Neural Novel Hybrid Algorithms For Time Series Prediction

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Neural, Novel & Hybrid Algorithms for Time Series Prediction

Author : Timothy Masters
Publisher :
ISBN 13 :
Total Pages : 548 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Neural, Novel & Hybrid Algorithms for Time Series Prediction by : Timothy Masters

Download or read book Neural, Novel & Hybrid Algorithms for Time Series Prediction written by Timothy Masters and published by . This book was released on 1995-10-20 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative guide to predicting the future using neural, novel, and hybrid algorithms Expert Timothy Masters provides you with carefully paced, step-by-step advice and guidance plus the proven tools and techniques you need to develop successful applications for business forecasting, stock market prediction, engineering process control, economic cycle tracking, marketing analysis, and more. Neural, Novel & Hybrid Algorithms for Time Series Prediction provides information on: * Robust confidence intervals for predictions made with neural, ARIMA, and other models * Wavelets for detecting features that presage important events * Multivariate ARMA models for simultaneous prediction of multiple series based on multiple inputs and shocks * Hybrid ARMA/neural models to improve the accuracy of predictions * Data reduction and orthogonalization using principal components and related operations * Digital filters for preprocessing to enhance useful information and suppress noise * Diagnostic tools such as the maximum entropy spectrum and Savitzky-Golay filters for suggesting and validating prediction models * Effective preprocessing techniques for prediction with neural networks CD-ROM INCLUDES: * PREDICT-both DOS and Windows NT versions-a powerful time series program that can be easily customized to make accurate predictions in any application area * Much useful source code, including the complex-general multivariate fast Fourier transform in both C++ and Pentium-optimized assembler

Handbook of Neural Computation

Author : Pijush Samui
Publisher : Academic Press
ISBN 13 : 0128113197
Total Pages : 660 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Handbook of Neural Computation by : Pijush Samui

Download or read book Handbook of Neural Computation written by Pijush Samui and published by Academic Press. This book was released on 2017-07-18 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Artificial Neural Nets and Genetic Algorithms

Author : Andrej Dobnikar
Publisher : Springer Science & Business Media
ISBN 13 : 9783211833643
Total Pages : 190 pages
Book Rating : 4.8/5 (336 download)

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Book Synopsis Artificial Neural Nets and Genetic Algorithms by : Andrej Dobnikar

Download or read book Artificial Neural Nets and Genetic Algorithms written by Andrej Dobnikar and published by Springer Science & Business Media. This book was released on 1999-07-15 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the contents: Neural networks – theory and applications: NNs (= neural networks) classifier on continuous data domains– quantum associative memory – a new class of neuron-like discrete filters to image processing – modular NNs for improving generalisation properties – presynaptic inhibition modelling for image processing application – NN recognition system for a curvature primal sketch – NN based nonlinear temporal-spatial noise rejection system – relaxation rate for improving Hopfield network – Oja's NN and influence of the learning gain on its dynamics Genetic algorithms – theory and applications: transposition: a biological-inspired mechanism to use with GAs (= genetic algorithms) – GA for decision tree induction – optimising decision classifications using GAs – scheduling tasks with intertask communication onto multiprocessors by GAs – design of robust networks with GA – effect of degenerate coding on GAs – multiple traffic signal control using a GA – evolving musical harmonisation – niched-penalty approach for constraint handling in GAs – GA with dynamic population size – GA with dynamic niche clustering for multimodal function optimisation Soft computing and uncertainty: self-adaptation of evolutionary constructed decision trees by information spreading – evolutionary programming of near optimal NNs

Advanced Algorithms for Neural Networks

Author : Timothy Masters
Publisher :
ISBN 13 :
Total Pages : 456 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Advanced Algorithms for Neural Networks by : Timothy Masters

Download or read book Advanced Algorithms for Neural Networks written by Timothy Masters and published by . This book was released on 1995-04-17 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is one of the first books to offer practical in-depth coverage of the Probabilistic Neural Network (PNN) and several other neural nets and their related algorithms critical to solving some of today's toughest real-world computing problems. Includes complete C++ source code for basic and advanced applications.

TIME SERIES FORECASTING USING NEURAL NETWORKS. EXAMPLES WITH MATLAB

Author : Cesar Perez Lopez
Publisher : CESAR PEREZ
ISBN 13 :
Total Pages : 283 pages
Book Rating : 4./5 ( download)

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Book Synopsis TIME SERIES FORECASTING USING NEURAL NETWORKS. EXAMPLES WITH MATLAB by : Cesar Perez Lopez

Download or read book TIME SERIES FORECASTING USING NEURAL NETWORKS. EXAMPLES WITH MATLAB written by Cesar Perez Lopez and published by CESAR PEREZ. This book was released on with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATLAB has the tool Deep Leraning Toolbox that provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, timeseries forecasting, and dynamic system modeling and control. Dynamic neural networks are good at timeseries prediction. You can use the Neural Net Time Series app to solve different kinds of time series problems It is generally best to start with the GUI, and then to use the GUI to automatically generate command line scripts. Before using either method, the first step is to define the problem by selecting a data set. Each GUI has access to many sample data sets that you can use to experiment with the toolbox. If you have a specific problem that you want to solve, you can load your own data into the workspace. With MATLAB is possibe to solve three different kinds of time series problems. In the first type of time series problem, you would like to predict future values of a time series y(t) from past values of that time series and past values of a second time series x(t). This form of prediction is called nonlinear autoregressive network with exogenous (external) input, or NARX. In the second type of time series problem, there is only one series involved. The future values of a time series y(t) are predicted only from past values of that series. This form of prediction is called nonlinear autoregressive, or NAR. The third time series problem is similar to the first type, in that two series are involved, an input series (predictors) x(t) and an output series (responses) y(t). Here you want to predict values of y(t) from previous values of x(t), but without knowledge of previous values of y(t). This book develops methods for time series forecasting using neural networks across MATLAB

Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction

Author : Jesus Soto
Publisher : Springer
ISBN 13 : 3319712640
Total Pages : 103 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction by : Jesus Soto

Download or read book Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction written by Jesus Soto and published by Springer. This book was released on 2017-11-19 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fields of hybrid intelligent systems based on fuzzy systems, neural networks, bio-inspired algorithms and time series. This book describes the construction of ensembles of Interval Type-2 Fuzzy Neural Networks models and the optimization of their fuzzy integrators with bio-inspired algorithms for time series prediction. Interval type-2 and type-1 fuzzy systems are used to integrate the outputs of the Ensemble of Interval Type-2 Fuzzy Neural Network models. Genetic Algorithms and Particle Swarm Optimization are the Bio-Inspired algorithms used for the optimization of the fuzzy response integrators. The Mackey-Glass, Mexican Stock Exchange, Dow Jones and NASDAQ time series are used to test of performance of the proposed method. Prediction errors are evaluated by the following metrics: Mean Absolute Error, Mean Square Error, Root Mean Square Error, Mean Percentage Error and Mean Absolute Percentage Error. The proposed prediction model outperforms state of the art methods in predicting the particular time series considered in this work.

Assessing and Improving Prediction and Classification

Author : Timothy Masters
Publisher : CreateSpace
ISBN 13 : 9781484137451
Total Pages : 562 pages
Book Rating : 4.1/5 (374 download)

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Book Synopsis Assessing and Improving Prediction and Classification by : Timothy Masters

Download or read book Assessing and Improving Prediction and Classification written by Timothy Masters and published by CreateSpace. This book was released on 2013-04-21 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book begins by presenting methods for performing practical, real-life assessment of the performance of prediction and classification models. It then goes on to discuss techniques for improving the performance of such models by intelligent resampling of training/testing data, combining multiple models into sophisticated committees, and making use of exogenous information to dynamically choose modeling methodologies. Rigorous statistical techniques for computing confidence in predictions and decisions receive extensive treatment. Finally, a hundred pages are devoted to the use of information theory in evaluating and selecting useful predictors. Special attention is paid to Schreiber's Information Transfer, a recent generalization of Grainger Causality. Well commented C++ code is given for every algorithm and technique. The ultimate purpose of this text is three-fold. The first goal is to open the eyes of serious developers to some of the hidden pitfalls that lurk in the model development process. The second is to provide broad exposure for some of the most powerful model enhancement algorithms that have emerged from academia in the last two decades, while not bogging down readers in cryptic mathematical theory. Finally, this text should provide the reader with a toolbox of ready-to-use C++ code that can be easily incorporated into his or her existing programs.

Advances in VLSI, Communication, and Signal Processing

Author : David Harvey
Publisher : Springer Nature
ISBN 13 : 9811568405
Total Pages : 741 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Advances in VLSI, Communication, and Signal Processing by : David Harvey

Download or read book Advances in VLSI, Communication, and Signal Processing written by David Harvey and published by Springer Nature. This book was released on 2020-10-14 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises select peer-reviewed papers from the International Conference on VLSI, Communication and Signal processing (VCAS) 2019, held at Motilal Nehru National Institute of Technology (MNNIT) Allahabad, Prayagraj, India. The contents focus on latest research in different domains of electronics and communication engineering, in particular microelectronics and VLSI design, communication systems and networks, and signal and image processing. The book also discusses the emerging applications of novel tools and techniques in image, video and multimedia signal processing. This book will be useful to students, researchers and professionals working in the electronics and communication domain.

Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms

Author : Dash, Sujata
Publisher : IGI Global
ISBN 13 : 152252858X
Total Pages : 567 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms by : Dash, Sujata

Download or read book Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms written by Dash, Sujata and published by IGI Global. This book was released on 2017-08-10 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.

Intelligent Technologies--theory and Applications

Author : Peter Sincak
Publisher : IOS Press
ISBN 13 : 9781586032562
Total Pages : 362 pages
Book Rating : 4.0/5 (325 download)

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Book Synopsis Intelligent Technologies--theory and Applications by : Peter Sincak

Download or read book Intelligent Technologies--theory and Applications written by Peter Sincak and published by IOS Press. This book was released on 2002 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation Intelligent Technologies including neural network, evolutionary computations, fuzzy approach and mainly hybrid approaches are very promising tools to build intelligent technologies in general. The progress of each theory or application is provided by a number of various theoretical as well as applicational experiments. Machine intelligence is the only alternative how to increase the level of technology to make technology more human-centred and more effective for society. This book includes theoretical as well as applicational papers in the field of neural networks, fuzzy systems and mainly evolutionary computations which application potential was increased by enormous progress in computer power. Hybrid technologies are still progressing and are trying to make some more applications with their ability to learn and process fuzzy information. Neurogenetic systems are very interesting approach to make systems re-configurable and on-line systems for real-world applications. The book is presenting papers from Japan, USA, Hungary, Poland, Germany, Finland, France, Slovakia, United Kingdom, Czech Republic and some other countries. This publication provides the latest state of the art in the field and could be contributed to theory and applications in the machine intelligence tools and their wide application potential in current and future technologies within the Information Society.

Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications

Author : Oscar Castillo
Publisher : Springer Nature
ISBN 13 : 3030687767
Total Pages : 383 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications by : Oscar Castillo

Download or read book Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications written by Oscar Castillo and published by Springer Nature. This book was released on 2021-03-24 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: We describe in this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that presents theory and practice of meta-heuristics in different areas of application. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems.

Recent Advances in Simulated Evolution and Learning

Author : K. C. Tan
Publisher : World Scientific
ISBN 13 : 9812389520
Total Pages : 836 pages
Book Rating : 4.8/5 (123 download)

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Book Synopsis Recent Advances in Simulated Evolution and Learning by : K. C. Tan

Download or read book Recent Advances in Simulated Evolution and Learning written by K. C. Tan and published by World Scientific. This book was released on 2004 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest advances in the theories, algorithms, and applications of simulated evolution and learning techniques. It provides insights into different evolutionary computation techniques and their applications in domains such as scheduling, control and power, robotics, signal processing, and bioinformatics. The book will be of significant value to all postgraduates, research scientists and practitioners dealing with evolutionary computation or complex real-world problems.

Advances in Time Series Forecasting

Author : Cagdas Hakan Aladag
Publisher : Bentham Science Publishers
ISBN 13 : 1681085283
Total Pages : 196 pages
Book Rating : 4.6/5 (81 download)

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Book Synopsis Advances in Time Series Forecasting by : Cagdas Hakan Aladag

Download or read book Advances in Time Series Forecasting written by Cagdas Hakan Aladag and published by Bentham Science Publishers. This book was released on 2017-12-06 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a valuable source of recent knowledge about advanced time series forecasting techniques such as artificial neural networks, fuzzy time series, or hybrid approaches. New forecasting frameworks are discussed and their application is demonstrated. The second volume of the series includes applications of some powerful forecasting approaches with a focus on fuzzy time series methods. Chapters integrate these methods with concepts such as neural networks, high order multivariate systems, deterministic trends, distance measurement and much more. The chapters are contributed by eminent scholars and serve to motivate and accelerate future progress while introducing new branches of time series forecasting. This book is a valuable resource for MSc and PhD students, academic personnel and researchers seeking updated and critically important information on the concepts of advanced time series forecasting and its applications.

Advances in the Theory of Probabilistic and Fuzzy Data Scientific Methods with Applications

Author : József Dombi
Publisher : Springer Nature
ISBN 13 : 303051949X
Total Pages : 201 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Advances in the Theory of Probabilistic and Fuzzy Data Scientific Methods with Applications by : József Dombi

Download or read book Advances in the Theory of Probabilistic and Fuzzy Data Scientific Methods with Applications written by József Dombi and published by Springer Nature. This book was released on 2020-08-11 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the advanced soft computational and probabilistic methods that the authors have published over the past few years. It describes theoretical results and applications, and discusses how various uncertainty measures – probability, plausibility and belief measures – can be treated in a unified way. It also examines approximations of four notable probability distributions (Weibull, exponential, logistic and normal) using a unified probability distribution function, and presents a fuzzy arithmetic-based time series model that provides an easy-to-use forecasting technique. Lastly, it proposes flexible fuzzy numbers for Likert scale-based evaluations. Featuring methods that can be successfully applied in a variety of areas, including engineering, economics, biology and the medical sciences, the book offers useful guidelines for practitioners and researchers.

Intelligent Information and Database Systems

Author : Ngoc Thanh Nguyen
Publisher : Springer
ISBN 13 : 3319157027
Total Pages : 672 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Intelligent Information and Database Systems by : Ngoc Thanh Nguyen

Download or read book Intelligent Information and Database Systems written by Ngoc Thanh Nguyen and published by Springer. This book was released on 2015-03-16 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume proceedings of the ACIIDS 2015 conference, LNAI 9011 + 9012, constitutes the refereed proceedings of the 7th Asian Conference on Intelligent Information and Database Systems, held in Bali, Indonesia, in March 2015. The total of 117 full papers accepted for publication in these proceedings was carefully reviewed and selected from 332 submissions. They are organized in the following topical sections: semantic web, social networks and recommendation systems; text processing and information retrieval; intelligent database systems; intelligent information systems; decision support and control systems; machine learning and data mining; multiple model approach to machine learning; innovations in intelligent systems and applications; bio-inspired optimization techniques and their applications; machine learning in biometrics and bioinformatics with applications; advanced data mining techniques and applications; collective intelligent systems for e-market trading, technology opportunity discovery and collaborative learning; intelligent information systems in security and defense; analysis of image, video and motion data in life sciences; augmented reality and 3D media; cloud based solutions; internet of things, big data and cloud computing; and artificial intelligent techniques and their application in engineering and operational research.

Handbook of Neural Network Signal Processing

Author : Yu Hen Hu
Publisher : CRC Press
ISBN 13 : 1351836307
Total Pages : 417 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Handbook of Neural Network Signal Processing by : Yu Hen Hu

Download or read book Handbook of Neural Network Signal Processing written by Yu Hen Hu and published by CRC Press. This book was released on 2018-10-03 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of neural networks is permeating every area of signal processing. They can provide powerful means for solving many problems, especially in nonlinear, real-time, adaptive, and blind signal processing. The Handbook of Neural Network Signal Processing brings together applications that were previously scattered among various publications to provide an up-to-date, detailed treatment of the subject from an engineering point of view. The authors cover basic principles, modeling, algorithms, architectures, implementation procedures, and well-designed simulation examples of audio, video, speech, communication, geophysical, sonar, radar, medical, and many other signals. The subject of neural networks and their application to signal processing is constantly improving. You need a handy reference that will inform you of current applications in this new area. The Handbook of Neural Network Signal Processing provides this much needed service for all engineers and scientists in the field.

Applied Time Series Analysis and Innovative Computing

Author : Sio-Iong Ao
Publisher : Springer Science & Business Media
ISBN 13 : 9048187680
Total Pages : 123 pages
Book Rating : 4.0/5 (481 download)

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Book Synopsis Applied Time Series Analysis and Innovative Computing by : Sio-Iong Ao

Download or read book Applied Time Series Analysis and Innovative Computing written by Sio-Iong Ao and published by Springer Science & Business Media. This book was released on 2010-04-21 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Time Series Analysis and Innovative Computing contains the applied time series analysis and innovative computing paradigms, with frontier application studies for the time series problems based on the recent works at the Oxford University Computing Laboratory, University of Oxford, the University of Hong Kong, and the Chinese University of Hong Kong. The monograph was drafted when the author was a post-doctoral fellow in Harvard School of Engineering and Applied Sciences, Harvard University. It provides a systematic introduction to the use of innovative computing paradigms as an investigative tool for applications in time series analysis. Applied Time Series Analysis and Innovative Computing offers the state of art of tremendous advances in applied time series analysis and innovative computing paradigms and also serves as an excellent reference work for researchers and graduate students working on applied time series analysis and innovative computing paradigms.