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Author: Harsh S. Dhiman Publisher: Academic Press ISBN: 0128213671 Category : Science Languages : en Pages : 218
Book Description
Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation. - Features various supervised machine learning based regression models - Offers global case studies for turbine wind farm layouts - Includes state-of-the-art models and methodologies in wind forecasting
Author: Harsh S. Dhiman Publisher: Academic Press ISBN: 0128213671 Category : Science Languages : en Pages : 218
Book Description
Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation. - Features various supervised machine learning based regression models - Offers global case studies for turbine wind farm layouts - Includes state-of-the-art models and methodologies in wind forecasting
Author: Harsh S. Dhiman Publisher: Academic Press ISBN: 0128213531 Category : Science Languages : en Pages : 216
Book Description
Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation.
Author: Anita Khosla Publisher: Springer Nature ISBN: 9811646635 Category : Technology & Engineering Languages : en Pages : 188
Book Description
This book gathers selected high-quality research papers presented at International Conference on Renewable Technologies in Engineering (ICRTE 2021) organized by Manav Rachna International Institute of Research & Studies, Faridabad, Haryana, India, during 15–16 April 2021. The book includes conference papers on the theme “Computational Techniques for Renewable Energy Optimization”, which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of renewable energy integration, planning, control and optimization. It also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends and concerns as well as practical challenges encountered and solutions adopted in the fields of renewable energy and resources.
Author: Valentina Emilia Balas Publisher: Springer Nature ISBN: 3030519929 Category : Technology & Engineering Languages : en Pages : 460
Book Description
This book presents the proceedings of the 8th International Workshop on Soft Computing Applications, SOFA 2018, held on 13–15 September 2018 in Arad, Romania. The workshop was organized by Aurel Vlaicu University of Arad, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics – Arad Section, General Association of Engineers in Romania – Arad Section and BTM Resources Arad. The papers included in these proceedings, published post-conference, cover the research including Knowledge-Based Technologies for Web Applications, Cloud Computing, Security Algorithms and Computer Networks, Business Process Management, Computational Intelligence in Education and Modelling and Applications in Textiles and many other areas related to the Soft Computing. The book is directed to professors, researchers, and graduate students in area of soft computing techniques and applications.
Author: Andreas Momber Publisher: Academic Press ISBN: 0323857450 Category : Technology & Engineering Languages : en Pages : 756
Book Description
Corrosion and Corrosion Protection of Wind Power Structures in Marine Environments: Volume 2: Corrosion Protection Measures offers the first comprehensive review on corrosion and corrosion protection of offshore wind power structures. The book extensively discusses corrosion phenomena and corrosion types in different marine corrosion zones, including the modeling of corrosion processes and interactions between corrosion and structural stability. The book addresses important design issues, namely materials selection relevant to their performance in marine environments, corrosion allowance, and constructive design. Active and passive corrosion protection measures are emphasized, with special sections on cathodic corrosion protection and the use of protective coatings. Seawater related issues associated with cathodic protection, such as calcareous deposit formation, hydrogen formation, and fouling, are discussed. With respect to protective coatings, the book considers, for the first time, complete loading scenarios, including corrosive loads, mechanical loads, and special loads, and covers a wide range of coating materials. Problems associated with fouling and bacterial-induced corrosion are extensively reviewed. The book closes with a chapter on recent developments in maintenance strategies, inspection techniques, and repair technologies. The book will be of special interest to materials scientists, materials developers, corrosion engineers, maintenance engineers, civil engineers, steel work designers, mechanical engineers, marine engineers, chemists, and coating specialists. Offshore wind power is an emerging renewable technology and a key factor for a cleaner environment. Offshore wind power structures are situated in a demanding and challenging marine environment. The structures are loaded in a complex way, including mechanical loads and corrosive loads. Corrosion is one of the major limiting factors to the reliability and performance of the technology. Maintenance and repair of corrosion protection systems are particularly laborious and costly. - Explores the literature between 1950 and 2020 and contains over 2000 references - Offers the most complete monograph on the issue - Covers all aspects of corrosion protection in detail, including coatings, cathodic protection, corrosion allowance, constructive design, as well as maintenance and repair - Delivers the most complete review on corrosion of metals in marine/offshore environments - Focuses on all aspects of offshore wind power structures, namely foundations, towers, internal sections, connection flanges, and transformation platforms
Author: Ignacio Rojas Publisher: Springer ISBN: 3642386792 Category : Computers Languages : en Pages : 687
Book Description
This two-volume set LNCS 7902 and 7903 constitutes the refereed proceedings of the 12th International Work-Conference on Artificial Neural Networks, IWANN 2013, held in Puerto de la Cruz, Tenerife, Spain, in June 2013. The 116 revised papers were carefully reviewed and selected from numerous submissions for presentation in two volumes. The papers explore sections on mathematical and theoretical methods in computational intelligence, neurocomputational formulations, learning and adaptation emulation of cognitive functions, bio-inspired systems and neuro-engineering, advanced topics in computational intelligence and applications
Author: André Gensler Publisher: kassel university press GmbH ISBN: 3737606366 Category : Weights and measures Languages : en Pages : 216
Book Description
This thesis describes performance measures and ensemble architectures for deterministic and probabilistic forecasts using the application example of wind power forecasting and proposes a novel scheme for the situation-dependent aggregation of forecasting models. For performance measures, error scores for deterministic as well as probabilistic forecasts are compared, and their characteristics are shown in detail. For the evaluation of deterministic forecasts, a categorization by basic error measure and normalization technique is introduced that simplifies the process of choosing an appropriate error measure for certain forecasting tasks. Furthermore, a scheme for the common evaluation of different forms of probabilistic forecasts is proposed. Based on the analysis of the error scores, a novel hierarchical aggregation technique for both deterministic and probabilistic forecasting models is proposed that dynamically weights individual forecasts using multiple weighting factors such as weather situation and lead time dependent weighting. In the experimental evaluation it is shown that the forecasting quality of the proposed technique is able to outperform other state of the art forecasting models and ensembles.
Author: Saeid Pourroostaei Ardakani Publisher: Springer Nature ISBN: 9819966205 Category : Computers Languages : en Pages : 197
Book Description
This book aims to introduce big data solutions in urban sustainability applications—mainly smart transportation and healthcare systems. It focuses on machine learning techniques and data processing approaches which have the capacity to handle/process huge, live, and complex datasets in real-time transportation and healthcare applications. For this, several state-of-the-art data processing approaches including data pre-processing, classification, regression, and clustering are introduced, tested, and evaluated to highlight their benefits and constraints where data is sensitive, real-time, and/or semi-structured.
Author: Harsh S. Dhiman
Author: Harsh S. Dhiman
Author: Harsh S. Dhiman
Author: Anita Khosla
Author: Valentina Emilia Balas
Author: Andreas Momber
Author: Swagatam Das
Author: Ignacio Rojas
Author: Chengguo Su
Author: André Gensler
Author: Saeid Pourroostaei Ardakani