Recurrent Neural Networks For Temporal Data Processing
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Recurrent Neural Networks For Temporal Data Processing
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Author : Hubert Cardot
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-02-09
Recurrent Neural Networks For Temporal Data Processing written by Hubert Cardot and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-09 with Computers categories.
The RNNs (Recurrent Neural Networks) are a general case of artificial neural networks where the connections are not feed-forward ones only. In RNNs, connections between units form directed cycles, providing an implicit internal memory. Those RNNs are adapted to problems dealing with signals evolving through time. Their internal memory gives them the ability to naturally take time into account. Valuable approximation results have been obtained for dynamical systems.
Recurrent Neural Networks For Temporal Data Processing
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Author : Hubert Cardot
language : en
Publisher:
Release Date : 2011
Recurrent Neural Networks For Temporal Data Processing written by Hubert Cardot and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
The RNNs (Recurrent Neural Networks) are a general case of artificial neural networks where the connections are not feed-forward ones only. In RNNs, connections between units form directed cycles, providing an implicit internal memory. Those RNNs are adapted to problems dealing with signals evolving through time. Their internal memory gives them the ability to naturally take time into account. Valuable approximation results have been obtained for dynamical systems.
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.
Deep Learning In Time Series Analysis
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Author : Arash Gharehbaghi
language : en
Publisher: CRC Press
Release Date : 2023-07-07
Deep Learning In Time Series Analysis written by Arash Gharehbaghi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-07 with Mathematics categories.
Deep learning is an important element of artificial intelligence, especially in applications such as image classification in which various architectures of neural network, e.g., convolutional neural networks, have yielded reliable results. This book introduces deep learning for time series analysis, particularly for cyclic time series. It elaborates on the methods employed for time series analysis at the deep level of their architectures. Cyclic time series usually have special traits that can be employed for better classification performance. These are addressed in the book. Processing cyclic time series is also covered herein. An important factor in classifying stochastic time series is the structural risk associated with the architecture of classification methods. The book addresses and formulates structural risk, and the learning capacity defined for a classification method. These formulations and the mathematical derivations will help the researchers in understanding the methods and even express their methodologies in an objective mathematical way. The book has been designed as a self-learning textbook for the readers with different backgrounds and understanding levels of machine learning, including students, engineers, researchers, and scientists of this domain. The numerous informative illustrations presented by the book will lead the readers to a deep level of understanding about the deep learning methods for time series analysis.
Intelligent Information Processing Xii
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Author : Zhongzhi Shi
language : en
Publisher: Springer Nature
Release Date : 2024-04-05
Intelligent Information Processing Xii written by Zhongzhi Shi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-05 with Computers categories.
The two-volume set IFIP AICT 703 and 704 constitutes the refereed conference proceedings of the 13th IFIP TC 12 International Conference on Intelligent Information Processing XII, IIP 2024, held in Shenzhen, China, during May 3–6, 2024. The 49 full papers and 5 short papers presented in these proceedings were carefully reviewed and selected from 58 submissions. The papers are organized in the following topical sections: Volume I: Machine Learning; Natural Language Processing; Neural and Evolutionary Computing; Recommendation and Social Computing; Business Intelligence and Risk Control; and Pattern Recognition. Volume II: Image Understanding.
Artificial Intelligence In Data And Big Data Processing
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Author : Ngoc Hoang Thanh Dang
language : en
Publisher: Springer Nature
Release Date : 2022-05-18
Artificial Intelligence In Data And Big Data Processing written by Ngoc Hoang Thanh Dang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-18 with Computers categories.
The book presents studies related to artificial intelligence (AI) and its applications to process and analyze data and big data to create machines or software that can better understand business behavior, industry activities, and human health. The studies were presented at “The 2021 International Conference on Artificial Intelligence and Big Data in Digital Era” (ICABDE 2021), which was held in Ho Chi Minh City, Vietnam, during December 18-19, 2021. The studies are pointing toward the famous slogan in technology “Make everything smarter,” i.e., creating machines that can understand and can communicate with humans, and they must act like humans in different aspects such as vision, communication, thinking, feeling, and acting. “A computer would deserve to be called intelligent if it could deceive a human into believing that it was human” —Alan Turing
Machine Learning And Cryptographic Solutions For Data Protection And Network Security
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Author : Ruth, J. Anitha
language : en
Publisher: IGI Global
Release Date : 2024-05-31
Machine Learning And Cryptographic Solutions For Data Protection And Network Security written by Ruth, J. Anitha and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-31 with Computers categories.
In the relentless battle against escalating cyber threats, data security faces a critical challenge – the need for innovative solutions to fortify encryption and decryption processes. The increasing frequency and complexity of cyber-attacks demand a dynamic approach, and this is where the intersection of cryptography and machine learning emerges as a powerful ally. As hackers become more adept at exploiting vulnerabilities, the book stands as a beacon of insight, addressing the urgent need to leverage machine learning techniques in cryptography. Machine Learning and Cryptographic Solutions for Data Protection and Network Security unveil the intricate relationship between data security and machine learning and provide a roadmap for implementing these cutting-edge techniques in the field. The book equips specialists, academics, and students in cryptography, machine learning, and network security with the tools to enhance encryption and decryption procedures by offering theoretical frameworks and the latest empirical research findings. Its pages unfold a narrative of collaboration and cross-pollination of ideas, showcasing how machine learning can be harnessed to sift through vast datasets, identify network weak points, and predict future cyber threats.
Icsetpsd 2023
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Author : Baskaran Jeevarathinam
language : en
Publisher: European Alliance for Innovation
Release Date : 2024-01-23
Icsetpsd 2023 written by Baskaran Jeevarathinam and has been published by European Alliance for Innovation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-23 with Business & Economics categories.
The International Conference on Science, Engineering and Technology Practices for Sustainable Development (ICSETPSD-23) brought researchers, scientists, engineers, industrial professionals, and scholar students for the dissemination of original research results, new ideas, and practical development experiences which concentrate on both theory and practices from around the world in all the areas of science, engineering, and technology practices for sustainable development. The theme of ICSETPSD-23 was “Science, Engineering and Technology for sustainable development”. The technical program of ICSETPSD-23 consisted of 140 full papers, scheduled for oral presentation sessions at the main conference tracks. The conference tracks were: Track 1 – Science for sustainable development; Track 2 – Sustainability through Engineering; Track 3 – Sustainable developments in Health Care; and Track 4 – Technology practices for sustainability. Aside from the high quality technical paper presentations, the technical program also featured eight keynote speeches and one invited talk. We strongly believe that ICSETPSD-23 conference provides a good forum for all researchers, developers, and practitioners to discuss all science and technology aspects that are relevant to sustainable developments. We also expect that the future ICSETPSD conference will be as successful and stimulating, as indicated by the contributions presented in this volume.
Proceedings Of The 2024 4th International Conference On Modern Educational Technology And Social Sciences Icmetss 2024
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Author : Vishalache A/P Balakrishnan
language : en
Publisher: Springer Nature
Release Date : 2024-11-30
Proceedings Of The 2024 4th International Conference On Modern Educational Technology And Social Sciences Icmetss 2024 written by Vishalache A/P Balakrishnan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-30 with Education categories.
This is an open access book. The term "modern educational technology" refers to the theory and practice of optimizing teaching through the design, development, utilization, management, and evaluation of instructional processes and resources using contemporary educational theories and advanced information technology. Education and social sciences are mutually reinforcing disciplines that play a crucial role in the new social development pattern. The knowledge capacity of individuals is increasingly becoming the decisive factor for modern productivity growth. Consequently, education has emerged as a vital investment field for intellectual resource development. Investing in education yields significant benefits by transforming scientific and technological potential into tangible productivity outcomes. Ultimately, it is imperative to prioritize education and foster lifelong learning opportunities. ICMETSS 2024 will concentrate on advancing modern educational technology alongside social sciences while exploring their interrelationship to promote mutual progress.
Introduction To Time Series Analysis
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Author : Vikas Rathi
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Introduction To Time Series Analysis written by Vikas Rathi and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.
"Introduction to Time Series Analysis" is a comprehensive guide exploring the world of time series data, blending theoretical insights with practical applications. Time series analysis is crucial across disciplines like economics, finance, engineering, and environmental science, helping us understand past patterns, forecast future trends, and make informed decisions. We cater to students, researchers, and practitioners seeking a deep understanding of time series analysis. Covering a range of topics from foundational concepts to advanced techniques, we ensure readers gain a holistic view of the subject. With clear explanations, illustrative examples, and real-world case studies, this book equips readers with the knowledge and skills needed to tackle complex time series data effectively. The book provides a solid theoretical foundation in time series analysis, covering topics such as time series decomposition, forecasting methods, and advanced modeling techniques. Emphasis is placed on practical applications, with real-world examples and case studies illustrating concepts and methodologies. The text is written in clear and accessible language, suitable for readers with varying expertise, and acknowledges the interdisciplinary nature of time series analysis, exploring its applications across different fields. Whether you're a student, researcher, or practitioner, "Introduction to Time Series Analysis" offers valuable insights and practical guidance to harness the power of time series data for informed decision-making.