Author: Diego Oliva
Publisher: Springer Nature
ISBN: 3030705420
Category : Computational intelligence
Languages : en
Pages : 765
Book Description
This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.
Metaheuristics in Machine Learning: Theory and Applications
Author: Diego Oliva
Publisher: Springer Nature
ISBN: 3030705420
Category : Computational intelligence
Languages : en
Pages : 765
Book Description
This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.
Publisher: Springer Nature
ISBN: 3030705420
Category : Computational intelligence
Languages : en
Pages : 765
Book Description
This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.
Handbook of AI-based Metaheuristics
Author: Anand J. Kulkarni
Publisher: CRC Press
ISBN: 1000434257
Category : Computers
Languages : en
Pages : 584
Book Description
At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms. This will be a valuable reference for researchers in industry and academia, as well as for all Master’s and PhD students working in the metaheuristics and applications domains.
Publisher: CRC Press
ISBN: 1000434257
Category : Computers
Languages : en
Pages : 584
Book Description
At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms. This will be a valuable reference for researchers in industry and academia, as well as for all Master’s and PhD students working in the metaheuristics and applications domains.
Introduction to Mobile Robot Control
Author: Spyros G Tzafestas
Publisher: Elsevier
ISBN: 0124171036
Category : Technology & Engineering
Languages : en
Pages : 718
Book Description
Introduction to Mobile Robot Control provides a complete and concise study of modeling, control, and navigation methods for wheeled non-holonomic and omnidirectional mobile robots and manipulators. The book begins with a study of mobile robot drives and corresponding kinematic and dynamic models, and discusses the sensors used in mobile robotics. It then examines a variety of model-based, model-free, and vision-based controllers with unified proof of their stabilization and tracking performance, also addressing the problems of path, motion, and task planning, along with localization and mapping topics. The book provides a host of experimental results, a conceptual overview of systemic and software mobile robot control architectures, and a tour of the use of wheeled mobile robots and manipulators in industry and society. Introduction to Mobile Robot Control is an essential reference, and is also a textbook suitable as a supplement for many university robotics courses. It is accessible to all and can be used as a reference for professionals and researchers in the mobile robotics field. - Clearly and authoritatively presents mobile robot concepts - Richly illustrated throughout with figures and examples - Key concepts demonstrated with a host of experimental and simulation examples - No prior knowledge of the subject is required; each chapter commences with an introduction and background
Publisher: Elsevier
ISBN: 0124171036
Category : Technology & Engineering
Languages : en
Pages : 718
Book Description
Introduction to Mobile Robot Control provides a complete and concise study of modeling, control, and navigation methods for wheeled non-holonomic and omnidirectional mobile robots and manipulators. The book begins with a study of mobile robot drives and corresponding kinematic and dynamic models, and discusses the sensors used in mobile robotics. It then examines a variety of model-based, model-free, and vision-based controllers with unified proof of their stabilization and tracking performance, also addressing the problems of path, motion, and task planning, along with localization and mapping topics. The book provides a host of experimental results, a conceptual overview of systemic and software mobile robot control architectures, and a tour of the use of wheeled mobile robots and manipulators in industry and society. Introduction to Mobile Robot Control is an essential reference, and is also a textbook suitable as a supplement for many university robotics courses. It is accessible to all and can be used as a reference for professionals and researchers in the mobile robotics field. - Clearly and authoritatively presents mobile robot concepts - Richly illustrated throughout with figures and examples - Key concepts demonstrated with a host of experimental and simulation examples - No prior knowledge of the subject is required; each chapter commences with an introduction and background
Corporate Financial Distress
Author: Edward I. Altman
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 408
Book Description
"A Wiley-Interscience publication."Includes index. Bibliography: p. 355-361.
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 408
Book Description
"A Wiley-Interscience publication."Includes index. Bibliography: p. 355-361.
Race and Social Equity
Author: Susan T Gooden
Publisher: Routledge
ISBN: 1317461452
Category : Biography & Autobiography
Languages : en
Pages : 224
Book Description
In this compelling book the author contends that social equity--specifically racial equity--is a nervous area of government. Over the course of history, this nervousness has stifled many individuals and organizations, thus leading to an inability to seriously advance the reduction of racial inequities in government. The author asserts that until this nervousness is effectively managed, public administration social equity efforts designed to reduce racial inequities cannot realize their full potential.
Publisher: Routledge
ISBN: 1317461452
Category : Biography & Autobiography
Languages : en
Pages : 224
Book Description
In this compelling book the author contends that social equity--specifically racial equity--is a nervous area of government. Over the course of history, this nervousness has stifled many individuals and organizations, thus leading to an inability to seriously advance the reduction of racial inequities in government. The author asserts that until this nervousness is effectively managed, public administration social equity efforts designed to reduce racial inequities cannot realize their full potential.
Seismic Data Interpretation and Evaluation for Hydrocarbon Exploration and Production
Author: Niranjan C. Nanda
Publisher: Springer
ISBN: 3319264915
Category : Science
Languages : en
Pages : 230
Book Description
This book introduces readers to the field of seismic data interpretation and evaluation, covering themes such as petroleum exploration and high resolution seismic data. It helps geoscientists and engineers who are practitioners in this area to both understand and to avoid the potential pitfalls of interpreting and evaluating such data, especially the over-reliance on sophisticated software packages and workstations alongside a lack of grasp on the elementary principles of geology and geophysics. Chapters elaborate on the necessary principles, from topics like seismic wave propagation and rock-fluid parameters to seismic modeling and inversions, explaining the need to understand geological implications. The difference between interpretation of data and its evaluation is highlighted and the author encourages imaginative, logical and practical application of knowledge. Readers will appreciate the exquisite illustrations included with the accessibly written text, which simplify the process of learning about interpretation of seismic data. This multidisciplinary, integrated and practical approach to data evaluation will prove to be a valuable tool for students and young professionals, especially those connected with oil companies.
Publisher: Springer
ISBN: 3319264915
Category : Science
Languages : en
Pages : 230
Book Description
This book introduces readers to the field of seismic data interpretation and evaluation, covering themes such as petroleum exploration and high resolution seismic data. It helps geoscientists and engineers who are practitioners in this area to both understand and to avoid the potential pitfalls of interpreting and evaluating such data, especially the over-reliance on sophisticated software packages and workstations alongside a lack of grasp on the elementary principles of geology and geophysics. Chapters elaborate on the necessary principles, from topics like seismic wave propagation and rock-fluid parameters to seismic modeling and inversions, explaining the need to understand geological implications. The difference between interpretation of data and its evaluation is highlighted and the author encourages imaginative, logical and practical application of knowledge. Readers will appreciate the exquisite illustrations included with the accessibly written text, which simplify the process of learning about interpretation of seismic data. This multidisciplinary, integrated and practical approach to data evaluation will prove to be a valuable tool for students and young professionals, especially those connected with oil companies.
Practical Propensity Score Methods Using R
Author: Walter Leite
Publisher: SAGE Publications
ISBN: 1483313395
Category : Social Science
Languages : en
Pages : 225
Book Description
Practical Propensity Score Methods Using R by Walter Leite is a practical book that uses a step-by-step analysis of realistic examples to help students understand the theory and code for implementing propensity score analysis with the R statistical language. With a comparison of both well-established and cutting-edge propensity score methods, the text highlights where solid guidelines exist to support best practices and where there is scarcity of research. Readers will find that this scaffolded approach to R and the book’s free online resources help them apply the text’s concepts to the analysis of their own data.
Publisher: SAGE Publications
ISBN: 1483313395
Category : Social Science
Languages : en
Pages : 225
Book Description
Practical Propensity Score Methods Using R by Walter Leite is a practical book that uses a step-by-step analysis of realistic examples to help students understand the theory and code for implementing propensity score analysis with the R statistical language. With a comparison of both well-established and cutting-edge propensity score methods, the text highlights where solid guidelines exist to support best practices and where there is scarcity of research. Readers will find that this scaffolded approach to R and the book’s free online resources help them apply the text’s concepts to the analysis of their own data.
Agents and Multi-Agent Systems: Technologies and Applications 2020
Author: G. Jezic
Publisher: Springer
ISBN: 9789811557668
Category : Technology & Engineering
Languages : en
Pages : 368
Book Description
The book highlights new trends and challenges in research on agents and the new digital and knowledge economy. It includes papers on business process management, agent-based modeling and simulation and anthropic-oriented computing that were originally presented at the 14th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2020), being held as a Virtual Conference in June 17–19, 2020. The respective papers cover topics such as software agents, multi-agent systems, agent modeling, mobile and cloud computing, big data analysis, business intelligence, artificial intelligence, social systems, computer embedded systems and nature inspired manufacturing, all of which contribute to the modern digital economy.
Publisher: Springer
ISBN: 9789811557668
Category : Technology & Engineering
Languages : en
Pages : 368
Book Description
The book highlights new trends and challenges in research on agents and the new digital and knowledge economy. It includes papers on business process management, agent-based modeling and simulation and anthropic-oriented computing that were originally presented at the 14th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2020), being held as a Virtual Conference in June 17–19, 2020. The respective papers cover topics such as software agents, multi-agent systems, agent modeling, mobile and cloud computing, big data analysis, business intelligence, artificial intelligence, social systems, computer embedded systems and nature inspired manufacturing, all of which contribute to the modern digital economy.
Scalable Optimization via Probabilistic Modeling
Author: Martin Pelikan
Publisher: Springer Science & Business Media
ISBN: 3540349537
Category : Mathematics
Languages : en
Pages : 363
Book Description
I’m not usually a fan of edited volumes. Too often they are an incoherent hodgepodge of remnants, renegades, or rejects foisted upon an unsuspecting reading public under a misleading or fraudulent title. The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited volumes fail. For example, take the title, Scalable Optimization via Probabilistic M- eling: From Algorithms to Applications. You need not worry that you’re going to pick up this book and ?nd stray articles about anything else. This book focuseslikealaserbeamononeofthehottesttopicsinevolutionary compu- tion over the last decade or so: estimation of distribution algorithms (EDAs). EDAs borrow evolutionary computation’s population orientation and sel- tionism and throw out the genetics to give us a hybrid of substantial power, elegance, and extensibility. The article sequencing in most edited volumes is hard to understand, but from the get go the editors of this volume have assembled a set of articles sequenced in a logical fashion. The book moves from design to e?ciency enhancement and then concludes with relevant applications. The emphasis on e?ciency enhancement is particularly important, because the data-mining perspectiveimplicitinEDAsopensuptheworldofoptimizationtonewme- ods of data-guided adaptation that can further speed solutions through the construction and utilization of e?ective surrogates, hybrids, and parallel and temporal decompositions.
Publisher: Springer Science & Business Media
ISBN: 3540349537
Category : Mathematics
Languages : en
Pages : 363
Book Description
I’m not usually a fan of edited volumes. Too often they are an incoherent hodgepodge of remnants, renegades, or rejects foisted upon an unsuspecting reading public under a misleading or fraudulent title. The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited volumes fail. For example, take the title, Scalable Optimization via Probabilistic M- eling: From Algorithms to Applications. You need not worry that you’re going to pick up this book and ?nd stray articles about anything else. This book focuseslikealaserbeamononeofthehottesttopicsinevolutionary compu- tion over the last decade or so: estimation of distribution algorithms (EDAs). EDAs borrow evolutionary computation’s population orientation and sel- tionism and throw out the genetics to give us a hybrid of substantial power, elegance, and extensibility. The article sequencing in most edited volumes is hard to understand, but from the get go the editors of this volume have assembled a set of articles sequenced in a logical fashion. The book moves from design to e?ciency enhancement and then concludes with relevant applications. The emphasis on e?ciency enhancement is particularly important, because the data-mining perspectiveimplicitinEDAsopensuptheworldofoptimizationtonewme- ods of data-guided adaptation that can further speed solutions through the construction and utilization of e?ective surrogates, hybrids, and parallel and temporal decompositions.
Employment in Metropolitan Areas
Author: United States. Bureau of Labor Statistics
Publisher:
ISBN:
Category : Labor supply
Languages : en
Pages : 126
Book Description
Publisher:
ISBN:
Category : Labor supply
Languages : en
Pages : 126
Book Description