Finite Element Model Updating Using Computational Intelligence Techniques

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Finite Element Model Updating Using Computational Intelligence Techniques

Tshilidzi Marwala
Finite Element Model Updating Using Computational Intelligence Techniques Book PDF

Author : Tshilidzi Marwala
Publisher : Springer Science & Business Media
Page : 254 pages
File Size : 53,5 Mb
Release : 2010-06-04
Category : Technology & Engineering
ISBN : 9781849963237

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Finite Element Model Updating Using Computational Intelligence Techniques by Tshilidzi Marwala Pdf

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.

Probabilistic Finite Element Model Updating Using Bayesian Statistics

Tshilidzi Marwala,Ilyes Boulkaibet,Sondipon Adhikari
Probabilistic Finite Element Model Updating Using Bayesian Statistics Book PDF

Author : Tshilidzi Marwala,Ilyes Boulkaibet,Sondipon Adhikari
Publisher : John Wiley & Sons
Page : 248 pages
File Size : 46,8 Mb
Release : 2016-09-23
Category : Technology & Engineering
ISBN : 9781119153009

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Probabilistic Finite Element Model Updating Using Bayesian Statistics by Tshilidzi Marwala,Ilyes Boulkaibet,Sondipon Adhikari Pdf

Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering Tshilidzi Marwala and Ilyes Boulkaibet, University of Johannesburg, South Africa Sondipon Adhikari, Swansea University, UK Covers the probabilistic finite element model based on Bayesian statistics with applications to aeronautical and mechanical engineering Finite element models are used widely to model the dynamic behaviour of many systems including in electrical, aerospace and mechanical engineering. The book covers probabilistic finite element model updating, achieved using Bayesian statistics. The Bayesian framework is employed to estimate the probabilistic finite element models which take into account of the uncertainties in the measurements and the modelling procedure. The Bayesian formulation achieves this by formulating the finite element model as the posterior distribution of the model given the measured data within the context of computational statistics and applies these in aeronautical and mechanical engineering. Probabilistic Finite Element Model Updating Using Bayesian Statistics contains simple explanations of computational statistical techniques such as Metropolis-Hastings Algorithm, Slice sampling, Markov Chain Monte Carlo method, hybrid Monte Carlo as well as Shadow Hybrid Monte Carlo and their relevance in engineering. Key features: Contains several contributions in the area of model updating using Bayesian techniques which are useful for graduate students. Explains in detail the use of Bayesian techniques to quantify uncertainties in mechanical structures as well as the use of Markov Chain Monte Carlo techniques to evaluate the Bayesian formulations. The book is essential reading for researchers, practitioners and students in mechanical and aerospace engineering.

Probabilistic Finite Element Model Updating Using Bayesian Statistics

Tshilidzi Marwala,Ilyes Boulkaibet,Sondipon Adhikari
Probabilistic Finite Element Model Updating Using Bayesian Statistics Book PDF

Author : Tshilidzi Marwala,Ilyes Boulkaibet,Sondipon Adhikari
Publisher : John Wiley & Sons
Page : 248 pages
File Size : 41,7 Mb
Release : 2016-09-23
Category : Technology & Engineering
ISBN : 9781119153016

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Probabilistic Finite Element Model Updating Using Bayesian Statistics by Tshilidzi Marwala,Ilyes Boulkaibet,Sondipon Adhikari Pdf

Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering Tshilidzi Marwala and Ilyes Boulkaibet, University of Johannesburg, South Africa Sondipon Adhikari, Swansea University, UK Covers the probabilistic finite element model based on Bayesian statistics with applications to aeronautical and mechanical engineering Finite element models are used widely to model the dynamic behaviour of many systems including in electrical, aerospace and mechanical engineering. The book covers probabilistic finite element model updating, achieved using Bayesian statistics. The Bayesian framework is employed to estimate the probabilistic finite element models which take into account of the uncertainties in the measurements and the modelling procedure. The Bayesian formulation achieves this by formulating the finite element model as the posterior distribution of the model given the measured data within the context of computational statistics and applies these in aeronautical and mechanical engineering. Probabilistic Finite Element Model Updating Using Bayesian Statistics contains simple explanations of computational statistical techniques such as Metropolis-Hastings Algorithm, Slice sampling, Markov Chain Monte Carlo method, hybrid Monte Carlo as well as Shadow Hybrid Monte Carlo and their relevance in engineering. Key features: Contains several contributions in the area of model updating using Bayesian techniques which are useful for graduate students. Explains in detail the use of Bayesian techniques to quantify uncertainties in mechanical structures as well as the use of Markov Chain Monte Carlo techniques to evaluate the Bayesian formulations. The book is essential reading for researchers, practitioners and students in mechanical and aerospace engineering.

Smart Computing Applications in Crowdfunding

Bo Xing,Tshilidzi Marwala
Smart Computing Applications in Crowdfunding Book PDF

Author : Bo Xing,Tshilidzi Marwala
Publisher : CRC Press
Page : 512 pages
File Size : 48,5 Mb
Release : 2018-12-07
Category : Business & Economics
ISBN : 9781351265072

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Smart Computing Applications in Crowdfunding by Bo Xing,Tshilidzi Marwala Pdf

The book focuses on smart computing for crowdfunding usage, looking at the crowdfunding landscape, e.g., reward-, donation-, equity-, P2P-based and the crowdfunding ecosystem, e.g., regulator, asker, backer, investor, and operator. The increased complexity of fund raising scenario, driven by the broad economic environment as well as the need for using alternative funding sources, has sparked research in smart computing techniques. Covering a wide range of detailed topics, the authors of this book offer an outstanding overview of the current state of the art; providing deep insights into smart computing methods, tools, and their applications in crowdfunding; exploring the importance of smart analysis, prediction, and decision-making within the fintech industry. This book is intended to be an authoritative and valuable resource for professional practitioners and researchers alike, as well as finance engineering, and computer science students who are interested in crowdfunding and other emerging fintech topics.

Condition Monitoring Using Computational Intelligence Methods

Tshilidzi Marwala
Condition Monitoring Using Computational Intelligence Methods Book PDF

Author : Tshilidzi Marwala
Publisher : Springer Science & Business Media
Page : 247 pages
File Size : 50,8 Mb
Release : 2012-01-23
Category : Technology & Engineering
ISBN : 9781447123798

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Condition Monitoring Using Computational Intelligence Methods by Tshilidzi Marwala Pdf

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.

Economic Modeling Using Artificial Intelligence Methods

Tshilidzi Marwala
Economic Modeling Using Artificial Intelligence Methods Book PDF

Author : Tshilidzi Marwala
Publisher : Springer Science & Business Media
Page : 271 pages
File Size : 54,8 Mb
Release : 2013-04-02
Category : Computers
ISBN : 9781447150107

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Economic Modeling Using Artificial Intelligence Methods by Tshilidzi Marwala Pdf

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.

Artificial Intelligence Techniques for Rational Decision Making

Tshilidzi Marwala
Artificial Intelligence Techniques for Rational Decision Making Book PDF

Author : Tshilidzi Marwala
Publisher : Springer
Page : 178 pages
File Size : 51,7 Mb
Release : 2014-10-20
Category : Computers
ISBN : 9783319114248

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Artificial Intelligence Techniques for Rational Decision Making by Tshilidzi Marwala Pdf

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.

Finite Element Model Updating in Structural Dynamics

Michael Friswell,J.E. Mottershead
Finite Element Model Updating in Structural Dynamics Book PDF

Author : Michael Friswell,J.E. Mottershead
Publisher : Springer Science & Business Media
Page : 305 pages
File Size : 42,8 Mb
Release : 2013-03-09
Category : Technology & Engineering
ISBN : 9789401585088

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Finite Element Model Updating in Structural Dynamics by Michael Friswell,J.E. Mottershead Pdf

Finite element model updating has emerged in the 1990s as a subject of immense importance to the design, construction and maintenance of mechanical systems and civil engineering structures. This book, the first on the subject, sets out to explain the principles of model updating, not only as a research text, but also as a guide for the practising engineer who wants to get acquainted with, or use, updating techniques. It covers all aspects of model preparation and data acquisition that are necessary for updating. The various methods for parameter selection, error localisation, sensitivity and parameter estimation are described in detail and illustrated with examples. The examples can be easily replicated and expanded in order to reinforce understanding. The book is aimed at researchers, postgraduate students and practising engineers.

Militarized Conflict Modeling Using Computational Intelligence

Tshilidzi Marwala,Monica Lagazio
Militarized Conflict Modeling Using Computational Intelligence Book PDF

Author : Tshilidzi Marwala,Monica Lagazio
Publisher : Springer Science & Business Media
Page : 268 pages
File Size : 49,5 Mb
Release : 2011-08-24
Category : Computers
ISBN : 9780857297907

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Militarized Conflict Modeling Using Computational Intelligence by Tshilidzi Marwala,Monica Lagazio Pdf

Militarized Conflict Modeling Using Computational Intelligence examines the application of computational intelligence methods to model conflict. Traditionally, conflict has been modeled using game theory. The inherent limitation of game theory when dealing with more than three players in a game is the main motivation for the application of computational intelligence in modeling conflict. Militarized interstate disputes (MIDs) are defined as a set of interactions between, or among, states that can result in the display, threat or actual use of military force in an explicit way. These interactions can result in either peace or conflict. This book models the relationship between key variables and the risk of conflict between two countries. The variables include Allies which measures the presence or absence of military alliance, Contiguity which measures whether the countries share a common boundary or not and Major Power which measures whether either or both states are a major power. Militarized Conflict Modeling Using Computational Intelligence implements various multi-layer perception neural networks, Bayesian networks, support vector machines, neuro-fuzzy models, rough sets models, neuro-rough sets models and optimized rough sets models to create models that estimate the risk of conflict given the variables. Secondly, these models are used to study the sensitivity of each variable to conflict. Furthermore, a framework on how these models can be used to control the possibility of peace is proposed. Finally, new and emerging topics on modelling conflict are identified and further work is proposed.

Dynamics of Civil Structures, Volume 2

Juan Caicedo,Shamim Pakzad
Dynamics of Civil Structures Volume 2 Book PDF

Author : Juan Caicedo,Shamim Pakzad
Publisher : Springer
Page : 557 pages
File Size : 50,6 Mb
Release : 2015-05-08
Category : Science
ISBN : 9783319152486

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Dynamics of Civil Structures, Volume 2 by Juan Caicedo,Shamim Pakzad Pdf

Dynamics of Civil Structures, Volume 2. Proceedings of the 33rd IMAC, , A Conference and Exposition on Balancing Simulation and Testing, 2015, the second volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Modal Parameter Identification Dynamic Testing of Civil Structures Human Induced Vibrations of Civil Structures Correlation & Updating Operational Modal Analysis Damage Detection of Structures Bridge Structures Damage Detection Models Experimental Techniques for Civil Structures

Model Validation and Uncertainty Quantification, Volume 3

Zhu Mao
Model Validation and Uncertainty Quantification Volume 3 Book PDF

Author : Zhu Mao
Publisher : Springer Nature
Page : 151 pages
File Size : 41,9 Mb
Release : 2022-07-01
Category : Technology & Engineering
ISBN : 9783031040900

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Model Validation and Uncertainty Quantification, Volume 3 by Zhu Mao Pdf

Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022, the third volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification and Propagation in Structural Dynamics Bayesian Analysis for Real-Time Monitoring and Maintenance Uncertainty in Early Stage Design Quantification of Model-Form Uncertainties Fusion of Test and Analysis MVUQ in Action

Handbook Of Machine Learning - Volume 2: Optimization And Decision Making

Tshilidzi Marwala,Collins Achepsah Leke
Handbook Of Machine Learning Volume 2 Optimization And Decision Making Book PDF

Author : Tshilidzi Marwala,Collins Achepsah Leke
Publisher : World Scientific
Page : 321 pages
File Size : 44,6 Mb
Release : 2019-11-21
Category : Computers
ISBN : 9789811205682

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Handbook Of Machine Learning - Volume 2: Optimization And Decision Making by Tshilidzi Marwala,Collins Achepsah Leke Pdf

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.

Handbook Of Machine Learning - Volume 1: Foundation Of Artificial Intelligence

Tshilidzi Marwala
Handbook Of Machine Learning Volume 1 Foundation Of Artificial Intelligence Book PDF

Author : Tshilidzi Marwala
Publisher : World Scientific
Page : 329 pages
File Size : 50,8 Mb
Release : 2018-10-22
Category : Computers
ISBN : 9789813271241

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Handbook Of Machine Learning - Volume 1: Foundation Of Artificial Intelligence by Tshilidzi Marwala Pdf

This is a comprehensive book on the theories of artificial intelligence with an emphasis on their applications. It combines fuzzy logic and neural networks, as well as hidden Markov models and genetic algorithm, describes advancements and applications of these machine learning techniques and describes the problem of causality. This book should serves as a useful reference for practitioners in artificial intelligence.

Special Topics in Structural Dynamics, Volume 6

Nikolaos Dervilis
Special Topics in Structural Dynamics Volume 6 Book PDF

Author : Nikolaos Dervilis
Publisher : Springer
Page : 197 pages
File Size : 47,6 Mb
Release : 2017-03-28
Category : Science
ISBN : 9783319538419

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Special Topics in Structural Dynamics, Volume 6 by Nikolaos Dervilis Pdf

Special Topics in Structural Dynamics, Volume 6: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the sixth volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Experimental Methods Analytical Methods General Dynamics & Modal Analysis General Dynamics & System Identification Damage Detection

Rational Machines and Artificial Intelligence

Tshilidzi Marwala
Rational Machines and Artificial Intelligence Book PDF

Author : Tshilidzi Marwala
Publisher : Academic Press
Page : 272 pages
File Size : 46,6 Mb
Release : 2021-03-31
Category : Science
ISBN : 9780128209448

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Rational Machines and Artificial Intelligence by Tshilidzi Marwala Pdf

Intelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning. They are used in decision making. One element of decision making is the issue of rationality. Regulations such as the General Data Protection Regulation (GDPR) require that decisions that are made by these intelligent machines are explainable. Rational Machines and Artificial Intelligence proposes that explainable decisions are good but the explanation must be rational to prevent these decisions from being challenged. Noted author Tshilidzi Marwala studies the concept of machine rationality and compares this to the rationality bounds prescribed by Nobel Laureate Herbert Simon and rationality bounds derived from the work of Nobel Laureates Richard Thaler and Daniel Kahneman. Rational Machines and Artificial Intelligence describes why machine rationality is flexibly bounded due to advances in technology. This effectively means that optimally designed machines are more rational than human beings. Readers will also learn whether machine rationality can be quantified and identify how this can be achieved. Furthermore, the author discusses whether machine rationality is subjective. Finally, the author examines whether a population of intelligent machines collectively make more rational decisions than individual machines. Examples in biomedical engineering, social sciences and the financial sectors are used to illustrate these concepts. Provides an introduction to the key questions and challenges surrounding Rational Machines, including, When do we rely on decisions made by intelligent machines? What do decisions made by intelligent machines mean? Are these decisions rational or fair? Can we quantify these decisions? and Is rationality subjective? Introduces for the first time the concept of rational opportunity costs and the concept of flexibly bounded rationality as a rationality of intelligent machines and the implications of these issues on the reliability of machine decisions Includes coverage of Rational Counterfactuals, group versus individual rationality, and rational markets Discusses the application of Moore’s Law and advancements in Artificial Intelligence, as well as developments in the area of data acquisition and analysis technologies and how they affect the boundaries of intelligent machine rationality