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Recent advances in artificial intelligence have the potential to further develop current big data research. The Special Issue on ‘Intelligent Computing for Big Data’ highlighted a number of recent studies related to the use of intelligent computing techniques in the processing of big data for text mining, autism diagnosis, behaviour recognition, and blockchain-based storage.
Information technology industries --- Computer science --- multimodal data --- behavior recognition --- dog detection --- fusion model --- deep learning --- older people --- long-term care --- artificial intelligence --- blockchain technology --- decentralized architecture --- autism spectrum disorder (ASD) --- big data --- bioinformatics --- machine learning --- classification --- bio-inspired algorithms --- Grey Wolf Optimization (GWO) --- Support Vector Machine (SVM) --- convolution neural network --- spatio-temporal document --- document classification --- big text data --- proxy re-encryption --- blockchain --- storage --- proof-of-replication --- n/a
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The present book contains the 10 articles finally accepted for publication in the Special Issue “Computational Optimizations for Machine Learning” of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity.
ARIMA model --- time series analysis --- online optimization --- online model selection --- precipitation nowcasting --- deep learning --- autoencoders --- radar data --- generalization error --- recurrent neural networks --- machine learning --- model predictive control --- nonlinear systems --- neural networks --- low power --- quantization --- CNN architecture --- multi-objective optimization --- genetic algorithms --- evolutionary computation --- swarm intelligence --- Heating, Ventilation and Air Conditioning (HVAC) --- metaheuristics search --- bio-inspired algorithms --- smart building --- soft computing --- training --- evolution of weights --- artificial intelligence --- deep neural networks --- convolutional neural network --- deep compression --- DNN --- ReLU --- floating-point numbers --- hardware acceleration --- energy dissipation --- FLOW-3D --- hydraulic jumps --- bed roughness --- sensitivity analysis --- feature selection --- evolutionary algorithms --- nature inspired algorithms --- meta-heuristic optimization --- computational intelligence
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The present book contains the 10 articles finally accepted for publication in the Special Issue “Computational Optimizations for Machine Learning” of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity.
Research & information: general --- Mathematics & science --- ARIMA model --- time series analysis --- online optimization --- online model selection --- precipitation nowcasting --- deep learning --- autoencoders --- radar data --- generalization error --- recurrent neural networks --- machine learning --- model predictive control --- nonlinear systems --- neural networks --- low power --- quantization --- CNN architecture --- multi-objective optimization --- genetic algorithms --- evolutionary computation --- swarm intelligence --- Heating, Ventilation and Air Conditioning (HVAC) --- metaheuristics search --- bio-inspired algorithms --- smart building --- soft computing --- training --- evolution of weights --- artificial intelligence --- deep neural networks --- convolutional neural network --- deep compression --- DNN --- ReLU --- floating-point numbers --- hardware acceleration --- energy dissipation --- FLOW-3D --- hydraulic jumps --- bed roughness --- sensitivity analysis --- feature selection --- evolutionary algorithms --- nature inspired algorithms --- meta-heuristic optimization --- computational intelligence --- ARIMA model --- time series analysis --- online optimization --- online model selection --- precipitation nowcasting --- deep learning --- autoencoders --- radar data --- generalization error --- recurrent neural networks --- machine learning --- model predictive control --- nonlinear systems --- neural networks --- low power --- quantization --- CNN architecture --- multi-objective optimization --- genetic algorithms --- evolutionary computation --- swarm intelligence --- Heating, Ventilation and Air Conditioning (HVAC) --- metaheuristics search --- bio-inspired algorithms --- smart building --- soft computing --- training --- evolution of weights --- artificial intelligence --- deep neural networks --- convolutional neural network --- deep compression --- DNN --- ReLU --- floating-point numbers --- hardware acceleration --- energy dissipation --- FLOW-3D --- hydraulic jumps --- bed roughness --- sensitivity analysis --- feature selection --- evolutionary algorithms --- nature inspired algorithms --- meta-heuristic optimization --- computational intelligence
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This reprint presents various aspects of the future grid, which is the next generation of the electrical grid and will enable the smart integration of conventional, renewable, and distributed power generation, energy storage, transmission and distribution, and demand management. Renewable energy is crucial in transitioning to a less carbon-intensive economy and a more sustainable energy system. The high penetration and uncertain power outputs of renewable energy pose great challenges to the stable operation of energy systems. The deployment of the smart grid is revolutionary, and also imperative around the world. It involves and deals with multidisciplinary fields such as energy sources, control systems, communications, computational generation, transmission, distribution, customer operations, markets, and service providers. Smart grids are emerging in both developed and developing countries, with the aim of achieving a reliable and secure electricity supply. Smart grids will eventually require standards, policy, and a regulatory framework for successful implementation. This reprint addresses the emerging and advanced green energy technologies for a sustainable and resilient future grid, and provides a platform to enhance interdisciplinary research and share the most recent ideas.
Technology: general issues --- History of engineering & technology --- islanded mode --- microgrid --- decentralized control --- robust tracking --- invariant set --- thermal energy storage --- parabolic dish --- latent heat --- phase change material --- heat transfer fluid --- bio-inspired algorithms --- wireless sensor network --- genetic algorithm --- particle swarm optimization --- advanced metering infrastructure --- blockchain --- Ethereum --- isolated DC–DC converter --- photovoltaics --- LLC resonant converter --- dual-bridge --- wide voltage range --- power optimizer --- coordinated control --- vehicle-to-grid --- primary frequency control --- secondary frequency control --- state of charge --- decentralized --- Simulink model --- dimensionality reduction --- simple linear regression --- multiple linear regression --- polynomial regression --- load forecasting --- VSC (voltage source converter) --- PLL (Phase-Locked Loop) --- weak grid --- small signal stability --- eigenvalues --- demand-side management --- low-power consumer electronic appliances --- low-voltage distribution system --- non-intrusive identification of appliance usage patterns --- power quality --- smart home --- true power factor --- total harmonic distortion --- renewable energy sources --- energy management system --- communication technologies --- microgrid standards --- third-order sliding mode control --- asynchronous generators --- variable speed dual-rotor wind turbine --- direct field-oriented control --- integral-proportional --- transformer --- internal fault currents --- magnetic inrush currents --- extended Kalman filter (EKF) algorithm --- harmonic estimation --- DC microgrid --- fault --- cluster --- DC/DC converter --- fault current limiter (FCL) --- multi-objective --- renewable energy --- profit-based scheduling --- Equilibrium Optimizer --- smart grid --- campus microgrid --- batteries --- prosumer market --- distributed generation --- renewable energy resources --- energy storage system --- distributed energy resources --- demand response --- load clustering techniques --- sizing methodologies --- digital signal processing --- green buildings --- spectral analysis --- spectral kurtosis --- life-cycle cost --- optimal scheduling --- reinforcement learning --- enabling technologies --- energy community --- smart meter --- nanogrid --- platform --- power cloud --- n/a --- isolated DC-DC converter
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This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.
n/a --- Stackelberg game --- MILP --- optimal congestion threshold --- magnetic field mitigation --- simulation --- multi-objective particle swarm optimization --- virtual power plant --- internal defect --- day-ahead load forecasting --- neural network --- modular predictor --- multi-objective particle swarm optimization algorithm --- stochastic optimization --- dragonfly algorithm --- unit commitment --- metaheuristic --- multi-population method (MP) --- optimization --- tabu search --- considerable decomposition --- loss minimization --- active distribution system --- islanded microgrid --- dynamic solving framework --- feature selection --- electric energy costs --- power factor compensation --- dependability --- interactive load --- overhead --- energy internet --- evolutionary computation --- wind power --- developed grew wolf optimizer --- underground --- ETAP --- fuzzy algorithm --- electric vehicles --- Schwarz’s equation --- evolutionary algorithms --- electric power contracts --- congestion management --- optimizing-scenarios method --- building energy management system --- particle encoding method --- ringdown detection --- HOMER software --- DC optimal power flow --- prosumer --- constrained parameter estimation --- distributed generations (DGs) --- strong track filter (STF) --- transient stability --- calibration --- cost minimization --- radiance --- decentralized and collaborative optimization --- hybrid renewable energy system --- renewable energy sources --- rural electrification --- distribution network reconfiguration --- interval variables --- optimization methods --- particle swarm optimization --- hierarchical scheduling --- micro grid --- AC/DC hybrid active distribution --- consensus --- artificial bee colony --- CCHP system --- data center --- support vector machine --- affinity propagation clustering --- extended Kalman filter --- affine arithmetic --- linear discriminant analysis (LDA) --- current margins --- heterogeneous networks --- Cameroon --- hybrid method --- distributed heat-electricity energy management --- discrete wind driven optimization --- fitness function --- cross-entropy --- GenOpt --- wind energy --- demand uncertainty --- UC --- off-design performance --- genetic algorithm --- energy storage --- the biomimetic membrane computing --- power system optimization --- electric vehicle --- power architectures --- economic load dispatch problem (ELD) --- runner-root algorithm (RRA) --- Cable joint --- battery energy storage system --- load curtailment --- integration assessment --- power system unit commitment --- artificial lighting --- power flow --- hybrid membrane computing --- two-point estimation method --- low-voltage networks --- demand bidding --- non-sinusoidal circuits --- energy flow model --- power transfer distribution factors --- sustainability --- HVAC system --- voltage deviation --- street light points --- radial basis function --- energy storage system --- charging/discharging --- power systems --- intelligent scatter search --- MV/LV substation --- optimal power flow --- stochastic state estimation --- eight searching sub-regions --- chaos optimization algorithm (COA) --- mutual information theory --- inter-turn shorted-circuit fault (ISCF) --- C&I particle swarm optimization --- multiobjective optimization --- passive shielding --- sub-Saharan Africa --- micro-phasor measurement unit --- geometric algebra --- bio-inspired algorithms --- adaptive consensus algorithm --- energy management --- PCS efficiency --- multi-stakeholders --- generalized generation distribution factors --- the genetic algorithm based P system --- JAYA algorithm --- thermal probability density --- power optimization --- pumped-hydro energy storage --- smart grid --- two-stage feature selection --- piecewise linear techniques --- photovoltaic --- SOCP relaxations --- switched reluctance machine (SRM) --- optimal reactive power dispatch --- optimal operation --- controllable response --- off-grid --- active shielding --- transformer-fault diagnosis --- IEEE Std. 80-2000 --- principal component analysis --- demand response --- Schwarz's equation
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This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.
n/a --- Stackelberg game --- MILP --- optimal congestion threshold --- magnetic field mitigation --- simulation --- multi-objective particle swarm optimization --- virtual power plant --- internal defect --- day-ahead load forecasting --- neural network --- modular predictor --- multi-objective particle swarm optimization algorithm --- stochastic optimization --- dragonfly algorithm --- unit commitment --- metaheuristic --- multi-population method (MP) --- optimization --- tabu search --- considerable decomposition --- loss minimization --- active distribution system --- islanded microgrid --- dynamic solving framework --- feature selection --- electric energy costs --- power factor compensation --- dependability --- interactive load --- overhead --- energy internet --- evolutionary computation --- wind power --- developed grew wolf optimizer --- underground --- ETAP --- fuzzy algorithm --- electric vehicles --- Schwarz’s equation --- evolutionary algorithms --- electric power contracts --- congestion management --- optimizing-scenarios method --- building energy management system --- particle encoding method --- ringdown detection --- HOMER software --- DC optimal power flow --- prosumer --- constrained parameter estimation --- distributed generations (DGs) --- strong track filter (STF) --- transient stability --- calibration --- cost minimization --- radiance --- decentralized and collaborative optimization --- hybrid renewable energy system --- renewable energy sources --- rural electrification --- distribution network reconfiguration --- interval variables --- optimization methods --- particle swarm optimization --- hierarchical scheduling --- micro grid --- AC/DC hybrid active distribution --- consensus --- artificial bee colony --- CCHP system --- data center --- support vector machine --- affinity propagation clustering --- extended Kalman filter --- affine arithmetic --- linear discriminant analysis (LDA) --- current margins --- heterogeneous networks --- Cameroon --- hybrid method --- distributed heat-electricity energy management --- discrete wind driven optimization --- fitness function --- cross-entropy --- GenOpt --- wind energy --- demand uncertainty --- UC --- off-design performance --- genetic algorithm --- energy storage --- the biomimetic membrane computing --- power system optimization --- electric vehicle --- power architectures --- economic load dispatch problem (ELD) --- runner-root algorithm (RRA) --- Cable joint --- battery energy storage system --- load curtailment --- integration assessment --- power system unit commitment --- artificial lighting --- power flow --- hybrid membrane computing --- two-point estimation method --- low-voltage networks --- demand bidding --- non-sinusoidal circuits --- energy flow model --- power transfer distribution factors --- sustainability --- HVAC system --- voltage deviation --- street light points --- radial basis function --- energy storage system --- charging/discharging --- power systems --- intelligent scatter search --- MV/LV substation --- optimal power flow --- stochastic state estimation --- eight searching sub-regions --- chaos optimization algorithm (COA) --- mutual information theory --- inter-turn shorted-circuit fault (ISCF) --- C&I particle swarm optimization --- multiobjective optimization --- passive shielding --- sub-Saharan Africa --- micro-phasor measurement unit --- geometric algebra --- bio-inspired algorithms --- adaptive consensus algorithm --- energy management --- PCS efficiency --- multi-stakeholders --- generalized generation distribution factors --- the genetic algorithm based P system --- JAYA algorithm --- thermal probability density --- power optimization --- pumped-hydro energy storage --- smart grid --- two-stage feature selection --- piecewise linear techniques --- photovoltaic --- SOCP relaxations --- switched reluctance machine (SRM) --- optimal reactive power dispatch --- optimal operation --- controllable response --- off-grid --- active shielding --- transformer-fault diagnosis --- IEEE Std. 80-2000 --- principal component analysis --- demand response --- Schwarz's equation
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