Computational Intelligence For Missing Data Imputation Estimation And Management Knowledge Optimization Techniques

Author : Marwala, Tshilidzi
Publisher : IGI Global
ISBN 13 : 1605663379
Total Pages : 326 pages
Book Rating : 4.71/5 ( download)

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Download or read book Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques written by Marwala, Tshilidzi and published by IGI Global. This book was released on 2009-04-30 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is for those who use data analysis to build decision support systems, particularly engineers, scientists and statisticians"--Provided by publisher.

Author : Tshilidzi Marwala
Publisher : Springer Science & Business Media
ISBN 13 : 1447123794
Total Pages : 247 pages
Book Rating : 4.98/5 ( download)

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Download or read book Condition Monitoring Using Computational Intelligence Methods written by Tshilidzi Marwala and published by Springer Science & Business Media. This book was released on 2012-01-23 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, minimize downtime and reduce maintenance costs. The text introduces various signal-processing and pre-processing techniques, wavelets and principal component analysis, for example, together with their uses in condition monitoring and details the development of effective feature extraction techniques classified into frequency-, time-frequency- and time-domain analysis. Data generated by these techniques can then be used for condition classification employing tools such as: • fuzzy systems; rough and neuro-rough sets; neural and Bayesian networks;hidden Markov and Gaussian mixture models; and support vector machines.

Author : Tshilidzi Marwala
Publisher : Springer
ISBN 13 : 3319114247
Total Pages : 178 pages
Book Rating : 4.48/5 ( download)

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Download or read book Artificial Intelligence Techniques for Rational Decision Making written by Tshilidzi Marwala and published by Springer. This book was released on 2014-10-20 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon’s bounded rationality theory are flexible due to advanced signal processing techniques, Moore’s Law and artificial intelligence. Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making: Theory of the marginalization of irrelevant information Principal component analysis Independent component analysis Automatic relevance determination method In addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence. Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.

Author : Collins Achepsah Leke
Publisher : Springer
ISBN 13 : 3030011801
Total Pages : 179 pages
Book Rating : 4.02/5 ( download)

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Download or read book Deep Learning and Missing Data in Engineering Systems written by Collins Achepsah Leke and published by Springer. This book was released on 2018-12-13 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning and Missing Data in Engineering Systems uses deep learning and swarm intelligence methods to cover missing data estimation in engineering systems. The missing data estimation processes proposed in the book can be applied in image recognition and reconstruction. To facilitate the imputation of missing data, several artificial intelligence approaches are presented, including: deep autoencoder neural networks; deep denoising autoencoder networks; the bat algorithm; the cuckoo search algorithm; and the firefly algorithm. The hybrid models proposed are used to estimate the missing data in high-dimensional data settings more accurately. Swarm intelligence algorithms are applied to address critical questions such as model selection and model parameter estimation. The authors address feature extraction for the purpose of reconstructing the input data from reduced dimensions by the use of deep autoencoder neural networks. They illustrate new models diagrammatically, report their findings in tables, so as to put their methods on a sound statistical basis. The methods proposed speed up the process of data estimation while preserving known features of the data matrix. This book is a valuable source of information for researchers and practitioners in data science. Advanced undergraduate and postgraduate students studying topics in computational intelligence and big data, can also use the book as a reference for identifying and introducing new research thrusts in missing data estimation.

Author : Tshilidzi Marwala
Publisher : World Scientific
ISBN 13 : 981120568X
Total Pages : 321 pages
Book Rating : 4.82/5 ( download)

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Download or read book Handbook Of Machine Learning - Volume 2: Optimization And Decision Making written by Tshilidzi Marwala and published by World Scientific. This book was released on 2019-11-21 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.

Author : Bo Xing
Publisher : Springer Science & Business Media
ISBN 13 : 3319034049
Total Pages : 451 pages
Book Rating : 4.41/5 ( download)

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Download or read book Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms written by Bo Xing and published by Springer Science & Business Media. This book was released on 2013-12-13 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first notable feature of this book is its innovation: Computational intelligence (CI), a fast evolving area, is currently attracting lots of researchers’ attention in dealing with many complex problems. At present, there are quite a lot competing books existing in the market. Nevertheless, the present book is markedly different from the existing books in that it presents new paradigms of CI that have rarely mentioned before, as opposed to the traditional CI techniques or methodologies employed in other books. During the past decade, a number of new CI algorithms are proposed. Unfortunately, they spread in a number of unrelated publishing directions which may hamper the use of such published resources. These provide us with motivation to analyze the existing research for categorizing and synthesizing it in a meaningful manner. The mission of this book is really important since those algorithms are going to be a new revolution in computer science. We hope it will stimulate the readers to make novel contributions or even start a new paradigm based on nature phenomena. Although structured as a textbook, the book's straightforward, self-contained style will also appeal to a wide audience of professionals, researchers and independent learners. We believe that the book will be instrumental in initiating an integrated approach to complex problems by allowing cross-fertilization of design principles from different design philosophies. The second feature of this book is its comprehensiveness: Through an extensive literature research, there are 134 innovative CI algorithms covered in this book.

Author : Tshilidzi Marwala
Publisher : Springer Science & Business Media
ISBN 13 : 1447150104
Total Pages : 271 pages
Book Rating : 4.07/5 ( download)

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Download or read book Economic Modeling Using Artificial Intelligence Methods written by Tshilidzi Marwala and published by Springer Science & Business Media. This book was released on 2013-04-02 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic Modeling Using Artificial Intelligence Methods examines the application of artificial intelligence methods to model economic data. Traditionally, economic modeling has been modeled in the linear domain where the principles of superposition are valid. The application of artificial intelligence for economic modeling allows for a flexible multi-order non-linear modeling. In addition, game theory has largely been applied in economic modeling. However, the inherent limitation of game theory when dealing with many player games encourages the use of multi-agent systems for modeling economic phenomena. The artificial intelligence techniques used to model economic data include: multi-layer perceptron neural networks radial basis functions support vector machines rough sets genetic algorithm particle swarm optimization simulated annealing multi-agent system incremental learning fuzzy networks Signal processing techniques are explored to analyze economic data, and these techniques are the time domain methods, time-frequency domain methods and fractals dimension approaches. Interesting economic problems such as causality versus correlation, simulating the stock market, modeling and controling inflation, option pricing, modeling economic growth as well as portfolio optimization are examined. The relationship between economic dependency and interstate conflict is explored, and knowledge on how economics is useful to foster peace – and vice versa – is investigated. Economic Modeling Using Artificial Intelligence Methods deals with the issue of causality in the non-linear domain and applies the automatic relevance determination, the evidence framework, Bayesian approach and Granger causality to understand causality and correlation. Economic Modeling Using Artificial Intelligence Methods makes an important contribution to the area of econometrics, and is a valuable source of reference for graduate students, researchers and financial practitioners.

Author : Xing, Bo
Publisher : IGI Global
ISBN 13 : 1466649097
Total Pages : 348 pages
Book Rating : 4.95/5 ( download)

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Download or read book Computational Intelligence in Remanufacturing written by Xing, Bo and published by IGI Global. This book was released on 2013-12-31 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: In attempts to reduce greenhouse gas emissions, many alternatives to manufacturing have been recommended from a number of international organizations. Although challenges will arise, remanufacturing has the ability to transform ecological and business value. Computational Intelligence in Remanufacturing introduces various computational intelligence techniques that are applied to remanufacturing-related issues, results, and lessons from specific applications while highlighting future development and research. This book is an essential reference for students, researchers, and practitioners in mechanical, industrial, and electrical engineering.

Author : Tshilidzi Marwala
Publisher : Springer Science & Business Media
ISBN 13 : 1849963231
Total Pages : 254 pages
Book Rating : 4.37/5 ( download)

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Download or read book Finite Element Model Updating Using Computational Intelligence Techniques written by Tshilidzi Marwala and published by Springer Science & Business Media. This book was released on 2010-06-04 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: FEM updating allows FEMs to be tuned better to reflect measured data. It can be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. This book applies both strategies to the field of structural mechanics, using vibration data. Computational intelligence techniques including: multi-layer perceptron neural networks; particle swarm and GA-based optimization methods; simulated annealing; response surface methods; and expectation maximization algorithms, are proposed to facilitate the updating process. Based on these methods, the most appropriate updated FEM is selected, a problem that traditional FEM updating has not addressed. This is found to incorporate engineering judgment into finite elements through the formulations of prior distributions. Case studies, demonstrating the principles test the viability of the approaches, and. by critically analysing the state of the art in FEM updating, this book identifies new research directions.

Author : Tshilidzi Marwala
Publisher : World Scientific
ISBN 13 : 9814630888
Total Pages : 208 pages
Book Rating : 4.87/5 ( download)

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Download or read book Causality, Correlation and Artificial Intelligence for Rational Decision Making written by Tshilidzi Marwala and published by World Scientific. This book was released on 2015-01-02 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Causality has been a subject of study for a long time. Often causality is confused with correlation. Human intuition has evolved such that it has learned to identify causality through correlation. In this book, four main themes are considered and these are causality, correlation, artificial intelligence and decision making. A correlation machine is defined and built using multi-layer perceptron network, principal component analysis, Gaussian Mixture models, genetic algorithms, expectation maximization technique, simulated annealing and particle swarm optimization. Furthermore, a causal machine is defined and built using multi-layer perceptron, radial basis function, Bayesian statistics and Hybrid Monte Carlo methods. Both these machines are used to build a Granger non-linear causality model. In addition, the Neyman–Rubin, Pearl and Granger causal models are studied and are unified. The automatic relevance determination is also applied to extend Granger causality framework to the non-linear domain. The concept of rational decision making is studied, and the theory of flexibly-bounded rationality is used to extend the theory of bounded rationality within the principle of the indivisibility of rationality. The theory of the marginalization of irrationality for decision making is also introduced to deal with satisficing within irrational conditions. The methods proposed are applied in biomedical engineering, condition monitoring and for modelling interstate conflict. Contents:Introduction to Artificial Intelligence based Decision MakingWhat is a Correlation Machine?What is a Causal Machine?Correlation Machines Using Optimization MethodsNeural Networks for Modeling Granger CausalityRubin, Pearl and Granger Causality Models: A Unified ViewCausal, Correlation and Automatic Relevance Determination Machines for Granger CausalityFlexibly-bounded RationalityMarginalization of Irrationality in Decision MakingConclusions and Further Work Readership: Graduate students, researchers and professionals in the field of artificial intelligence. Key Features:It proposes fresh definition of causality and proposes two new theories i.e. flexibly bounded rationality and marginalization of irrationality theory for decision makingIt also applies these techniques to a diverse areas in engineering, political science and biomedical engineeringKeywords:Causality;Correlation;Artificial Intelligence;Rational Decision Making