Identification for Prediction and Decision

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Author :
Publisher : Harvard University Press
ISBN 13 : 9780674033665
Total Pages : 370 pages
Book Rating : 4.0/5 (336 download)

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Book Synopsis Identification for Prediction and Decision by : Charles F. Manski

Download or read book Identification for Prediction and Decision written by Charles F. Manski and published by Harvard University Press. This book was released on 2009-06-30 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a full-scale exposition of Charles Manski's new methodology for analyzing empirical questions in the social sciences. He recommends that researchers first ask what can be learned from data alone, and then ask what can be learned when data are combined with credible weak assumptions. Inferences predicated on weak assumptions, he argues, can achieve wide consensus, while ones that require strong assumptions almost inevitably are subject to sharp disagreements. Building on the foundation laid in the author's Identification Problems in the Social Sciences (Harvard, 1995), the book's fifteen chapters are organized in three parts. Part I studies prediction with missing or otherwise incomplete data. Part II concerns the analysis of treatment response, which aims to predict outcomes when alternative treatment rules are applied to a population. Part III studies prediction of choice behavior. Each chapter juxtaposes developments of methodology with empirical or numerical illustrations. The book employs a simple notation and mathematical apparatus, using only basic elements of probability theory.

Neural Networks for Identification, Prediction and Control

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 1447132440
Total Pages : 243 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Neural Networks for Identification, Prediction and Control by : Duc T. Pham

Download or read book Neural Networks for Identification, Prediction and Control written by Duc T. Pham and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, there has been a growing interest in applying neural networks to dynamic systems identification (modelling), prediction and control. Neural networks are computing systems characterised by the ability to learn from examples rather than having to be programmed in a conventional sense. Their use enables the behaviour of complex systems to be modelled and predicted and accurate control to be achieved through training, without a priori information about the systems' structures or parameters. This book describes examples of applications of neural networks In modelling, prediction and control. The topics covered include identification of general linear and non-linear processes, forecasting of river levels, stock market prices and currency exchange rates, and control of a time-delayed plant and a two-joint robot. These applications employ the major types of neural networks and learning algorithms. The neural network types considered in detail are the muhilayer perceptron (MLP), the Elman and Jordan networks and the Group-Method-of-Data-Handling (GMDH) network. In addition, cerebellar-model-articulation-controller (CMAC) networks and neuromorphic fuzzy logic systems are also presented. The main learning algorithm adopted in the applications is the standard backpropagation (BP) algorithm. Widrow-Hoff learning, dynamic BP and evolutionary learning are also described.

Signal Analysis and Prediction

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Publisher : Springer Science & Business Media
ISBN 13 : 9780817640422
Total Pages : 536 pages
Book Rating : 4.6/5 (44 download)

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Book Synopsis Signal Analysis and Prediction by : Ales Prochazka

Download or read book Signal Analysis and Prediction written by Ales Prochazka and published by Springer Science & Business Media. This book was released on 1998-12-23 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods of signal analysis represent a broad research topic with applications in many disciplines, including engineering, technology, biomedicine, seismography, eco nometrics, and many others based upon the processing of observed variables. Even though these applications are widely different, the mathematical background be hind them is similar and includes the use of the discrete Fourier transform and z-transform for signal analysis, and both linear and non-linear methods for signal identification, modelling, prediction, segmentation, and classification. These meth ods are in many cases closely related to optimization problems, statistical methods, and artificial neural networks. This book incorporates a collection of research papers based upon selected contri butions presented at the First European Conference on Signal Analysis and Predic tion (ECSAP-97) in Prague, Czech Republic, held June 24-27, 1997 at the Strahov Monastery. Even though the Conference was intended as a European Conference, at first initiated by the European Association for Signal Processing (EURASIP), it was very gratifying that it also drew significant support from other important scientific societies, including the lEE, Signal Processing Society of IEEE, and the Acoustical Society of America. The organizing committee was pleased that the re sponse from the academic community to participate at this Conference was very large; 128 summaries written by 242 authors from 36 countries were received. In addition, the Conference qualified under the Continuing Professional Development Scheme to provide PD units for participants and contributors.

A Set-membership Approach to the Identification and Prediction of Ill-defined Systems

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Author :
Publisher :
ISBN 13 : 9789090026237
Total Pages : 134 pages
Book Rating : 4.0/5 (262 download)

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Book Synopsis A Set-membership Approach to the Identification and Prediction of Ill-defined Systems by : Karel Jacob Keesman

Download or read book A Set-membership Approach to the Identification and Prediction of Ill-defined Systems written by Karel Jacob Keesman and published by . This book was released on 1989 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A New Approach to Identification and Prediction of El Nino

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Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (131 download)

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Book Synopsis A New Approach to Identification and Prediction of El Nino by : J. A. Flueck

Download or read book A New Approach to Identification and Prediction of El Nino written by J. A. Flueck and published by . This book was released on 1987 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

LISS 2020

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Author :
Publisher : Springer Nature
ISBN 13 : 9813343591
Total Pages : 1056 pages
Book Rating : 4.8/5 (133 download)

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Book Synopsis LISS 2020 by : Shifeng Liu

Download or read book LISS 2020 written by Shifeng Liu and published by Springer Nature. This book was released on 2021-04-10 with total page 1056 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the proceedings of the 10th International Conference on Logistics, Informatics and Service Sciences (LISS 2020), which is co-organized by Beijing Jiaotong University, Budapest University of Technology and Economics, in July 25–28 2020. This book focuses on the “AI and data-driven technical and management innovation in logistics, informatics and services” and aims to provide new research methods, theories and applications from various areas of management and engineering. In detail the included scientific papers analyse and describe communication processes in the fields of logistics, informatics, service sciences and other related areas. The variety of papers delivers added value for both scholars and practitioners. Information and communication technologies have been providing an effective network infrastructure and development platform for logistics and service operations.

Identification for Prediction and Decision

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Author :
Publisher : Harvard University Press
ISBN 13 : 9780674026537
Total Pages : 0 pages
Book Rating : 4.0/5 (265 download)

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Book Synopsis Identification for Prediction and Decision by : Charles F. Manski

Download or read book Identification for Prediction and Decision written by Charles F. Manski and published by Harvard University Press. This book was released on 2008-01-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a full-scale exposition of Charles Manski's new methodology for analyzing empirical questions in the social sciences. He recommends that researchers first ask what can be learned from data alone, and then ask what can be learned when data are combined with credible weak assumptions. Inferences predicated on weak assumptions, he argues, can achieve wide consensus, while ones that require strong assumptions almost inevitably are subject to sharp disagreements. Building on the foundation laid in the author's Identification Problems in the Social Sciences (Harvard, 1995), the book's fifteen chapters are organized in three parts. Part I studies prediction with missing or otherwise incomplete data. Part II concerns the analysis of treatment response, which aims to predict outcomes when alternative treatment rules are applied to a population. Part III studies prediction of choice behavior. Each chapter juxtaposes developments of methodology with empirical or numerical illustrations. The book employs a simple notation and mathematical apparatus, using only basic elements of probability theory.

Drug-like Properties: Concepts, Structure Design and Methods

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Author :
Publisher : Elsevier
ISBN 13 : 0080557619
Total Pages : 549 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Drug-like Properties: Concepts, Structure Design and Methods by : Li Di

Download or read book Drug-like Properties: Concepts, Structure Design and Methods written by Li Di and published by Elsevier. This book was released on 2010-07-26 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Of the thousands of novel compounds that a drug discovery project team invents and that bind to the therapeutic target, typically only a fraction of these have sufficient ADME/Tox properties to become a drug product. Understanding ADME/Tox is critical for all drug researchers, owing to its increasing importance in advancing high quality candidates to clinical studies and the processes of drug discovery. If the properties are weak, the candidate will have a high risk of failure or be less desirable as a drug product. This book is a tool and resource for scientists engaged in, or preparing for, the selection and optimization process. The authors describe how properties affect in vivo pharmacological activity and impact in vitro assays. Individual drug-like properties are discussed from a practical point of view, such as solubility, permeability and metabolic stability, with regard to fundamental understanding, applications of property data in drug discovery and examples of structural modifications that have achieved improved property performance. The authors also review various methods for the screening (high throughput), diagnosis (medium throughput) and in-depth (low throughput) analysis of drug properties. - Serves as an essential working handbook aimed at scientists and students in medicinal chemistry - Provides practical, step-by-step guidance on property fundamentals, effects, structure-property relationships, and structure modification strategies - Discusses improvements in pharmacokinetics from a practical chemist's standpoint

Accuracy of the Comprehensive Identification Process in the Prediction of Early School Success

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Publisher :
ISBN 13 :
Total Pages : 124 pages
Book Rating : 4.:/5 (17 download)

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Book Synopsis Accuracy of the Comprehensive Identification Process in the Prediction of Early School Success by : Carolyn S. Schwent

Download or read book Accuracy of the Comprehensive Identification Process in the Prediction of Early School Success written by Carolyn S. Schwent and published by . This book was released on 1983 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

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Publisher : IGI Global
ISBN 13 : 1799827437
Total Pages : 586 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning by : Rani, Geeta

Download or read book Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning written by Rani, Geeta and published by IGI Global. This book was released on 2020-10-16 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

On the Identification and Prediction of Nonlinear Models

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Publisher :
ISBN 13 :
Total Pages : 16 pages
Book Rating : 4.:/5 (354 download)

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Book Synopsis On the Identification and Prediction of Nonlinear Models by : Dominique Guegan

Download or read book On the Identification and Prediction of Nonlinear Models written by Dominique Guegan and published by . This book was released on 1990 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Identification of Linear Systems

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Publisher : Elsevier
ISBN 13 : 0080912567
Total Pages : 353 pages
Book Rating : 4.0/5 (89 download)

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Book Synopsis Identification of Linear Systems by : J. Schoukens

Download or read book Identification of Linear Systems written by J. Schoukens and published by Elsevier. This book was released on 2014-06-28 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concentrates on the problem of accurate modeling of linear systems. It presents a thorough description of a method of modeling a linear dynamic invariant system by its transfer function. The first two chapters provide a general introduction and review for those readers who are unfamiliar with identification theory so that they have a sufficient background knowledge for understanding the methods described later. The main body of the book looks at the basic method used by the authors to estimate the parameter of the transfer function, how it is possible to optimize the excitation signals. Further chapters extend the estimation method proposed. Applications are then discussed and the book concludes with practical guidelines which illustrate the method and offer some rules-of-thumb.

System Identification

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Publisher : Pearson Education
ISBN 13 : 0132440539
Total Pages : 875 pages
Book Rating : 4.1/5 (324 download)

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Book Synopsis System Identification by : Lennart Ljung

Download or read book System Identification written by Lennart Ljung and published by Pearson Education. This book was released on 1998-12-29 with total page 875 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field's leading text, now completely updated. Modeling dynamical systems — theory, methodology, and applications. Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-fuzzy modeling. The book contains many new computer-based examples designed for Ljung's market-leading software, System Identification Toolbox for MATLAB. Ljung combines careful mathematics, a practical understanding of real-world applications, and extensive exercises. He introduces both black-box and tailor-made models of linear as well as non-linear systems, and he describes principles, properties, and algorithms for a variety of identification techniques: Nonparametric time-domain and frequency-domain methods. Parameter estimation methods in a general prediction error setting. Frequency domain data and frequency domain interpretations. Asymptotic analysis of parameter estimates. Linear regressions, iterative search methods, and other ways to compute estimates. Recursive (adaptive) estimation techniques. Ljung also presents detailed coverage of the key issues that can make or break system identification projects, such as defining objectives, designing experiments, controlling the bias distribution of transfer-function estimates, and carefully validating the resulting models. The first edition of System Identification has been the field's most widely cited reference for over a decade. This new edition will be the new text of choice for anyone concerned with system identification theory and practice.

Prediction and Analysis for Knowledge Representation and Machine Learning

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Publisher : CRC Press
ISBN 13 : 1000484211
Total Pages : 232 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Prediction and Analysis for Knowledge Representation and Machine Learning by : Avadhesh Kumar

Download or read book Prediction and Analysis for Knowledge Representation and Machine Learning written by Avadhesh Kumar and published by CRC Press. This book was released on 2022-01-31 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system’s perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems. Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book’s website. Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarter This book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which include both basic and advanced concepts.

Machine Learning Techniques on Gene Function Prediction Volume II

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Publisher : Frontiers Media SA
ISBN 13 : 2889766322
Total Pages : 264 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Machine Learning Techniques on Gene Function Prediction Volume II by : Quan Zou

Download or read book Machine Learning Techniques on Gene Function Prediction Volume II written by Quan Zou and published by Frontiers Media SA. This book was released on 2023-04-11 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Identification and Prediction of RNA Signal Expression of Species

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Publisher :
ISBN 13 :
Total Pages : 274 pages
Book Rating : 4.:/5 (635 download)

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Book Synopsis Identification and Prediction of RNA Signal Expression of Species by : 蔡昆男

Download or read book Identification and Prediction of RNA Signal Expression of Species written by 蔡昆男 and published by . This book was released on 2009 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Predicting Structured Data

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Publisher : MIT Press
ISBN 13 : 0262026171
Total Pages : 361 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Predicting Structured Data by : Neural Information Processing Systems Foundation

Download or read book Predicting Structured Data written by Neural Information Processing Systems Foundation and published by MIT Press. This book was released on 2007 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.