Hybrid Advanced Optimization Methods With Evolutionary Computation Techniques In Energy Forecasting
DOWNLOAD
Download Hybrid Advanced Optimization Methods With Evolutionary Computation Techniques In Energy Forecasting PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Hybrid Advanced Optimization Methods With Evolutionary Computation Techniques In Energy Forecasting book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Hybrid Advanced Optimization Methods With Evolutionary Computation Techniques In Energy Forecasting
DOWNLOAD
Author : Wei-Chiang Hong
language : en
Publisher: MDPI
Release Date : 2018-10-19
Hybrid Advanced Optimization Methods With Evolutionary Computation Techniques In Energy Forecasting written by Wei-Chiang Hong and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-19 with Technology & Engineering categories.
This book is a printed edition of the Special Issue "Hybrid Advanced Optimization Methods with Evolutionary Computation Techniques in Energy Forecasting" that was published in Energies
Hybrid Advanced Optimization Methods With Evolutionary Computation Techniques In Energy Forecasting
DOWNLOAD
Author : Wei-Chiang Hong
language : en
Publisher:
Release Date : 2018
Hybrid Advanced Optimization Methods With Evolutionary Computation Techniques In Energy Forecasting written by Wei-Chiang Hong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
More accurate and precise energy demand forecasts are required when energy decisions are made in a competitive environment. Particularly in the Big Data era, forecasting models are always based on a complex function combination, and energy data are always complicated. Examples include seasonality, cyclicity, fluctuation, dynamic nonlinearity, and so on. These forecasting models have resulted in an over-reliance on the use of informal judgment and higher expenses when lacking the ability to determine data characteristics and patterns. The hybridization of optimization methods and superior evolutionary algorithms can provide important improvements via good parameter determinations in the optimization process, which is of great assistance to actions taken by energy decision-makers. This book aimed to attract researchers with an interest in the research areas described above. Specifically, it sought contributions to the development of any hybrid optimization methods (e.g., quadratic programming techniques, chaotic mapping, fuzzy inference theory, quantum computing, et cetera) with advanced algorithms (e.g., genetic algorithms, ant colony optimization, particle swarm optimization algorithm, et cetera) that have superior capabilities over the traditional optimization approaches to overcome some embedded drawbacks, and the application of these advanced hybrid approaches to significantly improve forecasting accuracy.
Intelligent Optimization Modelling In Energy Forecasting
DOWNLOAD
Author : Wei-Chiang Hong
language : en
Publisher: MDPI
Release Date : 2020-04-01
Intelligent Optimization Modelling In Energy Forecasting written by Wei-Chiang Hong and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-01 with Computers categories.
Accurate energy forecasting is important to facilitate the decision-making process in order to achieve higher efficiency and reliability in power system operation and security, economic energy use, contingency scheduling, the planning and maintenance of energy supply systems, and so on. In recent decades, many energy forecasting models have been continuously proposed to improve forecasting accuracy, including traditional statistical models (e.g., ARIMA, SARIMA, ARMAX, multi-variate regression, exponential smoothing models, Kalman filtering, Bayesian estimation models, etc.) and artificial intelligence models (e.g., artificial neural networks (ANNs), knowledge-based expert systems, evolutionary computation models, support vector regression, etc.). Recently, due to the great development of optimization modeling methods (e.g., quadratic programming method, differential empirical mode method, evolutionary algorithms, meta-heuristic algorithms, etc.) and intelligent computing mechanisms (e.g., quantum computing, chaotic mapping, cloud mapping, seasonal mechanism, etc.), many novel hybrid models or models combined with the above-mentioned intelligent-optimization-based models have also been proposed to achieve satisfactory forecasting accuracy levels. It is important to explore the tendency and development of intelligent-optimization-based modeling methodologies and to enrich their practical performances, particularly for marine renewable energy forecasting.
Hybrid Advanced Techniques For Forecasting In Energy Sector
DOWNLOAD
Author : Wei-Chiang Hong
language : en
Publisher: MDPI
Release Date : 2018-10-19
Hybrid Advanced Techniques For Forecasting In Energy Sector written by Wei-Chiang Hong and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-19 with Technology & Engineering categories.
This book is a printed edition of the Special Issue "Hybrid Advanced Techniques for Forecasting in Energy Sector" that was published in Energies
Advanced Optimization Methods And Big Data Applications In Energy Demand Forecast
DOWNLOAD
Author : Federico Divina
language : en
Publisher: MDPI
Release Date : 2021-08-30
Advanced Optimization Methods And Big Data Applications In Energy Demand Forecast written by Federico Divina and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-30 with Technology & Engineering categories.
The use of data collectors in energy systems is growing more and more. For example, smart sensors are now widely used in energy production and energy consumption systems. This implies that huge amounts of data are generated and need to be analyzed in order to extract useful insights from them. Such big data give rise to a number of opportunities and challenges for informed decision making. In recent years, researchers have been working very actively in order to come up with effective and powerful techniques in order to deal with the huge amount of data available. Such approaches can be used in the context of energy production and consumption considering the amount of data produced by all samples and measurements, as well as including many additional features. With them, automated machine learning methods for extracting relevant patterns, high-performance computing, or data visualization are being successfully applied to energy demand forecasting.
Advanced Computation Solutions For Energy Efficiency
DOWNLOAD
Author : Azrour, Mourade
language : en
Publisher: IGI Global
Release Date : 2025-03-20
Advanced Computation Solutions For Energy Efficiency written by Azrour, Mourade and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-20 with Science categories.
Advanced computation solutions transform how industries and organizations optimize energy usage, reduce waste, and minimize environmental impact. By leveraging cutting-edge technologies, these solutions enable real-time monitoring and precise control over energy systems. From smart grids to energy-efficient building management systems, computational tools enable accurate prediction, analysis, and optimization of energy consumption. As the demand for sustainable energy practices grows, advanced computational solutions are becoming indispensable for achieving greater efficiency, lowering costs, and supporting global efforts to combat climate change. These innovations offer promising pathways toward a more sustainable and energy-conscious future. Advanced Computation Solutions for Energy Efficiency examines the intersection of technology and energy management. It explores the role of artificial intelligence and machine learning in analyzing energy consumption patterns and optimizing resource allocation. This book covers topics such as green economics, renewable energy, and fault detection, and is a useful resource for energy scientists, computer engineers, business owners, academicians, and researchers.
Advanced Computational Methods In Energy Power Electric Vehicles And Their Integration
DOWNLOAD
Author : Kang Li
language : en
Publisher: Springer
Release Date : 2017-09-01
Advanced Computational Methods In Energy Power Electric Vehicles And Their Integration written by Kang Li and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-01 with Computers categories.
The three-volume set CCIS 761, CCIS 762, and CCIS 763 constitutes the thoroughly refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2017, and of the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, held in Nanjing, China, in September 2017. The 208 revised full papers presented were carefully reviewed and selected from over 625 submissions. The papers of this volume are organized in topical sections on: Biomedical Signal Processing; Computational Methods in Organism Modeling; Medical Apparatus and Clinical Applications; Bionics Control Methods, Algorithms and Apparatus; Modeling and Simulation of Life Systems; Data Driven Analysis; Image and Video Processing; Advanced Fuzzy and Neural Network Theory and Algorithms; Advanced Evolutionary Methods and Applications; Advanced Machine Learning Methods and Applications; Intelligent Modeling, Monitoring, and Control of Complex Nonlinear Systems; Advanced Methods for Networked Systems; Control and Analysis of Transportation Systems; Advanced Sliding Mode Control and Applications; Advanced Analysis of New Materials and Devices; Computational Intelligence in Utilization of Clean and Renewable Energy Resources; Intelligent Methods for Energy Saving and Pollution Reduction; Intelligent Methods in Developing Electric Vehicles, Engines and Equipment; Intelligent Computing and Control in Power Systems; Modeling, Simulation and Control in Smart Grid and Microgrid; Optimization Methods; Computational Methods for Sustainable Environment.
Advanced Control And Optimization Paradigms For Wind Energy Systems
DOWNLOAD
Author : Radu-Emil Precup
language : en
Publisher: Springer
Release Date : 2019-02-07
Advanced Control And Optimization Paradigms For Wind Energy Systems written by Radu-Emil Precup and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-07 with Technology & Engineering categories.
This book presents advanced studies on the conversion efficiency, mechanical reliability, and the quality of power related to wind energy systems. The main concern regarding such systems is reconciling the highly intermittent nature of the primary source (wind speed) with the demand for high-quality electrical energy and system stability. This means that wind energy conversion within the standard parameters imposed by the energy market and power industry is unachievable without optimization and control. The book discusses the rapid growth of control and optimization paradigms and applies them to wind energy systems: new controllers, new computational approaches, new applications, new algorithms, and new obstacles.
Mechanical Design Optimization Using Advanced Optimization Techniques
DOWNLOAD
Author : R. Venkata Rao
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-01-14
Mechanical Design Optimization Using Advanced Optimization Techniques written by R. Venkata Rao and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-14 with Technology & Engineering categories.
Mechanical design includes an optimization process in which designers always consider objectives such as strength, deflection, weight, wear, corrosion, etc. depending on the requirements. However, design optimization for a complete mechanical assembly leads to a complicated objective function with a large number of design variables. It is a good practice to apply optimization techniques for individual components or intermediate assemblies than a complete assembly. Analytical or numerical methods for calculating the extreme values of a function may perform well in many practical cases, but may fail in more complex design situations. In real design problems, the number of design parameters can be very large and their influence on the value to be optimized (the goal function) can be very complicated, having nonlinear character. In these complex cases, advanced optimization algorithms offer solutions to the problems, because they find a solution near to the global optimum within reasonable time and computational costs. Mechanical Design Optimization Using Advanced Optimization Techniques presents a comprehensive review on latest research and development trends for design optimization of mechanical elements and devices. Using examples of various mechanical elements and devices, the possibilities for design optimization with advanced optimization techniques are demonstrated. Basic and advanced concepts of traditional and advanced optimization techniques are presented, along with real case studies, results of applications of the proposed techniques, and the best optimization strategies to achieve best performance are highlighted. Furthermore, a novel advanced optimization method named teaching-learning-based optimization (TLBO) is presented in this book and this method shows better performance with less computational effort for the large scale problems. Mechanical Design Optimization Using Advanced Optimization Techniques is intended for designers, practitioners, managers, institutes involved in design related projects, applied research workers, academics, and graduate students in mechanical and industrial engineering and will be useful to the industrial product designers for realizing a product as it presents new models and optimization techniques to make tasks easier, logical, efficient and effective. .
Designing Engineering Structures Using Stochastic Optimization Methods
DOWNLOAD
Author : Levent Aydin
language : en
Publisher: CRC Press
Release Date : 2020-04-27
Designing Engineering Structures Using Stochastic Optimization Methods written by Levent Aydin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-27 with Science categories.
Among all aspects of engineering, design is the most important step in developing a new product. A systematic approach to managing design issues can only be accomplished by applying mathematical optimization methods. Furthermore, due to the practical issues in engineering problems, there are limitations in using traditional methods. As such, stochastic optimization methods such as differential evolution, simulated annealing, and genetic algorithms are preferable in finding solutions in design optimization problems. This book reviews mechanical engineering design optimization using stochastic methods. It introduces students and design engineers to practical aspects of complicated mathematical optimization procedures, and outlines steps for wide range of selected engineering design problems. It shows how engineering structures are systematically designed. Many new engineering design applications based on stochastic optimization techniques in automotive, energy, military, naval, manufacturing process and fluids-heat transfer, are described in the book. For each design optimization problem described, background is provided for understanding the solutions. There are very few books on optimization that include engineering applications. They cover limited applications, and that too of well-known design problems of advanced and niche nature. Common problems are hardly addressed. Thus, the subject has remained fairly theoretical. To overcome this, each chapter in this book is contributed by at least one academic and one industrial expert researcher.