Applied Soft Computing Techniques For Renewable Energy
DOWNLOAD
Download Applied Soft Computing Techniques For Renewable Energy PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Applied Soft Computing Techniques For Renewable Energy 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
Applied Soft Computing Techniques
DOWNLOAD
Author : Samarjeet Borah
language : en
Publisher: CRC Press
Release Date : 2025-07-11
Applied Soft Computing Techniques written by Samarjeet Borah and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-11 with Computers categories.
Soft computing techniques have the ability to handle complex, uncertain, and imprecise information to create usable solutions to convoluted problems, or those just too time-consuming to solve with current hardware. This new book details the use and applications of soft computing technology in several fields, exploring the use of these techniques in biomedical applications, communication technologies, data analytics and applications, image processing, and natural language processing. The chapters in the section on biomedical applications explore soft computing techniques for cancer data analysis, depression and mental health analysis, heart disease detection, etc. The editors go on to discuss soft computing in communication systems, looking at graphs, design processes, and mapping techniques, as well as the integration of IoT devices, drone technology, etc. The volume also details how soft computing methodologies can assist in tackling the obstacles associated with signal processing, network optimization, quality of service, and beyond. Several chapters discuss the use of soft computing techniques in data compression, handling of large-scaled heterogenous databases, visualization techniques, etc. Applications of soft computing in image processing are also discussed and cover human face recognition, casualty detection, traffic sign recognition, and predicting soil features using satellite imagery. Soft computing techniques in natural language processing consider text-to-speech signal conversion, NLP and speech recognition, speech emotion recognition, and more. This volume will help to facilitate the amalgamation of theoretical principles and practical applications, bringing forth possible solutions to complex problems in various domains. The book is a welcome resource for researchers, students, professionals, and even for individuals looking for knowledge on soft computing. Applied Soft Computing Techniques: Theoretical Principles and Practical Applications will help to facilitate the amalgamation of theoretical principles and practical applications, bringing forth possible solutions to complex problems in various domains. The book is a welcome resource for researchers, students, professionals, and even for individuals looking for knowledge on soft computing.
Applied Soft Computing Techniques For Renewable Energy
DOWNLOAD
Author : Amit Kumar Thakur
language : en
Publisher: Nova Science Publishers
Release Date : 2020
Applied Soft Computing Techniques For Renewable Energy written by Amit Kumar Thakur and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Science categories.
"This book provides a better understanding of Fuzzy set theory, Fuzzy logic and Neural Networks and various other techniques seem very well suited for modeling and controlling a real system. Energy is of major importance to civilization, because it is driving force which binds human race. The estimation of energy in the form of renewable and sustainable is one of the important aspects to understand the how resources are harnessed and to predict what might happen under various possible future conditions. Using available modelling techniques to generate the best algorithms, the objective is to determine the best solution in terms of comparing the performances of the solutions through different parameters for a specific case. Consumption of Fossil fuels at a rapid pace has generated an alarming situation and with the subsequent increase in the number of vehicle the pollution level has reached well beyond human's control. This is frightening enough to observe the fact that the pollution level has surpassed all records and the need of the hour is to find an alternate fuel which can really be of great assistance in reducing the exhaust emission and augment the performance parameters of engine. Major researches are carried out on various engines to draw closer towards a realistic solution. Experiments performed on various engines are considered to be time consuming and the expenses met to perform these experiments are too costly, so the need of soft computing techniques involved in this area. Soft computing can be better described as the process to find the solution to an inexact problem. Soft computing has showed lot of potential in giving the researchers the exact solution may be in case of validating or predicting the performance and emission parameters. Artificial Neural Network (ANN), Adaptive Neuro Fuzzy Inference system (ANFIS), Fuzzy Expert System (FES), Response Surface Methodology (RSM) and Support Vector Machine (SVM) are the various soft computing techniques widely used. This book focuses on to carry out the comprehensive review and various other experimental works of various researchers who have carried out the work on these various soft computing techniques on various engines with various alternative fuels On the basis of modelling techniques, time is saved to a great extent and the capital investment involved is comparably very low. Various modelling technniques are being readily used to predict the performance parameters for various engines and modelling techniques have become the readily available tool to compare and validate the experimental work being carried out by researchers to get accurate matching with the experimental data.The benefit of this issue will be at large in connecting with varieties of work done in the field of Biomass which includes wood and wood waste, municipal solid waste. Landfill gas and biogas. Ethanol, Biodiesel, Hydropower, Geothermal, Wind, Solar.Thus soft computing techniques are fast and reliable hence, they can be a substitute for conventional experiments"--
Applied Soft Computing And Embedded System Applications In Solar Energy
DOWNLOAD
Author : Rupendra Kumar Pachauri
language : en
Publisher: CRC Press
Release Date : 2021-05-26
Applied Soft Computing And Embedded System Applications In Solar Energy written by Rupendra Kumar Pachauri and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-26 with Computers categories.
Applied Soft Computing and Embedded System Applications in Solar Energy deals with energy systems and soft computing methods from a wide range of approaches and application perspectives. The authors examine how embedded system applications can deal with the smart monitoring and controlling of stand-alone and grid-connected solar photovoltaic (PV) systems for increased efficiency. Growth in the area of artificial intelligence with embedded system applications has led to a new era in computing, impacting almost all fields of science and engineering. Soft computing methods implemented to energy-related problems regularly face data-driven issues such as problems of optimization, classification, clustering, or prediction. The authors offer real-time implementation of soft computing and embedded system in the area of solar energy to address the issues with microgrid and smart grid projects (both renewable and non-renewable generations), energy management, and power regulation. They also discuss and examine alternative solutions for energy capacity assessment, energy efficiency systems design, as well as other specific smart grid energy system applications. The book is intended for students, professionals, and researchers in electrical and computer engineering fields, working on renewable energy resources, microgrids, and smart grid projects. Examines the integration of hardware with stand-alone PV panels and real-time monitoring of factors affecting the efficiency of the PV panels Offers real-time implementation of soft computing and embedded system in the area of solar energy Discusses how soft computing plays a huge role in the prediction of efficiency of stand-alone and grid-connected solar PV systems Discusses how embedded system applications with smart monitoring can control and enhance the efficiency of stand-alone and grid-connected solar PV systems Explores swarm intelligence techniques for solar PV parameter estimation Dr. Rupendra Kumar Pachauri is Assistant Professor – Selection Grade in the Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies (UPES), Dehradun, India. Dr. Jitendra Kumar Pandey is Professor & Head of R&D in the University of Petroleum and Energy Studies (UPES), Dehradun, India. Mr. Abhishek Sharma is working as a research scientist in the research and development department (UPES, India). Dr. Om Prakash Nautiyal is working as a scientist in Uttarakhand Science Education & Research Centre (USERC), Department of Information and Science Technology, Govt. of Uttarakhand, Dehradun, India. Prof. Mangey Ram is working as a Research Professor at Graphic Era Deemed to be University, Dehradun, India.
Soft Computing Applications For Renewable Energy And Energy Efficiency
DOWNLOAD
Author : Cascales, Maria del Socorro García
language : en
Publisher: IGI Global
Release Date : 2014-10-31
Soft Computing Applications For Renewable Energy And Energy Efficiency written by Cascales, Maria del Socorro García and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-31 with Technology & Engineering categories.
As the climate and environment continue to fluctuate, researchers are urgently looking for new ways to preserve our limited resources and prevent further environmental degradation. The answer can be found through computer science, a field that is evolving at precisely the time it is needed most. Soft Computing Applications for Renewable Energy and Energy Efficiency brings together the latest technological research in computational intelligence and fuzzy logic as a way to care for our environment. This reference work highlights current advances and future trends in environmental sustainability using the principles of soft computing, making it an essential resource for students, researchers, engineers, and practitioners in the fields of project engineering and energy science.
Computer Vision And Machine Intelligence For Renewable Energy Systems
DOWNLOAD
Author : Ashutosh Kumar Dubey
language : en
Publisher: Elsevier
Release Date : 2024-09-20
Computer Vision And Machine Intelligence For Renewable Energy Systems written by Ashutosh Kumar Dubey and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-20 with Technology & Engineering categories.
Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source
Design Analysis And Applications Of Renewable Energy Systems
DOWNLOAD
Author : Ahmad Taher Azar
language : en
Publisher: Academic Press
Release Date : 2021-09-09
Design Analysis And Applications Of Renewable Energy Systems written by Ahmad Taher Azar and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-09 with Technology & Engineering categories.
Design, Analysis and Applications of Renewable Energy Systems covers recent advancements in the study of renewable energy control systems by bringing together diverse scientific breakthroughs on the modeling, control and optimization of renewable energy systems as conveyed by leading energy systems engineering researchers. The book focuses on present novel solutions for many problems in the field, covering modeling, control theorems and the optimization techniques that will help solve many scientific issues for researchers. Multidisciplinary applications are also discussed, along with their fundamentals, modeling, analysis, design, realization and experimental results. This book fills the gaps between different interdisciplinary applications, ranging from mathematical concepts, modeling, and analysis, up to the realization and experimental work. - Presents some of the latest innovative approaches to renewable energy systems from the point-of-view of dynamic modeling, system analysis, optimization, control and circuit design - Focuses on advances related to optimization techniques for renewable energy and forecasting using machine learning methods - Includes new circuits and systems, helping researchers solve many nonlinear problems
Optimization Techniques For Hybrid Power Systems Renewable Energy Electric Vehicles And Smart Grid
DOWNLOAD
Author : Hazra, Sunanda
language : en
Publisher: IGI Global
Release Date : 2024-07-17
Optimization Techniques For Hybrid Power Systems Renewable Energy Electric Vehicles And Smart Grid written by Hazra, Sunanda and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-17 with Technology & Engineering categories.
Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid is a comprehensive guide that delves into the intricate world of renewable energy integration and its impact on electrical systems. With the current global energy crisis and the urgent need to address climate change, this book explores the latest advancements and research surrounding optimization techniques in the realm of renewable energy. This book has a focus on nature-inspired and meta-heuristic optimization methods, and it demonstrates how these techniques have revolutionized renewable energy problem-solving and their application in real-world scenarios. It examines the challenges and opportunities in achieving a larger utilization of renewable energy sources to reduce carbon emissions and air pollutants while meeting renewable portfolio standards and enhancing energy efficiency. This book serves as a valuable resource for researchers, academicians, industry delegates, scientists, and final-year master's degree students. It covers a wide range of topics, including novel power generation technology, advanced energy conversion systems, low-carbon technology in power generation and smart grids, AI-based control strategies, data analytics, electrified transportation infrastructure, and grid-interactive building infrastructure.
Soft Computing In Industry 5 0 For Sustainability
DOWNLOAD
Author : C Kishor Kumar Reddy
language : en
Publisher: Springer Nature
Release Date : 2024-11-15
Soft Computing In Industry 5 0 For Sustainability written by C Kishor Kumar Reddy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-15 with Computers categories.
Soft computing and Industry 5.0 are two distinct concepts that, when combined, can have a significant impact on sustainability initiatives within various industries. Soft computing is a subfield of artificial intelligence (AI) that aims to address problems characterized by uncertainty, imprecision, and partial truth. It encompasses various computational techniques, such as fuzzy logic, neural networks, genetic algorithms, and machine learning, which enable machines to deal with complex and uncertain data in a more human-like manner. Soft computing techniques are particularly valuable in sustainability efforts because they can handle non-linear relationships and uncertain data that often arise in environmental and social contexts. For example, they can be used to optimize energy consumption, waste management, and resource allocation in industries by considering various factors and trade-offs. The book highlights the latest innovations in intelligent systems in classical machine learning, deep learning, Internet of Things (IoT), Industrial Internet of Things (IIoT), blockchain, knowledge representation, knowledge management, big data, and natural language processing. (NLP). The book contains many contemporary articles from both scientists and practitioners working in many fields where soft computing, intelligent systems and the IIoT can break new ground. Intelligent systems and the Internet of Things are now essential technologies in almost every field. From agriculture to industry to healthcare, the scope of smart systems and IIoT is as wide as the horizon. Nowadays, these technologies are extensively used in developed countries, but they are still at an early stage in emerging countries. The primary market of this book is senior undergraduate students, post graduate students, practitioners, researchers, academicians, industrialists, and professionals working in areas of core computer science, electrical engineering, mechanical engineering, environmental engineering and agricultural engineering. The secondary audience of this book is individuals working in the areas of manufacturing, agriculture, remote sensing, environmental engineering, health care, smart cities, smart farming, remote sensing, supply chain management and hydrology.
Evolutionary Methods Based Modeling And Analysis Of Solar Thermal Systems
DOWNLOAD
Author : Biplab Das
language : en
Publisher: Springer Nature
Release Date : 2023-04-29
Evolutionary Methods Based Modeling And Analysis Of Solar Thermal Systems written by Biplab Das and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-29 with Technology & Engineering categories.
This book presents insights into the thermal performance of solar thermal collectors using both computational and experimental modeling. It consists of various computational and experimental case studies conducted by the authors on the solar thermal collector system. The authors begin by developing thermal modeling using a case study that shows the effect of different governing parameters. A few more experimental cases studies follow that highlight the energy, exergy, and environmental performance of the solar thermal collector system and to examine the performance of a modified solar collector system, illustrating performance improvement techniques. Finally, application of different evolutionary optimization techniques such as soft computing and evolutionary methods, like fuzzy techniques, MCDM methods like fuzzy logic based expert system (FLDS), Artificial Neural Network (ANN), Grey relational analysis (GRA), Entropy-Jaya algorithm, Entropy-VIKOR etc. are employed.
Forecasting Methods For Renewable Power Generation
DOWNLOAD
Author : Jai Govind Singh
language : en
Publisher: John Wiley & Sons
Release Date : 2025-03-18
Forecasting Methods For Renewable Power Generation written by Jai Govind Singh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-18 with Technology & Engineering categories.
Forecasting Methods for Renewable Power Generation is an essential resource for both professionals and students, providing in-depth insights into vital forecasting techniques that enhance grid stability, optimize resource management, and enable effective electricity pricing strategies. It is a must-have reference for anyone involved in the clean energy sector. Forecasting techniques in renewable power generation, demand response, and electricity pricing are vital for grid stability, optimal resource allocation, efficient energy management, and cost-effective electricity supply. They enable grid operators and market participants to make informed decisions, mitigate risks, and enhance the overall reliability and sustainability of the electrical grid. Electricity prices can vary significantly based on supply and demand dynamics. By forecasting expected demand and the availability of generation resources, market operators can optimize electricity pricing strategies. This alignment of prices with anticipated supply-demand balance incentivizes the efficient use of electricity and promotes market efficiency. Accurate forecasting helps prevent price spikes, reduces market uncertainties, and supports the development of effective energy trading strategies. This book presents these topics and trends in an encyclopedic format, serving as a go-to reference for engineers, scientists, or students interested in the subject. The book is divided into three easy-to-navigate sections that thoroughly examine the AI and machine learning-based algorithms and pseudocode considered in this study. This is the most comprehensive and up-to-date encyclopedia of forecasting in renewable power generation, demand response, and electricity pricing ever written, and is a must-have for any library.