Applied Time Series Analysis and Innovative Computing PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Applied Time Series Analysis and Innovative Computing PDF full book. Access full book title Applied Time Series Analysis and Innovative Computing by Sio-Iong Ao. Download full books in PDF and EPUB format.
Author: Sio-Iong Ao Publisher: Springer Science & Business Media ISBN: 9048187680 Category : Mathematics Languages : en Pages : 123
Book Description
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.
Author: Sio-Iong Ao Publisher: Springer Science & Business Media ISBN: 9048187680 Category : Mathematics Languages : en Pages : 123
Book Description
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.
Author: Publisher: Springer ISBN: 9789048187782 Category : Mathematics Languages : en Pages : 112
Book Description
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.
Author: Aileen Nielsen Publisher: O'Reilly Media ISBN: 1492041629 Category : Computers Languages : en Pages : 500
Book Description
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: Raquel Prado Publisher: CRC Press ISBN: 1420093363 Category : Mathematics Languages : en Pages : 375
Book Description
Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLAB® code, and other material are available on the authors’ websites. Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas.
Author: Xin-She Yang Publisher: Springer Nature ISBN: 9811916101 Category : Technology & Engineering Languages : en Pages : 889
Book Description
This book gathers selected high-quality research papers presented at the Seventh International Congress on Information and Communication Technology, held at Brunel University, London, on February 21–24, 2022. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The work is presented in four volumes.
Author: Ivo Häring Publisher: Springer ISBN: 9811000158 Category : Technology & Engineering Languages : en Pages : 397
Book Description
The book introduces basic risk concepts and then goes on to discuss risk management and analysis processes and steps. The main emphasis is on methods that fulfill the requirements of one or several risk management steps. The focus is on risk analysis methods including statistical-empirical analyses, probabilistic and parametrized models, engineering approaches and simulative methods, e.g. for fragment and blast propagation or hazard density computation. Risk management is essential for improving all resilience management steps: preparation, prevention, protection, response and recovery. The methods investigate types of event and scenario, as well as frequency, exposure, avoidance, hazard propagation, damage and risks of events. Further methods are presented for context assessment, risk visualization, communication, comparison and assessment as well as selecting mitigation measures. The processes and methods are demonstrated using detailed results and overviews of security research projects, in particular in the applications domains transport, aviation, airport security, explosive threats and urban security and safety. Topics include: sufficient control of emerging and novel hazards and risks, occupational safety, identification of minimum (functional) safety requirements, engineering methods for countering malevolent or terrorist events, security research challenges, interdisciplinary approaches to risk control and management, risk-based change and improvement management, and support of rational decision-making. The book addresses advanced bachelor students, master and doctoral students as well as scientists, researchers and developers in academia, industry, small and medium enterprises working in the emerging field of security and safety engineering.
Author: Ajith Abraham Publisher: Springer Nature ISBN: 3031274997 Category : Technology & Engineering Languages : en Pages : 951
Book Description
This book highlights recent research on bio-inspired computing and its various innovative applications in information and communication technologies. It presents 85 high-quality papers from the 13th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2022) and 12th World Congress on Information and Communication Technologies (WICT 2022), which was held online during 15–17 December 2022. As a premier conference, IBICA–WICT brings together researchers, engineers and practitioners whose work involves bio-inspired computing, computational intelligence and their applications in information security, real-world contexts, etc. Including contributions by authors from 25 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
Author: Wilfredo Palma Publisher: John Wiley & Sons ISBN: 1118634233 Category : Mathematics Languages : en Pages : 620
Book Description
A modern and accessible guide to the analysis of introductory time series data Featuring an organized and self-contained guide, Time Series Analysis provides a broad introduction to the most fundamental methodologies and techniques of time series analysis. The book focuses on the treatment of univariate time series by illustrating a number of well-known models such as ARMA and ARIMA. Providing contemporary coverage, the book features several useful and newlydeveloped techniques such as weak and strong dependence, Bayesian methods, non-Gaussian data, local stationarity, missing values and outliers, and threshold models. Time Series Analysis includes practical applications of time series methods throughout, as well as: Real-world examples and exercise sets that allow readers to practice the presented methods and techniques Numerous detailed analyses of computational aspects related to the implementation of methodologies including algorithm efficiency, arithmetic complexity, and process time End-of-chapter proposed problems and bibliographical notes to deepen readers’ knowledge of the presented material Appendices that contain details on fundamental concepts and select solutions of the problems implemented throughout A companion website with additional data fi les and computer codes Time Series Analysis is an excellent textbook for undergraduate and beginning graduate-level courses in time series as well as a supplement for students in advanced statistics, mathematics, economics, finance, engineering, and physics. The book is also a useful reference for researchers and practitioners in time series analysis, econometrics, and finance. Wilfredo Palma, PhD, is Professor of Statistics in the Department of Statistics at Pontificia Universidad Católica de Chile. He has published several refereed articles and has received over a dozen academic honors and awards. His research interests include time series analysis, prediction theory, state space systems, linear models, and econometrics. He is the author of Long-Memory Time Series: Theory and Methods, also published by Wiley.
Author: Robert K. Otnes Publisher: John Wiley & Sons ISBN: Category : Business & Economics Languages : en Pages : 470
Book Description
Preliminary concepts; Probability and statistical concepts; Collecting and preprocessing data; Design of digital filters; Practical aspects of digital filtering; Fourier transforms; Covariance and convolution functions; Power and cross spectral densities; Transfer functions and coherence function; Computer subroutines for time series analysis.
Author: Sio-Iong Ao
Author: Sio-Iong Ao
Author: 
Author: Aileen Nielsen
Author: Raquel Prado
Author: Xin-She Yang
Author: Ivo Häring
Author: Ajith Abraham
Author: Wilfredo Palma
Author: Miroslav Verbič
Author: Robert K. Otnes