Deep Learning in Multi-step Prediction of Chaotic Dynamics PDF Download
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Author: Matteo Sangiorgio
Publisher: Springer Nature
ISBN: 3030944824
Category : Mathematics
Languages : en
Pages : 111
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Book Description
The book represents the first attempt to systematically deal with the use of deep neural networks to forecast chaotic time series. Differently from most of the current literature, it implements a multi-step approach, i.e., the forecast of an entire interval of future values. This is relevant for many applications, such as model predictive control, that requires predicting the values for the whole receding horizon. Going progressively from deterministic models with different degrees of complexity and chaoticity to noisy systems and then to real-world cases, the book compares the performances of various neural network architectures (feed-forward and recurrent). It also introduces an innovative and powerful approach for training recurrent structures specific for sequence-to-sequence tasks. The book also presents one of the first attempts in the context of environmental time series forecasting of applying transfer-learning techniques such as domain adaptation.
Author: Matteo Sangiorgio
Publisher: Springer Nature
ISBN: 3030944824
Category : Mathematics
Languages : en
Pages : 111
Get Book Here
Book Description
The book represents the first attempt to systematically deal with the use of deep neural networks to forecast chaotic time series. Differently from most of the current literature, it implements a multi-step approach, i.e., the forecast of an entire interval of future values. This is relevant for many applications, such as model predictive control, that requires predicting the values for the whole receding horizon. Going progressively from deterministic models with different degrees of complexity and chaoticity to noisy systems and then to real-world cases, the book compares the performances of various neural network architectures (feed-forward and recurrent). It also introduces an innovative and powerful approach for training recurrent structures specific for sequence-to-sequence tasks. The book also presents one of the first attempts in the context of environmental time series forecasting of applying transfer-learning techniques such as domain adaptation.
Author: Luigi Piroddi
Publisher: Springer Nature
ISBN: 3030859185
Category : Technology & Engineering
Languages : en
Pages : 151
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Book Description
This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists.
Author: Santo Banerjee
Publisher: Springer Nature
ISBN: 3030997928
Category : Science
Languages : en
Pages : 1433
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Book Description
This book covers recent trends and applications of nonlinear dynamics in various branches of society, science, and engineering. The selected peer-reviewed contributions were presented at the International Conference on Nonlinear Dynamics and Applications (ICNDA 2022) at Sikkim Manipal Institute of Technology (SMIT) and cover a broad swath of topics ranging from chaos theory and fractals to quantum systems and the dynamics of the COVID-19 pandemic. Organized by the SMIT Department of Mathematics, this international conference offers an interdisciplinary stage for scientists, researchers, and inventors to present and discuss the latest innovations and trends in all possible areas of nonlinear dynamics.
Author: Elena Tolkacheva
Publisher: Frontiers Media SA
ISBN: 2832522939
Category : Science
Languages : en
Pages : 186
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Book Description
Author: Fi-John Chang
Publisher: MDPI
ISBN: 3038975486
Category : Technology & Engineering
Languages : en
Pages : 376
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Book Description
Nowadays, the degree and scale of flood hazards has been massively increasing as a result of the changing climate, and large-scale floods jeopardize lives and properties, causing great economic losses, in the inundation-prone areas of the world. Early flood warning systems are promising countermeasures against flood hazards and losses. A collaborative assessment according to multiple disciplines, comprising hydrology, remote sensing, and meteorology, of the magnitude and impacts of flood hazards on inundation areas significantly contributes to model the integrity and precision of flood forecasting. Methodologically oriented countermeasures against flood hazards may involve the forecasting of reservoir inflows, river flows, tropical cyclone tracks, and flooding at different lead times and/or scales. Analyses of impacts, risks, uncertainty, resilience, and scenarios coupled with policy-oriented suggestions will give information for flood hazard mitigation. Emerging advances in computing technologies coupled with big-data mining have boosted data-driven applications, among which Machine Learning technology, with its flexibility and scalability in pattern extraction, has modernized not only scientific thinking but also predictive applications. This book explores recent Machine Learning advances on flood forecast and management in a timely manner and presents interdisciplinary approaches to modelling the complexity of flood hazards-related issues, with contributions to integrative solutions from a local, regional or global perspective.
Author: Haiyong Zheng
Publisher: Frontiers Media SA
ISBN: 2832549055
Category : Science
Languages : en
Pages : 555
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Book Description
Deep learning (DL), mainly composed of deep and complex neural networks such as recurrent network and convolutional network, is an emerging research branch in the field of artificial intelligence and machine learning. DL revolution has a far-reaching impact on all scientific disciplines and every corner of our lives. With continuing technological advances, marine science is entering into the big data era with the exponential growth of information. DL is an effective means of harnessing the power of big data. Combined with unprecedented data from cameras, acoustic recorders, satellite remote sensing, and large model outputs, DL enables scientists to solve complex problems in biology, ecosystems, climate, energy, as well as physical and chemical interactions. Although DL has made great strides, it is still only beginning to emerge in many fields of marine science, especially towards representative applications and best practices for the automatic analysis of marine organisms and marine environments. DL in nowadays' marine science mainly leverages cutting-edge techniques of deep neural networks and massive data which collected by
in-situ optical or acoustic imaging sensors for underwater applications, such as plankton classification and coral reef detection. This research topic aims to expand the applications of marine science to cover all aspects of detection, classification, segmentation, localization, and density estimation of marine objects, organisms, and phenomena.
Author: Tomonobu Senjyu
Publisher: Springer Nature
ISBN: 9819713293
Category :
Languages : en
Pages : 518
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Book Description
Author: Valeri Mladenov
Publisher: Springer
ISBN: 3642407285
Category : Computers
Languages : en
Pages : 660
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Book Description
The book constitutes the proceedings of the 23rd International Conference on Artificial Neural Networks, ICANN 2013, held in Sofia, Bulgaria, in September 2013. The 78 papers included in the proceedings were carefully reviewed and selected from 128 submissions. The focus of the papers is on following topics: neurofinance graphical network models, brain machine interfaces, evolutionary neural networks, neurodynamics, complex systems, neuroinformatics, neuroengineering, hybrid systems, computational biology, neural hardware, bioinspired embedded systems, and collective intelligence.
Author: Alberto Campisano
Publisher: MDPI
ISBN: 3039437895
Category : Technology & Engineering
Languages : en
Pages : 290
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Book Description
The Special Issue on Advances in Modeling and Management of Urban Water Networks (UWNs) explores four important topics of research in the context of UWNs: asset management, modeling of demand and hydraulics, energy recovery, and pipe burst identification and leakage reduction. In the first topic, the multi-objective optimization of interventions on the network is presented to find trade-off solutions between costs and efficiency. In the second topic, methodologies are presented to simulate and predict demand and to simulate network behavior in emergency scenarios. In the third topic, a methodology is presented for the multi-objective optimization of pump-as-turbine (PAT) installation sites in transmission mains. In the fourth topic, methodologies for pipe burst identification and leakage reduction are presented. As for the urban drainage systems (UDSs), the two explored topics are asset management, with a system upgrade to reduce flooding, and modeling of flow and water quality, with analyses on the transition from surface to pressurized flow, impact of water use reduction on the operation of UDSs, and sediment transport in pressurized pipes. The Special Issue also includes one paper dealing with the hydraulic modeling of an urban river with a complex cross-section.
Author: Chih-Huang Weng
Publisher: Springer Nature
ISBN: 9819957168
Category : Technology & Engineering
Languages : en
Pages : 418
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Book Description
This book presents select proceedings of the 5th International Conference on Advances in Civil and Ecological Engineering Research (ACEER 2023). The book covers a wide range of topics, including construction engineering and management hydraulic and hydrologic engineering, air quality and atmospheric pollution, ecological risk assessment and management, restoration and protection of environment, water pollution and treatment, and water recourses engineering. This book also covers state-of-the-art technologies in building sustainable city, resilient buildings, and sustainable issues in relating to civil engineering. It will be useful for researchers and engineers working in the field of civil and ecological engineering.
