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  • machine learning  (589)
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  • 1
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    Springer Nature | Springer Nature Switzerland
    Publication Date: 2024-04-14
    Description: This open access book constitutes revised selected papers from the International Workshops held at the 4th International Conference on Process Mining, ICPM 2022, which took place in Bozen-Bolzano, Italy, during October 23–28, 2022. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 42 papers included in this volume were carefully reviewed and selected from 89 submissions. They stem from the following workshops: – 3rd International Workshop on Event Data and Behavioral Analytics (EDBA) – 3rd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) – 3rd International Workshop on Responsible Process Mining (RPM) (previously known as Trust, Privacy and Security Aspects in Process Analytics) – 5th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) – 3rd International Workshop on Streaming Analytics for Process Mining (SA4PM) – 7th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) – 1st International Workshop on Education meets Process Mining (EduPM) – 1st International Workshop on Data Quality and Transformation in Process Mining (DQT-PM)
    Keywords: process mining ; process discovery ; process analytics ; process querying ; conformance checking ; predictive process monitoring ; data science ; knowledge graphs ; event data ; streaming analytics ; machine learning ; deep learning ; business process management ; health informatics ; thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining ; thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJQ Business mathematics and systems ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBH Digital and information technologies: Health and safety aspects
    Language: English
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  • 2
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Mathematical finance plays a vital role in many fields within finance and provides the theories and tools that have been widely used in all areas of finance. Knowledge of mathematics, probability, and statistics is essential to develop finance theories and test their validity through the analysis of empirical, real-world data. For example, mathematics, probability, and statistics could help to develop pricing models for financial assets such as equities, bonds, currencies, and derivative securities.
    Keywords: cluster analysis ; equity index networks ; machine learning ; copulas ; dependence structures ; quotient of random variables ; density functions ; distribution functions ; multi-factor model ; risk factors ; OLS and ridge regression model ; python ; chi-square test ; quantile ; VaR ; quadrangle ; CVaR ; conditional value-at-risk ; expected shortfall ; ES ; superquantile ; deviation ; risk ; error ; regret ; minimization ; CVaR estimation ; regression ; linear regression ; linear programming ; portfolio safeguard ; PSG ; equity option pricing ; factor models ; stochastic volatility ; jumps ; mathematics ; probability ; statistics ; finance ; applications ; investment home bias (IHB) ; bivariate first-degree stochastic dominance (BFSD) ; keeping up with the Joneses (KUJ) ; correlation loving (CL) ; return spillover ; volatility spillover ; optimal weights ; hedge ratios ; US financial crisis ; Chinese stock market crash ; stock price prediction ; auto-regressive integrated moving average ; artificial neural network ; stochastic process-geometric Brownian motion ; financial models ; firm performance ; causality tests ; leverage ; long-term debt ; capital structure ; shock spillover ; thema EDItEUR::W Lifestyle, Hobbies and Leisure::WC Antiques, vintage and collectables::WCF Collecting coins, banknotes, medals and other related items
    Language: English
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  • 3
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Commodity markets have evolved substantially since the early 2000s and have become more financialized. The recent cold war between the U.S.A. and China, the outbreak of COVID-19, and Russia's invasion of Ukraine have caused resource prices to soar, leading to greater volatility in the commodity markets. The volatility of the commodity markets has increased, and at the same time, financial markets such as the stock market, bond market, and foreign exchange market have become unstable. This has increased the linkage between the commodity and financial markets and has led to a great deal of attention being paid to the commodity markets by governments, companies, and investors.This reprint delves into recent developments in the commodity markets and elucidates the multifaceted factors that have shaped their trajectory. It examines how the interwoven dynamics of supply and demand, geopolitics, technology, and financialization have brought about a new era in commodity trading. By providing a comprehensive survey of these developments, we aim to provide insights that will help stakeholders successfully navigate the challenges and opportunities presented by this evolving landscape.
    Keywords: Russia and Ukraine conflict ; commodities ; G7 and BRIC markets ; TVP-VAR ; connectedness ; oil price uncertainty shocks ; international equity markets ; global vector autoregressive model ; arbitrage ; efficiency ; futures ; liquidity ; market integration ; platinum ; COVID-19 ; pandemic ; agriculture ; commodity ; MF-DFA ; high frequency ; asymmetric volatility spillover ; bitcoin ; altcoin ; cryptocurrency ; frequency connectedness ; Bitcoin ; machine learning ; random forest regression ; LSTM ; energy market volatility ; oil price dynamics ; fear index ; Markov-regime switching models ; volatility risk premium (VRP) ; implied and realized volatility ; oil and stock returns ; financialization ; Bermudan commodity options ; multi-layer perceptron ; multi-asset stochastic volatility model ; hybrid forecasting approaches ; two-step forecasting approaches ; gold ; euro ; sentiment analysis ; ARIMA ; wavelet transformation ; seasonal decomposition ; long short-term memory ; random forest ; eXtreme gradient boosting ; stock ; markets ; cycles ; investing ; risk ; returns ; thema EDItEUR::W Lifestyle, Hobbies and Leisure::WC Antiques, vintage and collectables::WCF Collecting coins, banknotes, medals and other related items
    Language: English
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  • 4
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    Springer Nature | Springer Nature Switzerland
    Publication Date: 2024-04-14
    Description: This open access book constitutes selected papers presented during the 30th Irish Conference on Artificial Intelligence and Cognitive Science, held in Munster, Ireland, in December 2022. The 41 presented papers were thoroughly reviewed and selected from the 102 submissions. They are organized in topical sections on ​machine learning, deep learning and applications; responsible and trustworthy artificial intelligence; natural language processing and recommender systems; knowledge representation, reasoning, optimisation and intelligent applications.
    Keywords: information retrieval ; computer vision ; artificial intelligence ; machine learning ; agent systems ; collaborative networks ; neural networks ; image processing ; patter recognition ; neural computing ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYD Systems analysis and design ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications ; thema EDItEUR::U Computing and Information Technology::UK Computer hardware::UKN Network hardware ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYD Systems analysis and design ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications ; thema EDItEUR::U Computing and Information Technology::UK Computer hardware::UKN Network hardware
    Language: English
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  • 5
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    Springer Nature | Springer Nature Switzerland
    Publication Date: 2024-04-14
    Description: This open access book constitutes refereed proceedings of the Third Conference on Silicon Valley Cybersecurity Conference, SVCC 2022, held as virtual event, in August 17–19, 2022. The 8 full papers included in this book were carefully reviewed and selected from 10 submissions. The contributions are divided into the following thematic blocks: Malware Analysis; Blockchain and Smart Contracts; Remote Device Assessment. This is an open access book.
    Keywords: artificial intelligence ; blockchain ; classification ; computer crime ; computer networks ; computer security ; computer systems ; computer vision ; cryptography ; data communication systems ; data security ; distributed computer systems ; distributed ledger ; image analysis ; intrusion detection ; machine learning ; network protocols ; network security ; parallel processing systems ; query languages ; thema EDItEUR::U Computing and Information Technology::UR Computer security ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications ; thema EDItEUR::U Computing and Information Technology::UR Computer security ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications
    Language: English
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  • 6
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields.
    Keywords: fintech ; financial technology ; blockchain ; deep learning ; regtech ; environment ; social sciences ; machine learning ; learning analytics ; student field forecasting ; imbalanced datasets ; explainable machine learning ; intelligent tutoring system ; adversarial machine learning ; transfer learning ; cognitive bias ; stock market ; behavioural finance ; investor’s profile ; Teheran Stock Exchange ; unsupervised learning ; clustering ; big data frameworks ; fault tolerance ; stream processing systems ; distributed frameworks ; Spark ; Hadoop ; Storm ; Samza ; Flink ; comparative analysis ; a survey ; data science ; educational data mining ; supervised learning ; secondary education ; academic performance ; text-to-SQL ; natural language processing ; database ; machine translation ; medical image segmentation ; convolutional neural networks ; SE block ; U-net ; DeepLabV3plus ; cyber-security ; medical services ; cyber-attacks ; data communication ; distributed ledger ; identity management ; RAFT ; HL7 ; electronic health record ; Hyperledger Composer ; cybersecurity ; password security ; browser security ; social media ; ANOVA ; SPSS ; internet of things ; cloud computing ; computational models ; metaheuristics ; phishing detection ; website phishing ; thema EDItEUR::U Computing and Information Technology
    Language: English
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  • 7
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Sports Medicine and Physical Fitness has been a successful Special Issue, which addressed novel topics in any subject related to sports medicine, physical fitness, and human movement. The article collection was able to positively evaluate three systematic reviews, nineteen original articles, and one brief report. These encompassed a broad range of topics ranging from accident kinematics, soccer monitoring, children’s physical evaluation, adapted physical activity, physical evaluation for people with intellectual disabilities, performance analysis in rowers, ultramarathon racers, karateka’s, rugby players, volleyball and basketball players, and cross-fit athletes, and also aspects related to biomechanics, fatigue and injury prevention in racing motorcycle riders, gymnasts, and cyclists.These scientific contributions within the field of Sports Medicine and Physical Fitness broaden the understanding of specific aspects of each analyzed discipline.It has been a pleasure for the Editorial Team to have served the International Journal Of Environmental Research and Public Health.
    Keywords: MotoGP ; video analysis ; collision ; accident ; safety ; disability ; tool ; health ; life span ; physical fitness ; reference values ; muscular strength profile ; quadriceps ; hamstring ; H/Q ratio ; total work ; sprint ; postactivation potentiation ; fixed seat rowing ; performance ; psychology ; odontology ; nutrition ; training ; stress ; running ; type 1 diabetes ; high-intensity interval training ; exercise ; VO2max ; anti-inflammatory ; machine learning ; PCA ; intensive training ; proprioception ; postural sway ; testing ; pacing ; cycling ; time trial ; RPE ; cognitive functions ; aging ; partnered dances ; fall prevention ; physical activity ; water polo ; biomechanics ; force-velocity relationship ; power-velocity relationship ; soccer ; match ; internal load ; external load ; fatigue ; young athletes ; cycling performance ; sport nutrition ; hydration ; PA ; MVPA ; accelerometer ; questionnaire ; children ; athlete ; high-intensity functional training ; cross-training ; functional fitness ; vitamin D ; explosive strength ; overload training ; wrist pain ; injury prevention ; overuse ; sitting position ; modified 505 test ; kinetic variables ; completion time ; foot contact ; predictors ; squat ; bench press ; strength ; speed ; interval training ; continuous training ; heart failure ; meta-analysis ; handgrip ; carpi radialis ; flexor digitorum superficialis ; neuromuscular fatigue ; motorcycle ; recovery ; spike jump ; block jump ; critical threshold ; specialization ; anaerobic power ; peak power ; HIFT, high-intensity functional training ; crossfit ; athletes ; field test ; hypertrophy ; katsu ; low-intensity training ; occlusive exercise ; sarcopenia ; diabetes type 1 ; HIIT ; sleep quality ; exercise motivation ; quality of life ; hypoxia ; hyperoxia ; hyperbaric breathing ; nitric oxide ; vascular reactions ; breathing ; extreme environments ; thema EDItEUR::W Lifestyle, Hobbies and Leisure
    Language: English
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  • 8
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
    Keywords: QA75.5-76.95 ; T58.5-58.64 ; metadata ; image classification ; sensitivity analysis ; ROI detection ; residual learning ; image alignment ; adaptive convolutional kernels ; Hough transform ; class imbalance ; land surface temperature ; inundation mapping ; multiscale representation ; object-based ; convolutional neural networks ; scene classification ; morphological profiles ; hyperedge weight estimation ; hyperparameter sparse representation ; semantic segmentation ; vehicle classification ; flood ; Landsat imagery ; target detection ; multi-sensor ; building damage detection ; optimized kernel minimum noise fraction (OKMNF) ; sea-land segmentation ; nonlinear classification ; land use ; SAR imagery ; anti-noise transfer network ; sub-pixel change detection ; Radon transform ; segmentation ; remote sensing image retrieval ; TensorFlow ; convolutional neural network ; particle swarm optimization ; optical sensors ; machine learning ; mixed pixel ; optical remotely sensed images ; object-based image analysis ; very high resolution images ; single stream optimization ; ship detection ; ice concentration ; online learning ; manifold ranking ; dictionary learning ; urban surface water extraction ; saliency detection ; spatial attraction model (SAM) ; quality assessment ; Fuzzy-GA decision making system ; land cover change ; multi-view canonical correlation analysis ensemble ; land cover ; semantic labeling ; sparse representation ; dimensionality expansion ; speckle filters ; hyperspectral imagery ; fully convolutional network ; infrared image ; Siamese neural network ; Random Forests (RF) ; feature matching ; color matching ; geostationary satellite remote sensing image ; change feature analysis ; road detection ; deep learning ; aerial images ; image segmentation ; aerial image ; multi-sensor image matching ; HJ-1A/B CCD ; endmember extraction ; high resolution ; multi-scale clustering ; heterogeneous domain adaptation ; hard classification ; regional land cover ; hypergraph learning ; automatic cluster number determination ; dilated convolution ; MSER ; semi-supervised learning ; gate ; Synthetic Aperture Radar (SAR) ; downscaling ; conditional random fields ; urban heat island ; hyperspectral image ; remote sensing image correction ; skip connection ; ISPRS ; spatial distribution ; geo-referencing ; Support Vector Machine (SVM) ; very high resolution (VHR) satellite image ; classification ; ensemble learning ; synthetic aperture radar ; conservation ; convolutional neural network (CNN) ; THEOS ; visible light and infrared integrated camera ; vehicle localization ; structured sparsity ; texture analysis ; DSFATN ; CNN ; image registration ; UAV ; unsupervised classification ; SVMs ; SAR image ; fuzzy neural network ; dimensionality reduction ; GeoEye-1 ; feature extraction ; sub-pixel ; energy distribution optimizing ; saliency analysis ; deep convolutional neural networks ; sparse and low-rank graph ; hyperspectral remote sensing ; tensor low-rank approximation ; optimal transport ; SELF ; spatiotemporal context learning ; Modest AdaBoost ; topic modelling ; multi-seasonal ; Segment-Tree Filtering ; locality information ; GF-4 PMS ; image fusion ; wavelet transform ; hashing ; machine learning techniques ; satellite images ; climate change ; road segmentation ; remote sensing ; tensor sparse decomposition ; Convolutional Neural Network (CNN) ; multi-task learning ; deep salient feature ; speckle ; canonical correlation weighted voting ; fully convolutional network (FCN) ; despeckling ; multispectral imagery ; ratio images ; linear spectral unmixing ; hyperspectral image classification ; multispectral images ; high resolution image ; multi-objective ; convolution neural network ; transfer learning ; 1-dimensional (1-D) ; threshold stability ; Landsat ; kernel method ; phase congruency ; subpixel mapping (SPM) ; tensor ; MODIS ; GSHHG database ; compressive sensing ; thema EDItEUR::U Computing and Information Technology::UY Computer science
    Language: English
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  • 9
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-14
    Description: Despite being one of the most popular sports worldwide, basketball has received limited research attention compared to other team sports. Establishing a strong evidence base with high-quality and impactful research is essential in enhancing decision-making processes to optimize player performance for basketball professionals. Consequently, the book entitled Improving Performance and Practice in Basketball provides a collection of novel research studies to increase the available evidence on various topics with strong translation to practice in basketball. The book includes work by 40 researchers from 16 institutions or professional organizations from 9 countries. In keeping with notable topics in basketball research, the book contains 2 reviews focused on monitoring strategies to detect player fatigue and considerations for travel in National Basketball Association players. In addition, 8 applied studies are also included in the book, focused on workload monitoring, game-related statistics, and the measurement of physical and skill attributes in basketball players. This book also has a strong focus on increasing the evidence available for female basketball players, who have traditionally been under-represented in the literature. The outcomes generated from this book should provide new insights to inform practice in many areas for professionals working in various roles with basketball teams.
    Keywords: GV557-1198.995 ; n/a ; talent selection ; classification tree ; Movement Assessment Battery for Children-2 ; NBA ; basketball ; maturation ; body composition ; fatigue ; countermovement jump ; athletic performance ; circadian rhythm ; injury ; basketball tactics ; female ; athlete ; non-linear analysis ; monitoring ; basketball performance ; performance analysis ; training load ; variability ; game-related statistics ; sleep ; youth athletes ; accelerometer ; women athletes ; fat free mass ; collegiate athletes ; workloads ; team sports ; machine learning ; microtechnology ; motor manual sequences ; elite sport ; attention ; visuo-spatial working memory ; playing position ; smallest worthwhile change ; body fat ; thema EDItEUR::V Health, Relationships and Personal development::VX Mind, body, spirit::VXH Complementary therapies, healing and health::VXHT Traditional medicine and herbal remedies
    Language: English
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  • 10
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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries.
    Keywords: virtual power plant (VPP) ; power quality (PQ) ; global index ; distributed energy resources (DER) ; energy storage systems (ESS) ; power systems ; long-term assessment ; battery energy storage systems (BESS) ; smart grids ; conducted disturbances ; power quality ; supraharmonics ; 2–150 kHz ; Power Line Communications (PLC) ; intentional emission ; non-intentional emission ; mains signalling ; virtual power plant ; data mining ; clustering ; distributed energy resources ; energy storage systems ; short term conditions ; cluster analysis (CA) ; nonlinear loads ; harmonics, cancellation, and attenuation of harmonics ; waveform distortion ; THDi ; low-voltage networks ; optimization techniques ; different batteries ; off-grid microgrid ; integrated renewable energy system ; cluster analysis ; K-means ; agglomerative ; ANFIS ; fuzzy logic ; induction generator ; MPPT ; neural network ; renewable energy ; variable speed WECS ; wind energy conversion system ; wind energy ; frequency estimation ; spectrum interpolation ; power network disturbances ; COVID-19 ; time-varying reproduction number ; social distancing ; load profile ; demographic characteristic ; household energy consumption ; demand-side management ; energy management ; time series ; Hidden Markov Model ; short-term forecast ; sparse signal decomposition ; supervised dictionary learning ; dictionary impulsion ; singular value decomposition ; discrete cosine transform ; discrete Haar transform ; discrete wavelet transform ; transient stability assessment ; home energy management ; binary-coded genetic algorithms ; optimal power scheduling ; demand response ; Data Injection Attack ; machine learning ; critical infrastructure ; smart grid ; water treatment plant ; power system ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities
    Language: English
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