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Wind Power Ensemble Forecasting
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 diff...
Modeling, Analysis and Control of Hydraulic Actuator for Forging
This book describes load modeling approaches for complex work pieces and batch forgings, and demonstrates analytical modeling and data-driven modeling approaches for known and unknown complex forging processes. It overcomes the current shortcomings of modeling, analysis and control approaches, presenting contributions in three major areas: In the first, several novel modeling approaches are proposed: a process/shape-decomposition modeling method to help estimate the deformation force; an online probabilistic learning machine for the modeling of batch forging processes; and several data-driven identification and modeling approaches for unknown forging processes under different work conditions...
Proceedings of ELM 2018
This book contains some selected papers from the International Conference on Extreme Learning Machine 2018, which was held in Singapore, November 21–23, 2018. This conference provided a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. Extreme Learning Machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental “learning particles” filling the gaps between machine ...
Non-intrusive Load Monitoring
Focusing on non-intrusive load monitoring techniques in the area of smart grids and smart buildings, this book presents a thorough introduction to related basic principles, while also proposing improvements. As the basis of demand-side energy management, the non-intrusive load monitoring techniques are highly promising in terms of their energy-saving and carbon emission reduction potential. The book is structured clearly and written concisely. It introduces each aspect of these techniques with a number of examples, helping readers to understand and use the corresponding results. It provides latest strengths on the non-intrusive load monitoring techniques for engineers and managers of relevant departments. It also offers extensive information and a source of inspiration for researchers and students, while outlining future research directions.
Energy Internet and We-Energy
This book focuses on the framework and implementation of energy integration systems with energy and smart-control technologies. It describes in detail We-Energy, a novel energy interaction mode based on a cyber-physical-economy-energy model, which can be adopted to solve the problem of energy supply and utilization. It then analyzes the key devices and technologies for developing the Energy Internet, such as converters, energy-conversion devices, system-level connection devices, optimization control strategies, cyber-physical system security, energy-system stability, communication technologies’ operating modes and distributed optimization algorithms, to enable readers to gain a comprehensi...
Plant Genetics and Molecular Breeding
The development of new plant varieties is a long and tedious process involving the generation of large seedling populations for the selection of the best individuals. While the ability of breeders to generate large populations is almost unlimited, the selection of these seedlings is the main factor limiting the generation of new cultivars. Molecular studies for the development of marker-assisted selection (MAS) strategies are particularly useful when the evaluation of the character is expensive, time-consuming, or with long juvenile periods. The papers published in the Special Issue “Plant Genetics and Molecular Breeding” report highly novel results and testable new models for the integr...
