Machine Learning Control By Symbolic Regression

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Machine Learning Control By Symbolic Regression
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Author : Askhat Diveev
language : en
Publisher: Springer Nature
Release Date : 2021-10-23
Machine Learning Control By Symbolic Regression written by Askhat Diveev and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-23 with Computers categories.
This book provides comprehensive coverage on a new direction in computational mathematics research: automatic search for formulas. Formulas must be sought in all areas of science and life: these are the laws of the universe, the macro and micro world, fundamental physics, engineering, weather and natural disasters forecasting; the search for new laws in economics, politics, sociology. Accumulating many years of experience in the development and application of numerical methods of symbolic regression to solving control problems, the authors offer new possibilities not only in the field of control automation, but also in the design of completely different optimal structures in many fields. For specialists in the field of control, Machine Learning Control by Symbolic Regression opens up a new promising direction of research and acquaints scientists with the methods of automatic construction of control systems.For specialists in the field of machine learning, the book opens up a new, much broader direction than neural networks: methods of symbolic regression. This book makes it easy to master this new area in machine learning and apply this approach everywhere neural networks are used. For mathematicians, the book opens up a new approach to the construction of numerical methods for obtaining analytical solutions to unsolvable problems; for example, numerical analytical solutions of algebraic equations, differential equations, non-trivial integrals, etc. For specialists in the field of artificial intelligence, the book offers a machine way to solve problems, framed in the form of analytical relationships.
Machine Learning Control Taming Nonlinear Dynamics And Turbulence
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Author : Thomas Duriez
language : en
Publisher: Springer
Release Date : 2016-11-02
Machine Learning Control Taming Nonlinear Dynamics And Turbulence written by Thomas Duriez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-02 with Technology & Engineering categories.
This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in Chapters 1 and 2. In Chapter 3, methods of linear control theory are reviewed. In Chapter 4, MLC is shown to reproduce known optimal control laws for linear dynamics (LQR, LQG). In Chapter 5, MLC detects and exploits a strongly nonlinear actuation mechanism of a low-dimensional dynamical system when linear control methods are shown to fail. Experimental control demonstrations from a laminar shear-layer to turbulent boundary-layers are reviewed in Chapter 6, followed by general good practices for experiments in Chapter 7. The book concludes with an outlook on the vast future applications of MLC in Chapter 8. Matlab codes are provided for easy reproducibility of the presented results. The book includes interviews with leading researchers in turbulence control (S. Bagheri, B. Batten, M. Glauser, D. Williams) and machine learning (M. Schoenauer) for a broader perspective. All chapters have exercises and supplemental videos will be available through YouTube.
Machine Learning And Knowledge Discovery In Databases Research Track
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Author : Danai Koutra
language : en
Publisher: Springer Nature
Release Date : 2023-09-17
Machine Learning And Knowledge Discovery In Databases Research Track written by Danai Koutra and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-17 with Computers categories.
The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part III: Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning. Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part V: Robustness; Time Series; Transfer and Multitask Learning. Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.
Intelligent Computing
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Author : Kohei Arai
language : en
Publisher: Springer Nature
Release Date : 2021-07-12
Intelligent Computing written by Kohei Arai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-12 with Technology & Engineering categories.
This book is a comprehensive collection of chapters focusing on the core areas of computing and their further applications in the real world. Each chapter is a paper presented at the Computing Conference 2021 held on 15-16 July 2021. Computing 2021 attracted a total of 638 submissions which underwent a double-blind peer review process. Of those 638 submissions, 235 submissions have been selected to be included in this book. The goal of this conference is to give a platform to researchers with fundamental contributions and to be a premier venue for academic and industry practitioners to share new ideas and development experiences. We hope that readers find this volume interesting and valuable as it provides the state-of-the-art intelligent methods and techniques for solving real-world problems. We also expect that the conference and its publications is a trigger for further related research and technology improvements in this important subject.
Machine Learning And Knowledge Discovery In Databases Research Track And Demo Track
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Author : Albert Bifet
language : en
Publisher: Springer Nature
Release Date : 2024-09-01
Machine Learning And Knowledge Discovery In Databases Research Track And Demo Track written by Albert Bifet and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-01 with Computers categories.
This multi-volume set, LNAI 14941 to LNAI 14950, constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2024, held in Vilnius, Lithuania, in September 2024. The papers presented in these proceedings are from the following three conference tracks: - Research Track: The 202 full papers presented here, from this track, were carefully reviewed and selected from 826 submissions. These papers are present in the following volumes: Part I, II, III, IV, V, VI, VII, VIII. Demo Track: The 14 papers presented here, from this track, were selected from 30 submissions. These papers are present in the following volume: Part VIII. Applied Data Science Track: The 56 full papers presented here, from this track, were carefully reviewed and selected from 224 submissions. These papers are present in the following volumes: Part IX and Part X. Chapter “1 and 24” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Numerical Computations Theory And Algorithms
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Author : Yaroslav D. Sergeyev
language : en
Publisher: Springer Nature
Release Date : 2024-12-31
Numerical Computations Theory And Algorithms written by Yaroslav D. Sergeyev and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-31 with Computers categories.
The three-volume set LNCS 14476-14478 constitutes the post conference proceedings of the 4th International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2023, held in Pizzo Calabro, Italy, during June 14–20, 2023. The 45 full papers presented in this book together with 60 short papers were carefully reviewed and selected from 170 submissions. The papers focus on topics such as: continuous and discrete single- and multi-objective problems, local, global and large-scale optimization, classification in machine learning, optimal control, and applications; computational and applied mathematics (such as approximation theory, computational geometry, computational fluid dynamics, dynamical systems and differential equations, numerical algebra, etc.) and applications in engineering and science; numerical models, methods and software using traditional and emerging high-performance computational tools and paradigms (including the infinity and quantum computing) and their application in artificial intelligence and data science, bioinformatics, economics and management, engineering and technology, mathematical education, number theory and foundations of mathematics, etc.
Explainable Artificial Intelligence
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Author : Luca Longo
language : en
Publisher: Springer Nature
Release Date : 2024-07-09
Explainable Artificial Intelligence written by Luca Longo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-09 with Computers categories.
This four-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2024, held in Valletta, Malta, during July 17-19, 2024. The 95 full papers presented were carefully reviewed and selected from 204 submissions. The conference papers are organized in topical sections on: Part I - intrinsically interpretable XAI and concept-based global explainability; generative explainable AI and verifiability; notion, metrics, evaluation and benchmarking for XAI. Part II - XAI for graphs and computer vision; logic, reasoning, and rule-based explainable AI; model-agnostic and statistical methods for eXplainable AI. Part III - counterfactual explanations and causality for eXplainable AI; fairness, trust, privacy, security, accountability and actionability in eXplainable AI. Part IV - explainable AI in healthcare and computational neuroscience; explainable AI for improved human-computer interaction and software engineering for explainability; applications of explainable artificial intelligence.
Frontiers In Robotics And Electromechanics
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Author : Andrey Ronzhin
language : en
Publisher: Springer Nature
Release Date : 2023-03-01
Frontiers In Robotics And Electromechanics written by Andrey Ronzhin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-01 with Technology & Engineering categories.
This book introduces intellectual control systems and electromechanics of heterogeneous robots. The book uncovers fundamental principles of robot control and recent developments in software and hardware of robots. The book presents solutions and discusses problems of single robotic devices as well as heterogeneous robotic teams while performing technological tasks that require informational, physical or energetic interaction with human users, environment and other robots. The book considers model–algorithmic and software–hardware control of ground, water and underwater robots, unmanned aerial vehicles, as well as their embedded and attached sub-systems, including manipulators, end-effectors, sensors, actuators, etc. The book will be useful for researchers of interdisciplinary issues related to robotics, electromechanics and artificial intelligence. The book is recommended for graduate students with a major/minor in the areas of robotics and mechatronics, management in technical systems, Internet of Things, artificial intelligence, electrical engineering, mechanical engineering and computer science.
Handbook Of Evolutionary Machine Learning
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Author : Wolfgang Banzhaf
language : en
Publisher: Springer Nature
Release Date : 2023-11-01
Handbook Of Evolutionary Machine Learning written by Wolfgang Banzhaf and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-01 with Computers categories.
This book, written by leading international researchers of evolutionary approaches to machine learning, explores various ways evolution can address machine learning problems and improve current methods of machine learning. Topics in this book are organized into five parts. The first part introduces some fundamental concepts and overviews of evolutionary approaches to the three different classes of learning employed in machine learning. The second addresses the use of evolutionary computation as a machine learning technique describing methodologic improvements for evolutionary clustering, classification, regression, and ensemble learning. The third part explores the connection between evolution and neural networks, in particular the connection to deep learning, generative and adversarial models as well as the exciting potential of evolution with large language models. The fourth part focuses on the use of evolutionary computation for supporting machine learning methods. This includes methodological developments for evolutionary data preparation, model parametrization, design, and validation. The final part covers several chapters on applications in medicine, robotics, science, finance, and other disciplines. Readers find reviews of application areas and can discover large-scale, real-world applications of evolutionary machine learning to a variety of problem domains. This book will serve as an essential reference for researchers, postgraduate students, practitioners in industry and all those interested in evolutionary approaches to machine learning.
Basic Chemometrics For Analytical Chemists
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Author : Jose Manuel Andrade Garda
language : en
Publisher: World Scientific
Release Date : 2025-06-06
Basic Chemometrics For Analytical Chemists written by Jose Manuel Andrade Garda and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Science categories.
This textbook provides undergraduate students with comprehensive and accessible instruction in the fundamentals of chemometrics. This branch of analytical chemistry is devoted to the optimisation and implementation of analytical methods and the use of statistical and informatic tools. Readers will receive detailed and practical training in how to devise efficient and reliable analytical methodologies using experimental design and signal calibration. They will also learn how to extract meaningful information using multivariate data analysis. The exercises contained within the volume will provide easy-to-follow standard protocols and guide students in the use of the valuable and freely available open-source software CAT (Chemometric Agile Tool).This book is a much-needed tool for undergraduate students in the modern academic environment. The theoretical and practical guidance it provides, alongside the dedicated software, is tailored to bridge any gaps in formal instruction and help inexperienced students excel in the field of chemometrics.