of the latest developments in intelligent paradigms such as knowledge-based systems, computational intelligence and hybrid combinations as well

Computational Finance presents a modern computational approach to mathematical finance within the Windows environment, and contains financial algorithms, mathematical proofs and computer code in C/C+

Constraints are everywhere: most computational problems can be described in terms of restrictions imposed on the set of possible solutions, and constraint programming is a problem-solving technique that works by incorporating those restrictions in a programming environment. It draws on methods from combinatorial optimisation and artificial intelligence, and has been successfully applied in a number of fields from scheduling, computational biology, finance, electrical engineering and operations research through to numerical analysis. This textbook for upper-division students provides a thorough and structured account of the main aspects of constraint programming. The author provides many worked examples that illustrate the usefulness and versatility of this approach to programming, as well as many exercises throughout the book that illustrate techniques, test skills and extend the text. Pointers to current research, extensive historical and bibliographic notes, and a comprehensive list

The last few decades have seen a new era of artificial intelligence focusing on emulating humans, either in their behaviour or in their neurophysiology. Computational intelligence is a well-establishe

Fact finding in judicial proceedings is a dynamic process. This collection of papers considers whether computational methods or other formal logical methods developed in disciplines such as artificial

This book describes computational methods used in quantum dynamics with emphasis on small quantum systems. Computational physics is a fundamental physical discipline at the forefront of physical r

Presenting a reference model architecture for the design of intelligent systemsEngineering of Mind presents the foundations for a computational theory of intelligence. It discusses the main streams of

Seven reviews highlight essential aspects of the methods, which are making a significant impact in quantum computational chemistry. The idea behind the approach is to generalize the Hartree-Fock wave

This book offers a critical reconstruction of the fundamental ideas and methods of artificial intelligence research. Through close attention to the metaphors of artificial intelligence and their consequences for the field's patterns of success and failure, it argues for a reorientation of the field away from thought in the head and towards activity in the world. By considering computational ideas in a large, philosophical framework, the author eases critical dialogue between technology and the social sciences. AI can benefit from an understanding of the field in relation to human nature, and in return, it offers a powerful mode of investigation into the practicalities of physical realization. This is one of a series of publications associated with the Earth System Governance Project. For more publications, see www.cambridge.org/earth-system-governance.

Intelligence services form an important but controversial part of the modern state. Drawing mainly on British and American examples, this book provides an analytic framework for understanding the 'intelligence community' and assessing its value. The author, a former senior British intelligence officer, describes intelligence activities, the purposes which the system serves, and the causes and effects of its secrecy. He considers 'intelligence failure' and how organisation and management can improve the chances of success. Using parallels with the information society and the current search for efficiency in public administration as a whole, the book explores the issues involved in deciding how much intelligence is needed and discusses the kinds of management necessary. In his conclusions Michael Herman discusses intelligence's national value in the post-Cold War world. He also argues that it has important contributions to make to international security, but that its threat-inducing acti

Creativity is a topic that has traditionally interested psychologists, historians and biographers. Developments in cognitive science and artificial intelligence have provided a powerful computational framework in which creativity can be studied and the creative process can be described and explained. In this book, creativity in technology is discussed using such a computational approach. Using an important historical episode in computer technology as a case study, namely the invention of microprogramming by Maurice Wilkes in 1951, the author presents a plausible explanation of the process by which Wilkes may have arrived at his invention. Based on this case study, the author has also proposed some very general hypotheses concerning creativity that appear to corroborate the findings of some psychologists and historians and then suggests that creative thinking is not significantly different in nature from everyday thinking and reasoning.

Design of Water Quality Monitoring Systems Design of Water Quality Monitoring Systems presents a state-of-the-art approach to designing a water quality monitoring system that gets consistently valid r

These two books cover the most significant recent advances in oncological molecular imaging, from methods and preclinical research to clinical practice. The first book is divided into two sections. The first section focuses on standardized and emerging technologies, as well as probe designs for various imaging modalities, including advanced X-ray imaging, CT, MRI, SPECT, total body PET, ultrasound, optical imaging, optoacoustic imaging, and probes for these modalities. The section also covers artificial intelligence in radiomics. The second section focuses on preclinical applications, including advanced microscopy in animal imaging. The second book presents various clinical applications of molecular imaging and related imaging features. The first section of the second book discusses the crucial, emerging role of molecular imaging in planning and monitoring oncological therapies and future challenges and prospects in multimodality imaging. The second section discusses radiotherapy appro

This new volume addresses the growing interest in and use of big data analytics in many industries and in many research fields around the globe; it is a comprehensive resource on the core concepts of big data analytics and the tools, techniques, and methodologies. The book gives the why and the how of big data analytics in an organized and straightforward manner, using both theoretical and practical approaches.The book's authors have organized the contents in a systematic manner, starting with an introduction and overview of big data analytics and then delving into pre-processing methods, feature selection methods and algorithms, big data streams, and big data classification. Such terms and methods as swarm intelligence, data mining, the bat algorithm and genetic algorithms, big data streams, and many more are discussed. The authors explain how deep learning and machine learning along with other methods and tools are applied in big data analytics. The last section of the book presents

Sentence comprehension - the way we process and understand spoken and written language - is a central and important area of research within psycholinguistics. This book explores the contribution of computational linguistics to the field, showing how computational models of sentence processing can help scientists in their investigation of human cognitive processes. It presents the leading computational model of retrieval processes in sentence processing, the Lewis and Vasishth cue-based retrieval mode, and develops a principled methodology for parameter estimation and model comparison/evaluation using benchmark data, to enable researchers to test their own models of retrieval against the present model. It also provides readers with an overview of the last 20 years of research on the topic of retrieval processes in sentence comprehension, along with source code that allows researchers to extend the model and carry out new research. Comprehensive in its scope, this book is essential readi

Effective transaction monitoring begins with proper implementation Anti-Money Laundering Transaction Monitoring Systems Implementation provides comprehensive guidance for bank compliance and IT person

The first introductory textbook in the emerging, fast-developing field of computational psychiatry.Computational psychiatry applies computational modeling and theoretical approaches to psychiatric que

A book at the intersection of data science and media studies, presenting concepts and methods for computational analysis of cultural data. How can we see a billion images? What analytical methods can

This book covers tools and techniques used for developing mathematical methods and modelling related to real-life situations. It brings forward significant aspects of mathematical research by using di

This book is written for engineers and other practitioners using numerical methods in their work and serves as a textbook for courses in applied mathematics and numerical analysis.

This book presents the theory and practice of non-parametric statistics, with an emphasis on motivating principals. The course is a combination of traditional rank based methods and more computational

Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This introduction for researchers and graduate students is the first in-depth, comprehensive treatment of statistical and machine learning methods for neuroscience. The methods are demonstrated through case studies of real problems to empower readers to build their own solutions. The book covers a wide variety of methods, including supervised classification with non-probabilistic models (nearest-neighbors, classification trees, rule induction, artificial neural networks and support vector machines) and probabilistic models (discriminant analysis, logistic regression and Bayesian network classifiers), meta-classifiers, multi-dimensional classifiers and feature subset selection methods. Other parts of the book are devoted to association discovery with probabilistic graphical models (Bayesian networks and Markov networks) and spatial statistics with po

This combines theory and practice for the design of earth lateral support for deep excavations in soil, along with design methods, basic and computational numerical methods. It is heavily illustrated