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Advanced Analytics And Learning On Temporal Data

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Advanced Analytics And Learning On Temporal Data

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Author : Georgiana Ifrim
language : en
Publisher: Springer Nature
Release Date : 2023-12-19

Advanced Analytics And Learning On Temporal Data written by Georgiana Ifrim and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-19 with Computers categories.

This volume LNCS 14343 constitutes the refereed proceedings of the 8th ECML PKDD Workshop, AALTD 2023, in Turin, Italy, in September 2023. The 20 full papers were carefully reviewed and selected from 28 submissions. They are organized in the following topical section as follows: Machine Learning; Data Mining; Pattern Analysis; Statistics to Share their Challenges and Advances in Temporal Data Analysis.

Advanced Analytics And Learning On Temporal Data

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Author : Vincent Lemaire
language : en
Publisher: Springer Nature
Release Date : 2024-12-31

Advanced Analytics And Learning On Temporal Data written by Vincent Lemaire and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-31 with Computers categories.

This book constitutes the refereed proceedings of the 9th ECML PKDD workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2024, held in Vilnius, Lithuania, during September 9-13, 2024. The 8 full papers presented here were carefully reviewed and selected from 15 submissions. The papers focus on recent advances in Temporal Data Analysis, Metric Learning, Representation Learning, Unsupervised Feature Extraction, Clustering, and Classification.

Advanced Analytics And Learning On Temporal Data

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Author : Vincent Lemaire
language : en
Publisher: Springer Nature
Release Date : 2021-12-02

This book constitutes the refereed proceedings of the 6th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2021, held during September 13-17, 2021. The workshop was planned to take place in Bilbao, Spain, but was held virtually due to the COVID-19 pandemic. The 12 full papers presented in this book were carefully reviewed and selected from 21 submissions. They focus on the following topics: Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Multivariate Time Series Co-clustering; Efficient Event Detection; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Cluster-based Forecasting; Explanation Methods for Time Series Classification; Multimodal Meta-Learning for Time Series Regression; and Multivariate Time Series Anomaly Detection.

Advanced Analytics And Learning On Temporal Data

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Author : Thomas Guyet
language : en
Publisher: Springer Nature
Release Date : 2023-03-20

Advanced Analytics And Learning On Temporal Data written by Thomas Guyet and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-20 with Computers categories.

This book constitutes the refereed proceedings of the 7th ECML PKDD Workshop, AALTD 2022, held in Grenoble, France, during September 19–23, 2022. The 12 full papers included in this book were carefully reviewed and selected from 21 submissions. They were organized in topical sections as follows: Oral presentation and poster presentation.

Advanced Analytics And Learning On Temporal Data

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Author : Vincent Lemaire
language : en
Publisher: Springer Nature
Release Date : 2020-01-22

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Würzburg, Germany, in September 2019. The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover topics such as temporal data clustering; classification of univariate and multivariate time series; early classification of temporal data; deep learning and learning representations for temporal data; modeling temporal dependencies; advanced forecasting and prediction models; space-temporal statistical analysis; functional data analysis methods; temporal data streams; interpretable time-series analysis methods; dimensionality reduction, sparsity, algorithmic complexity and big data challenge; and bio-informatics, medical, energy consumption, on temporal data.

Advanced Analytics And Learning On Temporal Data

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Author : Vincent Lemaire
language : en
Publisher: Springer Nature
Release Date : 2020-12-15

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Ghent, Belgium, in September 2020. The 15 full papers presented in this book were carefully reviewed and selected from 29 submissions. The selected papers are devoted to topics such as Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Early Classification of Temporal Data; Deep Learning and Learning Representations for Temporal Data; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Space-Temporal Statistical Analysis; Functional Data Analysis Methods; Temporal Data Streams; Interpretable Time-Series Analysis Methods; Dimensionality Reduction, Sparsity, Algorithmic Complexity and Big Data Challenge; and Bio-Informatics, Medical, Energy Consumption, Temporal Data.

Advanced Analysis And Learning On Temporal Data

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Author : Ahlame Douzal-Chouakria
language : en
Publisher: Springer
Release Date : 2016-08-03

Advanced Analysis And Learning On Temporal Data written by Ahlame Douzal-Chouakria and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-03 with Computers categories.

This book constitutes the refereed proceedings of the First ECML PKDD Workshop, AALTD 2015, held in Porto, Portugal, in September 2016. The 11 full papers presented were carefully reviewed and selected from 22 submissions. The first part focuses on learning new representations and embeddings for time series classification, clustering or for dimensionality reduction. The second part presents approaches on classification and clustering with challenging applications on medicine or earth observation data. These works show different ways to consider temporal dependency in clustering or classification processes. The last part of the book is dedicated to metric learning and time series comparison, it addresses the problem of speeding-up the dynamic time warping or dealing with multi-modal and multi-scale metric learning for time series classification and clustering.

Big Data Application In Power Systems

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Author : Reza Arghandeh
language : en
Publisher: Elsevier
Release Date : 2017-11-27

Big Data Application In Power Systems written by Reza Arghandeh and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-27 with Science categories.

Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement data in electricity transmission and distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data. The book chapters discuss challenges, opportunities, success stories and pathways for utilizing big data value in smart grids. - Provides expert analysis of the latest developments by global authorities - Contains detailed references for further reading and extended research - Provides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformatics - Focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data

Applied Time Series Analysis And Forecasting With Python

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Author : Changquan Huang
language : en
Publisher: Springer Nature
Release Date : 2022-10-19

Applied Time Series Analysis And Forecasting With Python written by Changquan Huang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-19 with Mathematics categories.

This textbook presents methods and techniques for time series analysis and forecasting and shows how to use Python to implement them and solve data science problems. It covers not only common statistical approaches and time series models, including ARMA, SARIMA, VAR, GARCH and state space and Markov switching models for (non)stationary, multivariate and financial time series, but also modern machine learning procedures and challenges for time series forecasting. Providing an organic combination of the principles of time series analysis and Python programming, it enables the reader to study methods and techniques and practice writing and running Python code at the same time. Its data-driven approach to analyzing and modeling time series data helps new learners to visualize and interpret both the raw data and its computed results. Primarily intended for students of statistics, economics and data science with an undergraduate knowledge of probability and statistics, the book will equally appeal to industry professionals in the fields of artificial intelligence and data science, and anyone interested in using Python to solve time series problems.

Multitemporal Earth Observation Image Analysis

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Author : Clément Mallet
language : en
Publisher: John Wiley & Sons
Release Date : 2024-08-20

Multitemporal Earth Observation Image Analysis written by Clément Mallet and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-20 with Technology & Engineering categories.

Earth observation has witnessed a unique paradigm change in the last decade with a diverse and ever-growing number of data sources. Among them, time series of remote sensing images has proven to be invaluable for numerous environmental and climate studies. Multitemporal Earth Observation Image Analysis provides illustrations of recent methodological advances in data processing and information extraction from imagery, with an emphasis on the temporal dimension uncovered either by recent satellite constellations (in particular the Sentinels from the European Copernicus programme) or archival aerial images available in national archives. The book shows how complementary data sources can be efficiently used, how spatial and temporal information can be leveraged for biophysical parameter estimation, classification of land surfaces and object tracking, as well as how standard machine learning and state-of-the-art deep learning solutions can solve complex problems with real-world applications.

Advanced Analytics And Learning On Temporal Data

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