Time Series Prediction And Applications PDF Download
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| Author | : Amit Konar |
| Publisher | : Springer |
| Total Pages | : 242 |
| Release | : 2017-03-25 |
| Genre | : Technology & Engineering |
| ISBN | : 3319545973 |
Download Time-Series Prediction and Applications Book in PDF, ePub and Kindle
This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at the end of each chapter to the readers’ ability and understanding of the topics covered.
| Author | : Witold Pedrycz |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 398 |
| Release | : 2012-11-29 |
| Genre | : Technology & Engineering |
| ISBN | : 3642334393 |
Download Time Series Analysis, Modeling and Applications Book in PDF, ePub and Kindle
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.
| Author | : Ajoy K. Palit |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 382 |
| Release | : 2006-01-04 |
| Genre | : Computers |
| ISBN | : 1846281849 |
Download Computational Intelligence in Time Series Forecasting Book in PDF, ePub and Kindle
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.
| Author | : Rob J Hyndman |
| Publisher | : OTexts |
| Total Pages | : 380 |
| Release | : 2018-05-08 |
| Genre | : Business & Economics |
| ISBN | : 0987507117 |
Download Forecasting: principles and practice Book in PDF, ePub and Kindle
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
| Author | : G. J. Janacek |
| Publisher | : Ellis Horwood |
| Total Pages | : 344 |
| Release | : 1993 |
| Genre | : Business & Economics |
| ISBN | : |
Download Time Series Book in PDF, ePub and Kindle
This introduction to time series analysis has been written for undergraduates and postgraduates, and assumes some basic statistical knowledge. Using a general state space model, the authors draw together methodologies to enable the development of methods for estimation and forecasting.
| Author | : Anthony Mihirana De Silva |
| Publisher | : Springer |
| Total Pages | : 105 |
| Release | : 2015-02-14 |
| Genre | : Technology & Engineering |
| ISBN | : 9812874119 |
Download Grammar-Based Feature Generation for Time-Series Prediction Book in PDF, ePub and Kindle
This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method can be applied to a wide range of machine learning architectures and applications to represent complex feature dependencies explicitly when machine learning cannot achieve this by itself. Industrial applications can use the proposed technique to improve their predictions.
| Author | : Andreas S. Weigend |
| Publisher | : Routledge |
| Total Pages | : 665 |
| Release | : 2018-05-04 |
| Genre | : Social Science |
| ISBN | : 042997227X |
Download Time Series Prediction Book in PDF, ePub and Kindle
The book is a summary of a time series forecasting competition that was held a number of years ago. It aims to provide a snapshot of the range of new techniques that are used to study time series, both as a reference for experts and as a guide for novices.
| Author | : Olga Valenzuela |
| Publisher | : Springer Nature |
| Total Pages | : 460 |
| Release | : 2020-11-20 |
| Genre | : Business & Economics |
| ISBN | : 3030562190 |
Download Theory and Applications of Time Series Analysis Book in PDF, ePub and Kindle
This book presents a selection of peer-reviewed contributions on the latest advances in time series analysis, presented at the International Conference on Time Series and Forecasting (ITISE 2019), held in Granada, Spain, on September 25-27, 2019. The first two parts of the book present theoretical contributions on statistical and advanced mathematical methods, and on econometric models, financial forecasting and risk analysis. The remaining four parts include practical contributions on time series analysis in energy; complex/big data time series and forecasting; time series analysis with computational intelligence; and time series analysis and prediction for other real-world problems. Given this mix of topics, readers will acquire a more comprehensive perspective on the field of time series analysis and forecasting. The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics, statistics and econometrics.
| Author | : Aileen Nielsen |
| Publisher | : O'Reilly Media |
| Total Pages | : 500 |
| Release | : 2019-09-20 |
| Genre | : Computers |
| ISBN | : 1492041629 |
Download Practical Time Series Analysis Book in PDF, ePub and Kindle
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance
| Author | : William W. S. Wei |
| Publisher | : John Wiley & Sons |
| Total Pages | : 536 |
| Release | : 2019-03-18 |
| Genre | : Mathematics |
| ISBN | : 1119502853 |
Download Multivariate Time Series Analysis and Applications Book in PDF, ePub and Kindle
An essential guide on high dimensional multivariate time series including all the latest topics from one of the leading experts in the field Following the highly successful and much lauded book, Time Series Analysis—Univariate and Multivariate Methods, this new work by William W.S. Wei focuses on high dimensional multivariate time series, and is illustrated with numerous high dimensional empirical time series. Beginning with the fundamentalconcepts and issues of multivariate time series analysis,this book covers many topics that are not found in general multivariate time series books. Some of these are repeated measurements, space-time series modelling, and dimension reduction. The book also looks at vector time series models, multivariate time series regression models, and principle component analysis of multivariate time series. Additionally, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral analysis of time series. With the development of computers and the internet, we have increased potential for data exploration. In the next few years, dimension will become a more serious problem. Multivariate Time Series Analysis and its Applications provides some initial solutions, which may encourage the development of related software needed for the high dimensional multivariate time series analysis. Written by bestselling author and leading expert in the field Covers topics not yet explored in current multivariate books Features classroom tested material Written specifically for time series courses Multivariate Time Series Analysis and its Applications is designed for an advanced time series analysis course. It is a must-have for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.
