Modeling And Stochastic Learning For Forecasting In High Dimensions

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Modeling and Stochastic Learning for Forecasting in High Dimensions

Author : Anestis Antoniadis
Publisher :
ISBN 13 : 9783319187334
Total Pages : 339 pages
Book Rating : 4.1/5 (873 download)

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Book Synopsis Modeling and Stochastic Learning for Forecasting in High Dimensions by : Anestis Antoniadis

Download or read book Modeling and Stochastic Learning for Forecasting in High Dimensions written by Anestis Antoniadis and published by . This book was released on 2015 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: The chapters in this volume stress the need for advances in theoretical understanding to go hand-in-hand with the widespread practical application of forecasting in industry. Forecasting and time series prediction have enjoyed considerable attention over the last few decades, fostered by impressive advances in observational capabilities and measurement procedures. On June 5-7, 2013, an international Workshop on Industry Practices for FORecasting was held in Paris, France, organized and supported by the OSIRIS Department of Electricité de France Research and Development Division. In keeping with tradition, both theoretical statistical results and practical contributions on this active field of statistical research and on forecasting issues in a rapidly evolving industrial environment are presented. The volume reflects the broad spectrum of the conference, including 16 articles contributed by specialists in various areas. The material compiled is broad in scope and ranges from new findings on forecasting in industry and in time series, on nonparametric and functional methods, and on on-line machine learning for forecasting, to the latest developments in tools for high dimension and complex data analysis.

Modeling and Stochastic Learning for Forecasting in High Dimensions

Author : Anestis Antoniadis
Publisher : Springer
ISBN 13 : 3319187325
Total Pages : 344 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Modeling and Stochastic Learning for Forecasting in High Dimensions by : Anestis Antoniadis

Download or read book Modeling and Stochastic Learning for Forecasting in High Dimensions written by Anestis Antoniadis and published by Springer. This book was released on 2015-06-04 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: The chapters in this volume stress the need for advances in theoretical understanding to go hand-in-hand with the widespread practical application of forecasting in industry. Forecasting and time series prediction have enjoyed considerable attention over the last few decades, fostered by impressive advances in observational capabilities and measurement procedures. On June 5-7, 2013, an international Workshop on Industry Practices for Forecasting was held in Paris, France, organized and supported by the OSIRIS Department of Electricité de France Research and Development Division. In keeping with tradition, both theoretical statistical results and practical contributions on this active field of statistical research and on forecasting issues in a rapidly evolving industrial environment are presented. The volume reflects the broad spectrum of the conference, including 16 articles contributed by specialists in various areas. The material compiled is broad in scope and ranges from new findings on forecasting in industry and in time series, on nonparametric and functional methods and on on-line machine learning for forecasting, to the latest developments in tools for high dimension and complex data analysis.

An Introduction to Stochastic Modeling

Author : Howard M. Taylor
Publisher : Academic Press
ISBN 13 : 1483269272
Total Pages : 410 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis An Introduction to Stochastic Modeling by : Howard M. Taylor

Download or read book An Introduction to Stochastic Modeling written by Howard M. Taylor and published by Academic Press. This book was released on 2014-05-10 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.

Statistical Learning Tools for Electricity Load Forecasting

Author : Anestis Antoniadis
Publisher : Springer Nature
ISBN 13 : 3031603397
Total Pages : 232 pages
Book Rating : 4.0/5 (316 download)

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Book Synopsis Statistical Learning Tools for Electricity Load Forecasting by : Anestis Antoniadis

Download or read book Statistical Learning Tools for Electricity Load Forecasting written by Anestis Antoniadis and published by Springer Nature. This book was released on with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting

Author : Anuradha Tomar
Publisher : Springer Nature
ISBN 13 : 9811964904
Total Pages : 208 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting by : Anuradha Tomar

Download or read book Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting written by Anuradha Tomar and published by Springer Nature. This book was released on 2023-01-20 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to forecasting methods for renewable energy sources integrated with existing grid. It consists of two sections; the first one is on the generation side forecasting methods, while the second section deals with the different ways of load forecasting. It broadly includes artificial intelligence, machine learning, hybrid techniques and other state-of-the-art techniques for renewable energy and load predictions. The book reflects the state of the art in distributed generation system and future microgrids and covers theory, algorithms, simulations and case studies. It offers invaluable insights through this valuable resource to students and researchers working in the fields of renewable energy, integration of renewable energy with existing grid and electrical distribution network.

Stochastic Methods for Modeling and Predicting Complex Dynamical Systems

Author : Nan Chen
Publisher : Springer Nature
ISBN 13 : 3031222490
Total Pages : 208 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Stochastic Methods for Modeling and Predicting Complex Dynamical Systems by : Nan Chen

Download or read book Stochastic Methods for Modeling and Predicting Complex Dynamical Systems written by Nan Chen and published by Springer Nature. This book was released on 2023-03-13 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book enables readers to understand, model, and predict complex dynamical systems using new methods with stochastic tools. The author presents a unique combination of qualitative and quantitative modeling skills, novel efficient computational methods, rigorous mathematical theory, as well as physical intuitions and thinking. An emphasis is placed on the balance between computational efficiency and modeling accuracy, providing readers with ideas to build useful models in practice. Successful modeling of complex systems requires a comprehensive use of qualitative and quantitative modeling approaches, novel efficient computational methods, physical intuitions and thinking, as well as rigorous mathematical theories. As such, mathematical tools for understanding, modeling, and predicting complex dynamical systems using various suitable stochastic tools are presented. Both theoretical and numerical approaches are included, allowing readers to choose suitable methods in different practical situations. The author provides practical examples and motivations when introducing various mathematical and stochastic tools and merges mathematics, statistics, information theory, computational science, and data science. In addition, the author discusses how to choose and apply suitable mathematical tools to several disciplines including pure and applied mathematics, physics, engineering, neural science, material science, climate and atmosphere, ocean science, and many others. Readers will not only learn detailed techniques for stochastic modeling and prediction, but will develop their intuition as well. Important topics in modeling and prediction including extreme events, high-dimensional systems, and multiscale features are discussed.

Novel Mathematics Inspired by Industrial Challenges

Author : Michael Günther
Publisher : Springer Nature
ISBN 13 : 3030961737
Total Pages : 348 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Novel Mathematics Inspired by Industrial Challenges by : Michael Günther

Download or read book Novel Mathematics Inspired by Industrial Challenges written by Michael Günther and published by Springer Nature. This book was released on 2022-03-30 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume convenes a rich selection of works with a focus on innovative mathematical methods with applications in real-world, industrial problems. Studies included in this book are all motivated by a relevant industrial challenge, and demonstrate that mathematics for industry can be extremely rewarding, leading to new mathematical methods and sometimes even to entirely new fields within mathematics. The book is organized into two parts: Computational Sciences and Engineering, and Data Analysis and Finance. In every chapter, readers will find a brief description of why such work fits into this volume; an explanation on which industrial challenges have been instrumental for their inspiration; and which methods have been developed as a result. All these contribute to a greater unity of the text, benefiting not only practitioners and professionals seeking information on novel techniques but also graduate students in applied mathematics, engineering, and related fields.

Machine Learning and Knowledge Discovery in Databases

Author : Michele Berlingerio
Publisher : Springer
ISBN 13 : 3030109259
Total Pages : 740 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Michele Berlingerio

Download or read book Machine Learning and Knowledge Discovery in Databases written by Michele Berlingerio and published by Springer. This book was released on 2019-01-17 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.

Interpretability for Industry 4.0 : Statistical and Machine Learning Approaches

Author : Antonio Lepore
Publisher : Springer Nature
ISBN 13 : 3031124022
Total Pages : 130 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Interpretability for Industry 4.0 : Statistical and Machine Learning Approaches by : Antonio Lepore

Download or read book Interpretability for Industry 4.0 : Statistical and Machine Learning Approaches written by Antonio Lepore and published by Springer Nature. This book was released on 2022-10-19 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides readers with a compact, stimulating and multifaceted introduction to interpretability, a key issue for developing insightful statistical and machine learning approaches as well as for communicating modelling results in business and industry. Different views in the context of Industry 4.0 are offered in connection with the concepts of explainability of machine learning tools, generalizability of model outputs and sensitivity analysis. Moreover, the book explores the integration of Artificial Intelligence and robust analysis of variance for big data mining and monitoring in Additive Manufacturing, and sheds new light on interpretability via random forests and flexible generalized additive models together with related software resources and real-world examples.

Renewable Energy: Forecasting and Risk Management

Author : Philippe Drobinski
Publisher : Springer
ISBN 13 : 3319990527
Total Pages : 246 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Renewable Energy: Forecasting and Risk Management by : Philippe Drobinski

Download or read book Renewable Energy: Forecasting and Risk Management written by Philippe Drobinski and published by Springer. This book was released on 2018-12-27 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gathering selected, revised and extended contributions from the conference ‘Forecasting and Risk Management for Renewable Energy FOREWER’, which took place in Paris in June 2017, this book focuses on the applications of statistics to the risk management and forecasting problems arising in the renewable energy industry. The different contributions explore all aspects of the energy production chain: forecasting and probabilistic modelling of renewable resources, including probabilistic forecasting approaches; modelling and forecasting of wind and solar power production; prediction of electricity demand; optimal operation of microgrids involving renewable production; and finally the effect of renewable production on electricity market prices. Written by experts in statistics, probability, risk management, economics and electrical engineering, this multidisciplinary volume will serve as a reference on renewable energy risk management and at the same time as a source of inspiration for statisticians and probabilists aiming to work on energy-related problems.

Advances in Intelligent Data Analysis XVIII

Author : Michael R. Berthold
Publisher : Springer Nature
ISBN 13 : 3030445844
Total Pages : 601 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Advances in Intelligent Data Analysis XVIII by : Michael R. Berthold

Download or read book Advances in Intelligent Data Analysis XVIII written by Michael R. Berthold and published by Springer Nature. This book was released on 2020-04-22 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.

Solar Irradiance and Photovoltaic Power Forecasting

Author : Dazhi Yang
Publisher : CRC Press
ISBN 13 : 1003830854
Total Pages : 682 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Solar Irradiance and Photovoltaic Power Forecasting by : Dazhi Yang

Download or read book Solar Irradiance and Photovoltaic Power Forecasting written by Dazhi Yang and published by CRC Press. This book was released on 2024-02-05 with total page 682 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting plays an indispensable role in grid integration of solar energy, which is an important pathway toward the grand goal of achieving planetary carbon neutrality. This rather specialized field of solar forecasting constitutes both irradiance and photovoltaic power forecasting. Its dependence on atmospheric sciences and implications for power system operations and planning make the multi-disciplinary nature of solar forecasting immediately obvious. Advances in solar forecasting represent a quiet revolution, as the landscape of solar forecasting research and practice has dramatically advanced as compared to just a decade ago. Solar Irradiance and Photovoltaic Power Forecasting provides the reader with a holistic view of all major aspects of solar forecasting: the philosophy, statistical preliminaries, data and software, base forecasting methods, post-processing techniques, forecast verification tools, irradiance-to-power conversion sequences, and the hierarchical and firm forecasting framework. The book’s scope and subject matter are designed to help anyone entering the field or wishing to stay current in understanding solar forecasting theory and applications. The text provides concrete and honest advice, methodological details and algorithms, and broader perspectives for solar forecasting. Both authors are internationally recognized experts in the field, with notable accomplishments in both academia and industry. Each author has many years of experience serving as editors of top journals in solar energy meteorology. The authors, as forecasters, are concerned not merely with delivering the technical specifics through this book, but more so with the hopes of steering future solar forecasting research in a direction that can truly expand the boundary of forecasting science.

Entropy Application for Forecasting

Author : Ana Jesus Lopez-Menendez
Publisher : MDPI
ISBN 13 : 3039364871
Total Pages : 200 pages
Book Rating : 4.0/5 (393 download)

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Book Synopsis Entropy Application for Forecasting by : Ana Jesus Lopez-Menendez

Download or read book Entropy Application for Forecasting written by Ana Jesus Lopez-Menendez and published by MDPI. This book was released on 2020-12-29 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows the potential of entropy and information theory in forecasting, including both theoretical developments and empirical applications. The contents cover a great diversity of topics, such as the aggregation and combination of individual forecasts, the comparison of forecasting performance, and the debate concerning the tradeoff between complexity and accuracy. Analyses of forecasting uncertainty, robustness, and inconsistency are also included, as are proposals for new forecasting approaches. The proposed methods encompass a variety of time series techniques (e.g., ARIMA, VAR, state space models) as well as econometric methods and machine learning algorithms. The empirical contents include both simulated experiments and real-world applications focusing on GDP, M4-Competition series, confidence and industrial trend surveys, and stock exchange composite indices, among others. In summary, this collection provides an engaging insight into entropy applications for forecasting, offering an interesting overview of the current situation and suggesting possibilities for further research in this field.

Applications of Artificial Intelligence in Planning and Operation of Smart Grids

Author : Mehdi Rahmani-Andebili
Publisher : Springer Nature
ISBN 13 : 3030945227
Total Pages : 140 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Applications of Artificial Intelligence in Planning and Operation of Smart Grids by : Mehdi Rahmani-Andebili

Download or read book Applications of Artificial Intelligence in Planning and Operation of Smart Grids written by Mehdi Rahmani-Andebili and published by Springer Nature. This book was released on 2022-03-26 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is going to play a significant role in smart grid planning and operation, especially in solving its real-time problems, as it is fast, adaptive, robust, and less dependent on the system’s accurate model and parameters. This collection covers research advancements in the application of AI in the planning and operation of smart grids. A global group of researchers and scholars present innovative approaches to AI-based smart grid planning and operation, cover the theoretical concepts and experimental results of the application of AI-based techniques, and apply these techniques to deal with smart grid issues. Applications of Artificial Intelligence in Planning and Operation of Smart Grids is an ideal resource for researchers on the theory and application of AI, practicing engineers working in electrical power engineering, and students in advanced graduate-level courses.

Machine Learning and Knowledge Discovery in Databases

Author : Ulf Brefeld
Publisher : Springer Nature
ISBN 13 : 3030461505
Total Pages : 799 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Ulf Brefeld

Download or read book Machine Learning and Knowledge Discovery in Databases written by Ulf Brefeld and published by Springer Nature. This book was released on 2020-05-01 with total page 799 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume proceedings LNAI 11906 – 11908 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, held in Würzburg, Germany, in September 2019. The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track. The contributions were organized in topical sections named as follows: Part I: pattern mining; clustering, anomaly and outlier detection, and autoencoders; dimensionality reduction and feature selection; social networks and graphs; decision trees, interpretability, and causality; strings and streams; privacy and security; optimization. Part II: supervised learning; multi-label learning; large-scale learning; deep learning; probabilistic models; natural language processing. Part III: reinforcement learning and bandits; ranking; applied data science: computer vision and explanation; applied data science: healthcare; applied data science: e-commerce, finance, and advertising; applied data science: rich data; applied data science: applications; demo track. Chapter "Heavy-tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Data Mining and Big Data

Author : Ying Tan
Publisher : Springer
ISBN 13 : 3319409735
Total Pages : 564 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Data Mining and Big Data by : Ying Tan

Download or read book Data Mining and Big Data written by Ying Tan and published by Springer. This book was released on 2016-07-04 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS volume LNCS 9714 constitutes the refereed proceedings of the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016. The 57 papers presented in this volume were carefully reviewed and selected from 115 submissions. The theme of DMBD 2016 is "Serving Life with Data Science". Data mining refers to the activity of going through big data sets to look for relevant or pertinent information.The papers are organized in 10 cohesive sections covering all major topics of the research and development of data mining and big data and one Workshop on Computational Aspects of Pattern Recognition and Computer Vision.

Quantitative Trading

Author : Xin Guo
Publisher : CRC Press
ISBN 13 : 1315354357
Total Pages : 414 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Quantitative Trading by : Xin Guo

Download or read book Quantitative Trading written by Xin Guo and published by CRC Press. This book was released on 2017-01-06 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part covers market impact models, network models, multi-asset trading, machine learning techniques, and nonlinear filtering. The third part discusses electronic market making, liquidity, systemic risk, recent developments and debates on the subject.