Download or read book Combination of uncertain ordinal expert statements The combination rule EIDMR and its application to low voltage grid classi cation with SVM written by Sebastian Breker and published by Infinite Study. This book was released on with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of expert knowledge is always more or less afflicted with uncertainties for many reasons: Expert knowledge may be imprecise, imperfect, or erroneous, for instance. If we ask several experts to label data (e.g., to assign class labels to given data objects, i.e. samples), we often state that these experts make different, sometimes conflicting statements.
Download or read book Classic Works of the Dempster Shafer Theory of Belief Functions written by Ronald R. Yager and published by Springer. This book was released on 2008-01-22 with total page 813 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a collection of classic research papers on the Dempster-Shafer theory of belief functions. The book is the authoritative reference in the field of evidential reasoning and an important archival reference in a wide range of areas including uncertainty reasoning in artificial intelligence and decision making in economics, engineering, and management. The book includes a foreword reflecting the development of the theory in the last forty years.
Download or read book Deep Learning Algorithms and Applications written by Witold Pedrycz and published by Springer Nature. This book was released on 2019-10-23 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm’s algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.
Download or read book Adaptive Dynamic Programming for Control written by Huaguang Zhang and published by Springer Science & Business Media. This book was released on 2012-12-14 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming in Discrete Time approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-horizon control, implemented in discrete-time nonlinear systems showing the reader how to obtain suboptimal control solutions within a fixed number of control steps and with results more easily applied in real systems than those usually gained from infinite-horizon control; • nonlinear games for which a pair of mixed optimal policies are derived for solving games both when the saddle point does not exist, and, when it does, avoiding the existence conditions of the saddle point. Non-zero-sum games are studied in the context of a single network scheme in which policies are obtained guaranteeing system stability and minimizing the individual performance function yielding a Nash equilibrium. In order to make the coverage suitable for the student as well as for the expert reader, Adaptive Dynamic Programming in Discrete Time: • establishes the fundamental theory involved clearly with each chapter devoted to a clearly identifiable control paradigm; • demonstrates convergence proofs of the ADP algorithms to deepen understanding of the derivation of stability and convergence with the iterative computational methods used; and • shows how ADP methods can be put to use both in simulation and in real applications. This text will be of considerable interest to researchers interested in optimal control and its applications in operations research, applied mathematics computational intelligence and engineering. Graduate students working in control and operations research will also find the ideas presented here to be a source of powerful methods for furthering their study.
Download or read book Reinforcement Learning and Approximate Dynamic Programming for Feedback Control written by Frank L. Lewis and published by John Wiley & Sons. This book was released on 2013-01-28 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.
Download or read book Intelligent Technical Systems written by Natividad Martínez Madrid and published by Springer Science & Business Media. This book was released on 2009-02-18 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent technical systems are networked, embedded systems incorporating real-time capacities that are able to interact with and adapt to their environments. These systems need innovative approaches in order to meet requirements like cost, size, power and memory consumption, as well as real-time compliance and security. Intelligent Technical Systems covers different levels like multimedia systems, embedded programming, middleware platforms, sensor networks and autonomous systems and applications for intelligent engineering. Each level is discussed by a set of original articles summarizing the state of the art and presenting a concrete application; they include a deep discussion of their model and explain all design decisions relevant to obtain a mature solution.
Download or read book Pattern Recognition ICPR International Workshops and Challenges written by Alberto Del Bimbo and published by Springer Nature. This book was released on 2021-02-20 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.
Download or read book Neutrosophy written by Florentin Smarandache and published by . This book was released on 1998 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Computational Intelligence written by Jing Liu and published by Springer. This book was released on 2012-05-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This state-of-the-art survey offers a renewed and refreshing focus on the progress in evolutionary computation, in neural networks, and in fuzzy systems. The book presents the expertise and experiences of leading researchers spanning a diverse spectrum of computational intelligence in these areas. The result is a balanced contribution to the research area of computational intelligence that should serve the community not only as a survey and a reference, but also as an inspiration for the future advancement of the state of the art of the field. The 13 selected chapters originate from lectures and presentations given at the IEEE World Congress on Computational Intelligence, WCCI 2012, held in Brisbane, Australia, in June 2012.
Download or read book Evolutionary Learning Advances in Theories and Algorithms written by Zhi-Hua Zhou and published by Springer. This book was released on 2019-05-22 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many machine learning tasks involve solving complex optimization problems, such as working on non-differentiable, non-continuous, and non-unique objective functions; in some cases it can prove difficult to even define an explicit objective function. Evolutionary learning applies evolutionary algorithms to address optimization problems in machine learning, and has yielded encouraging outcomes in many applications. However, due to the heuristic nature of evolutionary optimization, most outcomes to date have been empirical and lack theoretical support. This shortcoming has kept evolutionary learning from being well received in the machine learning community, which favors solid theoretical approaches. Recently there have been considerable efforts to address this issue. This book presents a range of those efforts, divided into four parts. Part I briefly introduces readers to evolutionary learning and provides some preliminaries, while Part II presents general theoretical tools for the analysis of running time and approximation performance in evolutionary algorithms. Based on these general tools, Part III presents a number of theoretical findings on major factors in evolutionary optimization, such as recombination, representation, inaccurate fitness evaluation, and population. In closing, Part IV addresses the development of evolutionary learning algorithms with provable theoretical guarantees for several representative tasks, in which evolutionary learning offers excellent performance.
Download or read book Organic Computing written by Sick, Bernhard and published by kassel university press GmbH. This book was released on 2014-01-01 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of twelve different contributions that reflect several aspects of OC research. Therefore, we introduced four major categories summarizing the contents of the contributions as well as describing the different aspects of OC research in general: (1) design and architectures, (2) trustworthiness, (3) self-learning, and (4) self-x properties.
Download or read book Fuzzy Set and Possibility Theory written by Ronald R. Yager and published by . This book was released on 1982 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Conflict Decision Method based on Quadratic Combination written by Xin Guan and published by Infinite Study. This book was released on with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many unsatisfactory situations in the existing improvement methods of evidence theory, such as a large amount of calculation, the normalization process is unreasonable, the evidence combination effect is not ideal in the conflict evidence decision-making process, and so on. This paper proposes a method based on quadratic combination of conflict evidence to improve the above situations. Firstly, a new flow chart of conflict evidence decision method based on quadratic combination is proposed. Secondly, a new multiplicative normalization rule is proposed, and the new rule is analyzed to verify its rationality. Thirdly, the shortcomings of the existing conflict measurement methods are analyzed, a new conflict measurement function is proposed, and the rationality of the new function is analyzed. Finally, through the analysis of the example and comparison with the existing evidence combination rules, the effectiveness of the method of this paper is verified.
Download or read book A novel decision probability transformation method based on belief interval written by Zhan Deng and published by Infinite Study. This book was released on with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Dempster–Shafer evidence theory, the basic probability assignment (BPA) can effectively represent and process uncertain information. How to transform the BPA of uncertain information into a decision probability remains a problem to be solved. In the light of this issue, we develop a novel decision probability transformation method to realize the transition from the belief decision to the probability decision in the framework of Dempster–Shafer evidence theory. The newly proposed method considers the transformation of BPA with multi-subset focal elements from the perspective of the belief interval, and applies the continuous interval argument ordered weighted average operator to quantify the data information contained in the belief interval for each singleton. Afterward, we present an approach to calculate the support degree of the singleton based on quantitative data information. According to the support degree of the singleton, the BPA of multi-subset focal elements is allocated reasonably. Furthermore, we introduce the concepts of probabilistic information content in this paper, which is utilized to evaluate the performance of the decision probability transformation method. Eventually, a few numerical examples and a practical application are given to demonstrate the rationality and accuracy of our proposed method.
