Condition Monitoring Using Computational Intelligence Methods

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence – quickly and with a high quality. The intent is to

The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence-quickly and with a high quality. The intent is to cov

Essentials of Computational Electromagnetics provides an in-depth introduction of the three main full-wave numerical methods in computational electromagnetics (CEM); namely, the method of moment (MoM)

Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes

Computational methods have become an indispensible tool for elucidating the mechanism of organometallic reactions. This snapshot of state-of-the-art computational studies provides an overview of the v

This second edition presents the theory of continuum mechanics using computational methods. The text covers a broad range of topics including general problems of large rotation and large deformations and the development and limitations of finite element formulations in solving such problems. Dr Shabana introduces theories on motion kinematics, strain, forces and stresses and goes on to discuss linear and nonlinear constitutive equations, including viscoelastic and plastic constitutive models. General nonlinear continuum mechanics theory is used to develop small and large finite element formulations which correctly describe rigid body motion for use in engineering applications. This second edition features a new chapter that focuses on computational geometry and finite element analysis. This book is ideal for graduate and undergraduate students, professionals and researchers who are interested in continuum mechanics.

The two-volume set LNAI 6922 and LNAI 6923 constitutes the refereed proceedings of the Third International Conference on Computational Collective Intelligence, ICCCI 2011, held in Gdynia, Poland, in S

This book focuses on chemical marine monitoring, highlighting policy frameworks and analytical trends with an emphasis on laboratory methods and laboratory quality control.Contents:CHAPTER I – S

The book shows how the various paradigms of computational intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG sign

Industrial engineers, mechanical engineers, and related contributors summarize major developments in statistical profile monitoring methods, which are a potential sub-area of statistical quality contr

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence – quickly and with a high quality. The intent is to

The current rapid and complex advancement applications of electromagnetic (EM) and optical systems calls for a much needed update on the computational methods currently in use. Completely revised and

This book consists of important contributions by world-renowned experts on adaptive high-order methods in computational fluid dynamics (CFD). It covers several widely used, and still intensively resea

Using Mixed Methods argues for research from a holistic perspective, integrating different methods, different data and overall research strategies. It provides innovative and ground-breaking in their

Computational Methods in Elasticity and Plasticity: Solids and Porous Media presents the latest developments in the area of elastic and elasto-plastic finite element modeling of solids, porous media a

Computational biology is an interdisciplinary field that applies mathematical, statistical, and computer science methods to answer biological questions, and its importance has only increased with the

The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence - quickly and with a high quality. The intent is to co

Researchers (most of them from Brazil) in mathematics, computer science, and a range of biological and agricultural sciences survey mathematical and computational methods used in agriculture research.

Robot intelligence has become a major focus of intelligent robotics. Recent innovation in computational intelligence including fuzzy learning, neural networks, evolutionary computation and classical A

This book deals with the application of spectral methods to problems of uncertainty propagation and quanti?cation in model-based computations. It speci?cally focuses on computational and algorithmic f

Physicists, chemical engineers, and other scientists set out the theory, numerical methods, and practice of computational gas-solids flows for advanced graduate students, researchers, and practitioner

The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence - quickly and with a high quality. The intent is to co

* Focuses on learning patterns and knowledge from data generated by mobile users and mobile technology. * Covers research and application issues in applying computational intelligence applications to

The papers compiled in this book focus on use of computational intelligence techniques in architecting engineering systems. As the world is moving towards a networked society, business and government

For drugs with a narrow therapeutic index, therapeutic drug monitoring methods are essential for patient management. Although immunoassays are commercially available for many drugs and most laboratori

This book constitutes the proceedings of the First International Conference on Computational Collective Intelligence, ICCCI 2009, held in Wroclaw, Poland, in October 2009. The 71 papers presented in t

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and their applications in the environmental sciences. Due to their powerful nonlinear modelling capability, machine learning methods today are used in satellite data processing, general circulation models(GCM), weather and climate prediction, air quality forecasting, analysis and modelling of environmental data, oceanographic and hydrological forecasting, ecological modelling, and monitoring of snow, ice and forests. The book includes end-of-chapter review questions and an appendix listing websites for downloading computer code and data sources. A resources website contains datasets for exercises, and password-protected solutions are available. The book is suitable for first-year graduate students and advanced undergraduates. It is also valuable for resear

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and their applications in the environmental sciences. Due to their powerful nonlinear modelling capability, machine learning methods today are used in satellite data processing, general circulation models(GCM), weather and climate prediction, air quality forecasting, analysis and modelling of environmental data, oceanographic and hydrological forecasting, ecological modelling, and monitoring of snow, ice and forests. The book includes end-of-chapter review questions and an appendix listing websites for downloading computer code and data sources. A resources website contains datasets for exercises, and password-protected solutions are available. The book is suitable for first-year graduate students and advanced undergraduates. It is also valuable for resear

Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes

Recent Advances in Numerical Methods features contributions from distinguished researchers, focused on significant aspects of current numerical methods and computational mathematics. The increasing n

This monograph aims to provide state-of-the-art numerical methods, procedures and algorithms in the field of computational geoscience, based on the authors’ own work during the last decade. Although s

The TACC conference deals with the theoretical methods and application of computational chemistry. The theoretical aspects include development of computational and statistical techniques, quantum and

Emphasizing the search for patterns within and between biological sequences, trees, and graphs, Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R shows how combinator

This practical guide describes the basic computational methodologies for catalysis and materials science at an introductory level, presenting the methods with relevant applications, such as spectrosco

Business Research Methods and Statistics Using SPSS provides a simple, easy to follow, and non-mathematical approach to understanding and using quantitative methods and statistics. It is solidly groun

This guide covers all methods of measuring and monitoring forest carbon pools and fluxes. Each chapter covers a specific method and discusses measurement methods, background information, necessary cal

The International Workshop on Computational Intelligence for Security in Information Systems (CISIS) proposes a meeting ground to the various communities involved in building intelligent systems for s

Presents a drug-free plan for curing psoriasis using natural methods that rely on diet, detoxification, and mental attitude to alleviate and control the condition.

The subject of computational plasticity encapsulates the numerical methods used for the finite element simulation of the behaviour of a wide range of engineering materials considered to be plastic &#

Inferring the precise locations and splicing patterns of genes in DNA is a difficult but important task, with broad applications to biomedicine. The mathematical and statistical techniques that have been applied to this problem are surveyed and organized into a logical framework based on the theory of parsing. Both established approaches and methods at the forefront of current research are discussed. Numerous case studies of existing software systems are provided, in addition to detailed examples that work through the actual implementation of effective gene-predictors using hidden Markov models and other machine-learning techniques. Background material on probability theory, discrete mathematics, computer science, and molecular biology is provided, making the book accessible to students and researchers from across the life and computational sciences. This book is ideal for use in a first course in bioinformatics at graduate or advanced undergraduate level, and for anyone wanting to kee