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Computational Intelligence-based Time Series Analysis

2022-11-30 Science
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Release : 2022-11-30
Genre : Science
Kind : eBook
Book Rating : 818/5 ( reviews)

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Book Synopsis Computational Intelligence-based Time Series Analysis by : Dinesh C. S. Bisht

Download or read book Computational Intelligence-based Time Series Analysis written by Dinesh C. S. Bisht. This book was released on 2022-11-30. Available in PDF, EPUB and Kindle. Book excerpt: The sequential analysis of data and information gathered from past to present is called time series analysis. Time series data are of high dimension, large size and updated continuously. A time series depends on various factors like trend, seasonality, cycle and irregular data set, and is basically a series of data points well-organized in time. Time series forecasting is a significant area of machine learning. There are various prediction problems that are time-dependent and these problems can be handled through time series analysis. Computational intelligence (CI) is a developing computing approach for the forthcoming several years. CI gives the litheness to model the problem according to given requirements. It helps to find swift solutions to the problems arising in numerous disciplines. These methods mimic human behavior. The main objective of CI is to develop intelligent machines to provide solutions to real world problems, which are not modelled or are too difficult to model mathematically. This book aims to cover the recent advances in time series and applications of CI for time series analysis.

Computational Intelligence in Time Series Forecasting

2006-01-04 Computers
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Release : 2006-01-04
Genre : Computers
Kind : eBook
Book Rating : 849/5 ( reviews)

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Book Synopsis Computational Intelligence in Time Series Forecasting by : Ajoy K. Palit

Download or read book Computational Intelligence in Time Series Forecasting written by Ajoy K. Palit. This book was released on 2006-01-04. Available in PDF, EPUB and Kindle. Book excerpt: Foresight in an engineering business can make the difference between success and failure, and can be vital to the effective control of industrial systems. The authors of this book harness the power of intelligent technologies individually and in combination.

Time Series Analysis, Modeling and Applications

2012-11-29 Technology & Engineering
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Release : 2012-11-29
Genre : Technology & Engineering
Kind : eBook
Book Rating : 393/5 ( reviews)

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Book Synopsis Time Series Analysis, Modeling and Applications by : Witold Pedrycz

Download or read book Time Series Analysis, Modeling and Applications written by Witold Pedrycz. This book was released on 2012-11-29. Available in PDF, EPUB and Kindle. Book excerpt: Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable). The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological and algorithmic approaches and case studies. This volume is aimed at a broad audience of researchers and practitioners engaged in various branches of operations research, management, social sciences, engineering, and economics. Owing to the nature of the material being covered and a way it has been arranged, it establishes a comprehensive and timely picture of the ongoing pursuits in the area and fosters further developments.

Pattern Recognition and Classification in Time Series Data

2016-07-22 Computers
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Release : 2016-07-22
Genre : Computers
Kind : eBook
Book Rating : 660/5 ( reviews)

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Book Synopsis Pattern Recognition and Classification in Time Series Data by : Volna, Eva

Download or read book Pattern Recognition and Classification in Time Series Data written by Volna, Eva. This book was released on 2016-07-22. Available in PDF, EPUB and Kindle. Book excerpt: Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.

Using Artificial Neural Networks for Timeseries Smoothing and Forecasting

2021-09-04 Technology & Engineering
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Release : 2021-09-04
Genre : Technology & Engineering
Kind : eBook
Book Rating : 491/5 ( reviews)

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Book Synopsis Using Artificial Neural Networks for Timeseries Smoothing and Forecasting by : Jaromír Vrbka

Download or read book Using Artificial Neural Networks for Timeseries Smoothing and Forecasting written by Jaromír Vrbka. This book was released on 2021-09-04. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this publication is to identify and apply suitable methods for analysing and predicting the time series of gold prices, together with acquainting the reader with the history and characteristics of the methods and with the time series issues in general. Both statistical and econometric methods, and especially artificial intelligence methods, are used in the case studies. The publication presents both traditional and innovative methods on the theoretical level, always accompanied by a case study, i.e. their specific use in practice. Furthermore, a comprehensive comparative analysis of the individual methods is provided. The book is intended for readers from the ranks of academic staff, students of universities of economics, but also the scientists and practitioners dealing with the time series prediction. From the point of view of practical application, it could provide useful information for speculators and traders on financial markets, especially the commodity markets.

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