Marwala, Tshilidzi's Books

Rational Machines and Artificial Intelligence

By: Tshilidzi Marwala

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Rational Machines and Artificial Intelligence

By: Tshilidzi Marwala

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

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270

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Elsevier

Published Date

ISBN 10

0128206764

ISBN 13

9780128206768

Heal our World

Securing a Sustainable Future

By: Tshilidzi Marwala

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Heal our World

Securing a Sustainable Future

By: Tshilidzi Marwala

The world is emerging from the COVID-19 pandemic, more fragmented and further away from the more equal and equitable iteration imagined in 2015 when the Sustainable Development Goals (SDGs) were conceptualised. As we hurtle at seemingly lightning speed towards the 2030 deadline to achieve these goals, the urgency is palpable. Although we have certainly strayed further away from the targets, there is still time to act in order to ensure that we inch closer to this vision. Professor Tshilidzi Marwala paints a stark, and often grim, picture of our current context, one defined by monumental setbacks in the SDGs. Yet, as he carves out each developmental goal and its implications, it is apparent that there are tangible solutions that can be implemented now. Tshilidzi's assertion that now is the time to act is backed by intricate and actionable data with a simple mission statement: we must heal the future. He offers a new narrative that addresses how we can translate the latent potential that exists through technology, innovation and Fourth Industrial Revolution approaches to leadership and policy making to deal with, among others, corruption, poverty eradication, joblessness, an education system in crisis, declining economies and food insecurity. Heal our World is a deep dive into the SDGs, particularly in the African context, and it looks toward securing a future in which our divisions are blurred, and our goals seem almost in reach again. Tshilidzi Marwala, the author of Heal our World, Leading in the 21st Century and Leadership Lessons from Books I Have Read is the Vice-Chancellor and Principal of the University of Johannesburg. From 1 March 2023, he will be the Rector of the United Nations University based in Tokyo, Japan. He was previously Deputy Vice-Chancellor for Research and Executive Dean of the Faculty of Engineering at the University of Johannesburg and Full Professor at the Carl & Emily Fuchs Chair of Systems and Control Engineering at the University of the Witwatersrand. Tshilidzi holds a Bachelor of Science in Mechanical Engineering (magna cum laude) from Case Western Reserve University, a PhD in Artificial Intelligence from the University of Cambridge and a Post-Doc at Imperial College (London). He is a member of the American Academy of Arts and Sciences, The World Academy of Sciences (TWAS), the Academy of Science of South Africa (ASSAf), the African Academy of Sciences (AAS) and the South African Academy of Engineering (SAAE). He is a distinguished member of the Association for Computing Machinery (ACM). His research interests are multidisciplinary and include the theory and application of artificial intelligence to engineering, computer science, finance, social science and medicine. He has supervised 37 doctoral students. He has also published 23 books on artificial intelligence (one translated into Chinese) and over 300 papers in journals, proceedings, book chapters and magazines. He holds five international patents.

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270

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Jonathan Ball Publishers

Published Date

ISBN 10

1998958604

ISBN 13

9781998958603

Artificial Intelligence and International Relations Theories

By: Bhaso Ndzendze,Tshilidzi Marwala

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Artificial Intelligence and International Relations Theories

By: Bhaso Ndzendze,Tshilidzi Marwala

This book discusses the impact of artificial intelligence (AI) on international relations theories. As a phenomenon, AI is everywhere in the real world and growing. Through its transformative nature, it is simultaneously simplifying and complicating processes. Importantly, it also overlooks and “misunderstands”. Globally, leaders, diplomats and policymakers have had to familiarise themselves and grapple with concepts such as algorithms, automation, machine learning, and neural networks. These and other features of modern AI are redefining our world, and with it, the long-held assumptions scholars of IR have relied on for their theoretical accounts of our universe. The book takes a historic, contemporary and long-term approach to explain and anticipate AI’s impact on IR – and vice versa – through a systematic treatment of 9 theoretical paradigms and schools of thought including realism, liberalism, feminism, postcolonial theory and green theory. This book draws on original datasets, innovative empirical case studies and in-depth engagement with the core claims of the traditional and critical theoretical lenses to reignite debates on the nature and patterns of power, ethics, conflict, and systems among states and non-state actors.

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172

Publisher

Springer Nature

Published Date

ISBN 10

9811948771

ISBN 13

9789811948770

Smart Computing Applications in Crowdfunding

By: Bo Xing,Tshilidzi Marwala

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Smart Computing Applications in Crowdfunding

By: Bo Xing,Tshilidzi Marwala

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.

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Page Count

512

Publisher

CRC Press

Published Date

ISBN 10

1351265075

ISBN 13

9781351265072

Artificial Intelligence Techniques for Rational Decision Making

By: Tshilidzi Marwala

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Artificial Intelligence Techniques for Rational Decision Making

By: Tshilidzi Marwala

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.

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178

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Springer

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ISBN 10

3319114247

ISBN 13

9783319114248

Artificial Intelligence and Economic Theory: Skynet in the Market

By: Tshilidzi Marwala,Evan Hurwitz

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Artificial Intelligence and Economic Theory: Skynet in the Market

By: Tshilidzi Marwala,Evan Hurwitz

This book theoretically and practically updates major economic ideas such as demand and supply, rational choice and expectations, bounded rationality, behavioral economics, information asymmetry, pricing, efficient market hypothesis, game theory, mechanism design, portfolio theory, causality and financial engineering in the age of significant advances in man-machine systems. The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence concepts such as the swarming of birds, the working of the brain and the pathfinding of the ants. Artificial Intelligence and Economic Theory: Skynet in the Market analyses the impact of artificial intelligence on economic theories, a subject that has not been studied. It also introduces new economic theories and these are rational counterfactuals and rational opportunity costs. These ideas are applied to diverse areas such as modelling of the stock market, credit scoring, HIV and interstate conflict. Artificial intelligence ideas used in this book include neural networks, particle swarm optimization, simulated annealing, fuzzy logic and genetic algorithms. It, furthermore, explores ideas in causality including Granger as well as the Pearl causality models.

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206

Publisher

Springer

Published Date

ISBN 10

3319661043

ISBN 13

9783319661049

Deep Learning and Missing Data in Engineering Systems

By: Collins Achepsah Leke,Tshilidzi Marwala

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Deep Learning and Missing Data in Engineering Systems

By: Collins Achepsah Leke,Tshilidzi Marwala

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.

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188

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Springer

Published Date

ISBN 10

3030011801

ISBN 13

9783030011802

Leading in the 21st Century

The Call for a New Type of African Leader

By: Tshilidzi Marwala

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Leading in the 21st Century

The Call for a New Type of African Leader

By: Tshilidzi Marwala

It became apparent to me that, due to the complexity of problems that face humanity today, those who do not know should not lead.' – Professor Tshilidzi Marwala In 2020 the world found itself in a state of flux. A global pandemic disrupted the world order while the digital transformation of the Fourth Industrial Revolution (4IR), with its challenges and huge potential benefits, presented a fundamental paradigm shift. How are Africa's leaders to respond, today? In a crisis, decisive leadership is imperative for the public good, but as we move beyond the pandemic and confront the changes of the 4IR, we must determine how we will adapt. What is clear is that leadership will have to be grounded in scientific and mathematical thinking and in good governance. It follows, then, that for South Africa to succeed as a nation in the 21st century we must be able to provide our people with an all-embracing education, not just science and technology but human and social sciences as well. Leading in the 21st Century presents a comprehensive overview of how the world is changing and lessons we can draw from leaders, particularly in the African context. From Charlotte Maxeke and the Rain Queen Modjadji, to Mangaliso Robert Sobukwe, Eric Molobi and Richard Maponya, there is much to learn from great leaders. The challenges of the 21st century are immense, from climate change to social media and the digital divide that deepens our understanding of inequality, particularly in the 'new normal'. South Africa faces not only a shifting global context but a fraught local context of stagnant growth, rising unemployment and deep-seated inequality, worsened in 2020 by the national lockdown necessitated by the coronavirus pandemic. The 4IR offers solutions to many of our most pressing problems and we cannot afford to be left behind. The certainty is that the 4IR has arrived. The debates lie in how we respond to it. Tshilidzi Marwala deciphers it all, while providing a framework for navigating these shifts. A leading academic of international standing, and Deputy Chair of South Africa's Presidential 4IR Commission, Tshilidzi Marwala provides valuable insights into how leadership should be responding to the digital challenges of the 21st century.

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240

Publisher

Jonathan Ball Publishers

Published Date

ISBN 10

1776260848

ISBN 13

9781776260843

Leadership Lessons from Books I Have Read

The collective wisdom, knowledge and experience from the pages of fifty books

By: Tshilidzi Marwala

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Leadership Lessons from Books I Have Read

The collective wisdom, knowledge and experience from the pages of fifty books

By: Tshilidzi Marwala

Professor Marwala has sought to understand what good leadership should mean by drawing on the collective experience of authors who have written on many topics.' – Former President of South Africa, THABO MBEKI We cannot underestimate how critical strong leadership is in all aspects of our lives. It enables us to run our lives, homes, communities, workplaces and nations. Given its importance, it is pertinent to ask: What is the source of good leadership? Albert Einstein once said, 'The only source of knowledge is experience.' Many philosophers have observed this and, if we accept experience as the only source of knowledge, can we extend this conclusion to leadership? Or is the basis of good leadership intuition or instinct? Or is it perhaps a combination of these? In Leadership Lessons From Books I Have Read, Tshilidzi Marwala adopts the thesis that the source of good leadership is knowledge, and the source of knowledge is experience, which can take many forms: reading widely, listening, and engaging in discussion and debate with other knowledge seekers. If leadership is derived from knowledge and knowledge is derived from experience, the 'experience' in this book is from 50 books that Tshilidzi has read, and so the source of knowledge informing leadership is the collective experience of the more than 50 accomplished authors who wrote those books including, among others, Chinua Achebe, Thomas Sankara, NoViolet Bulawayo, Nelson Mandela, Mandla Mathebula, Eugène Marais, Chimamanda Ngozi Adichie, Jean-Jacques Rousseau, Daniel Kahneman, Karl Marx, Ngũgĩ wa Thiong'o, Nassim Taleb and Aristotle. Divided into four sections, Tshilidzi shares his leadership lessons in the areas of Africa and the diaspora, the search for the ideal polity, science, technology and society, and the leadership of nations. 'Those who do not read, should not lead.' – THILIDZI MARWALA

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291

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Jonathan Ball Publishers

Published Date

ISBN 10

1776260937

ISBN 13

9781776260935

On Rationality, Artificial Intelligence And Economics

By: Daniel Muller,Fernando Buarque,Tshilidzi Marwala

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On Rationality, Artificial Intelligence And Economics

By: Daniel Muller,Fernando Buarque,Tshilidzi Marwala

The world we live in presents plenty of tricky, impactful, and hard-tomake decisions to be taken. Sometimes the available options are ample, at other times they are apparently binary, either way, they often confront us with dilemmas, paradoxes, and even denial of values.In the dawn of the age of intelligence, when robots are gradually taking over most decision-making from humans, this book sheds a bit of light on decision rationale. It delves into the limits of these decision processes (for both humans and machines), and it does so by providing a new perspective that is somehow opposed to orthodox economics. All Economics reflections in this book are underlined and linked to Artificial Intelligence.The authors hope that this comprehensive and modern analysis, firmly grounded in the opinions of various groundbreaking Nobel laureate economists, may be helpful to a broad audience interested in how decisions may lead us all to flourishing societies. That is, societies in which economic blunders (caused by over simplification of problems and super estimation of tools) are reduced substantially.

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253

Publisher

World Scientific

Published Date

ISBN 10

981125513X

ISBN 13

9789811255137

Closing the Gap

The Fourth Industrial Revolution in Africa

By: Tshilidzi Marwala

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Closing the Gap

The Fourth Industrial Revolution in Africa

By: Tshilidzi Marwala

UPDATED EDITION ‘A holistic take on AI from an African perspective, Closing the Gap joins the dots on deploying AI efficiently into everyday business and life.’ – RENUKA METHIL, editor of Forbes Africa ‘This book simplifies complex concepts through relatable stories and awakens fellow Africans to the opportunities ushered in by the 4IR. Closing the Gapmust occupy our waking times.’ – MTETO NYATI, chief executive of Altron Closing the Gap is an accessible overview of the fourth industrial revolution (4IR) and the impact it is set to have on various sectors in South Africa and Africa. It explores the previous industrial revolutions that have led up to this point and outlines what South Africa’s position has been through each one. With a focus on artificial intelligence as a core concept in understanding the 4IR, this book uses familiar concepts to explain artificial intelligence, how it works and how it can be used in banking, mining, medicine and many other fields. Written from an African perspective, Closing the Gap addresses the challenges and fears around the 4IR by pointing to the opportunities presented by new technologies and outlining some of the challenges and successes to date.

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225

Publisher

Pan Macmillan South africa

Published Date

ISBN 10

1770108149

ISBN 13

9781770108141

Condition Monitoring Using Computational Intelligence Methods

Applications in Mechanical and Electrical Systems

By: Tshilidzi Marwala

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Condition Monitoring Using Computational Intelligence Methods

Applications in Mechanical and Electrical Systems

By: Tshilidzi Marwala

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.

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247

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Springer Science & Business Media

Published Date

ISBN 10

1447123794

ISBN 13

9781447123798

Hamiltonian Monte Carlo Methods in Machine Learning

By: Tshilidzi Marwala,Rendani Mbuvha,Wilson Tsakane Mongwe

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Hamiltonian Monte Carlo Methods in Machine Learning

By: Tshilidzi Marwala,Rendani Mbuvha,Wilson Tsakane Mongwe

Hamiltonian Monte Carlo Methods in Machine Learning introduces methods for optimal tuning of HMC parameters, along with an introduction of Shadow and Non-canonical HMC methods with improvements and speedup. Lastly, the authors address the critical issues of variance reduction for parameter estimates of numerous HMC based samplers. The book offers a comprehensive introduction to Hamiltonian Monte Carlo methods and provides a cutting-edge exposition of the current pathologies of HMC-based methods in both tuning, scaling and sampling complex real-world posteriors. These are mainly in the scaling of inference (e.g., Deep Neural Networks), tuning of performance-sensitive sampling parameters and high sample autocorrelation. Other sections provide numerous solutions to potential pitfalls, presenting advanced HMC methods with applications in renewable energy, finance and image classification for biomedical applications. Readers will get acquainted with both HMC sampling theory and algorithm implementation. - Provides in-depth analysis for conducting optimal tuning of Hamiltonian Monte Carlo (HMC) parameters - Presents readers with an introduction and improvements on Shadow HMC methods as well as non-canonical HMC methods - Demonstrates how to perform variance reduction for numerous HMC-based samplers - Includes source code from applications and algorithms

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Page Count

222

Publisher

Elsevier

Published Date

ISBN 10

0443190364

ISBN 13

9780443190360

Finite Element Model Updating Using Computational Intelligence Techniques

Applications to Structural Dynamics

By: Tshilidzi Marwala

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Finite Element Model Updating Using Computational Intelligence Techniques

Applications to Structural Dynamics

By: Tshilidzi Marwala

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.

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Page Count

250

Publisher

Springer

Published Date

ISBN 10

1849963223

ISBN 13

9781849963220

Probabilistic Finite Element Model Updating Using Bayesian Statistics

Applications to Aeronautical and Mechanical Engineering

By: Tshilidzi Marwala,Ilyes Boulkaibet,Sondipon Adhikari

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Probabilistic Finite Element Model Updating Using Bayesian Statistics

Applications to Aeronautical and Mechanical Engineering

By: Tshilidzi Marwala,Ilyes Boulkaibet,Sondipon Adhikari

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.

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