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The transition to 100% renewable energy in the future is one of the most important ways of achieving "carbon peaking and carbon neutrality" and of reducing the adverse effects of climate change. In this process, the safe, stable and economical operation of renewable energy generation systems, represented by hydro-, wind and solar power, is particularly important, and has naturally become a key concern for researchers and engineers. Therefore, this book focuses on the fundamental and applied research on the modeling, control, monitoring and diagnosis of renewable energy generation systems, especially hydropower energy systems, and aims to provide some theoretical reference for researchers, power generation departments or government agencies.

Research & information: general --- Physics --- doubly-fed variable-speed pumped storage --- Hopf bifurcation --- stability analysis --- parameter sensitivity --- pumped storage unit --- degradation trend prediction --- maximal information coefficient --- light gradient boosting machine --- variational mode decomposition --- gated recurrent unit --- high proportional renewable power system --- active power --- change point detection --- maximum information coefficient --- cosine similarity --- anomaly detection --- thermal-hydraulic characteristics --- hydraulic oil viscosity --- hydraulic PTO --- wave energy converter --- pumped storage units --- pressure pulsation --- noise reduction --- sparrow search algorithm --- hybrid system --- facility agriculture --- chaotic particle swarms method --- operation strategy --- stochastic dynamic programming (SDP) --- power yield --- seasonal price --- reliability --- cascaded reservoirs --- doubly-fed variable speed pumped storage power station --- nonlinear modeling --- nonlinear pump turbine characteristics --- pumped storage units (PSUs) --- successive start-up --- ‘S’ characteristics --- low water head conditions --- multi-objective optimization --- fractional order PID controller (FOPID) --- hydropower units --- comprehensive deterioration index --- long and short-term neural network --- ensemble empirical mode decomposition --- approximate entropy --- 1D–3D coupling model --- transition stability --- sensitivity analysis --- hydro power

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The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved state-of-the-art applications in many fields, such as computer vision, speech and text processing, medical applications, and IoT (Internet of Things). The probability of a successful outcome from a neural network is linked to selection of an appropriate network architecture and training algorithm. Accordingly, much of the recent research on neural networks has been devoted to the study and proposal of novel architectures, including solutions tailored to specific problems. This book gives significant contributions to the above-mentioned fields by merging theoretical aspects and relevant applications.

Information technology industries --- facial image analysis --- facial nerve paralysis --- deep convolutional neural networks --- image classification --- Chinese text classification --- long short-term memory --- convolutional neural network --- Arabic named entity recognition --- bidirectional recurrent neural network --- GRU --- LSTM --- natural language processing --- word embedding --- CNN --- object detection network --- attention mechanism --- feature fusion --- LSTM-CRF model --- elements recognition --- linguistic features --- POS syntactic rules --- action recognition --- fused features --- 3D convolution neural network --- motion map --- long short-term-memory --- tooth-marked tongue --- gradient-weighted class activation maps --- ship identification --- fully convolutional network --- embedded deep learning --- scalability --- gesture recognition --- human computer interaction --- alternative fusion neural network --- deep learning --- sentiment attention mechanism --- bidirectional gated recurrent unit --- Internet of Things --- convolutional neural networks --- graph partitioning --- distributed systems --- resource-efficient inference --- pedestrian attribute recognition --- graph convolutional network --- multi-label learning --- autoencoders --- long-short-term memory networks --- convolution neural Networks --- object recognition --- sentiment analysis --- text recognition --- IoT (Internet of Thing) systems --- medical applications

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The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved state-of-the-art applications in many fields, such as computer vision, speech and text processing, medical applications, and IoT (Internet of Things). The probability of a successful outcome from a neural network is linked to selection of an appropriate network architecture and training algorithm. Accordingly, much of the recent research on neural networks has been devoted to the study and proposal of novel architectures, including solutions tailored to specific problems. This book gives significant contributions to the above-mentioned fields by merging theoretical aspects and relevant applications.

Information technology industries --- facial image analysis --- facial nerve paralysis --- deep convolutional neural networks --- image classification --- Chinese text classification --- long short-term memory --- convolutional neural network --- Arabic named entity recognition --- bidirectional recurrent neural network --- GRU --- LSTM --- natural language processing --- word embedding --- CNN --- object detection network --- attention mechanism --- feature fusion --- LSTM-CRF model --- elements recognition --- linguistic features --- POS syntactic rules --- action recognition --- fused features --- 3D convolution neural network --- motion map --- long short-term-memory --- tooth-marked tongue --- gradient-weighted class activation maps --- ship identification --- fully convolutional network --- embedded deep learning --- scalability --- gesture recognition --- human computer interaction --- alternative fusion neural network --- deep learning --- sentiment attention mechanism --- bidirectional gated recurrent unit --- Internet of Things --- convolutional neural networks --- graph partitioning --- distributed systems --- resource-efficient inference --- pedestrian attribute recognition --- graph convolutional network --- multi-label learning --- autoencoders --- long-short-term memory networks --- convolution neural Networks --- object recognition --- sentiment analysis --- text recognition --- IoT (Internet of Thing) systems --- medical applications --- facial image analysis --- facial nerve paralysis --- deep convolutional neural networks --- image classification --- Chinese text classification --- long short-term memory --- convolutional neural network --- Arabic named entity recognition --- bidirectional recurrent neural network --- GRU --- LSTM --- natural language processing --- word embedding --- CNN --- object detection network --- attention mechanism --- feature fusion --- LSTM-CRF model --- elements recognition --- linguistic features --- POS syntactic rules --- action recognition --- fused features --- 3D convolution neural network --- motion map --- long short-term-memory --- tooth-marked tongue --- gradient-weighted class activation maps --- ship identification --- fully convolutional network --- embedded deep learning --- scalability --- gesture recognition --- human computer interaction --- alternative fusion neural network --- deep learning --- sentiment attention mechanism --- bidirectional gated recurrent unit --- Internet of Things --- convolutional neural networks --- graph partitioning --- distributed systems --- resource-efficient inference --- pedestrian attribute recognition --- graph convolutional network --- multi-label learning --- autoencoders --- long-short-term memory networks --- convolution neural Networks --- object recognition --- sentiment analysis --- text recognition --- IoT (Internet of Thing) systems --- medical applications

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This book offers a compilation for experts, scholars, and researchers to present the most recent advancements, from theoretical methods to the applications of sophisticated fault diagnosis techniques. The deep learning methods for analyzing and testing complex mechanical systems are of particular interest. Special attention is given to the representation and analysis of system information, operating condition monitoring, the establishment of technical standards, and scientific support of machinery fault diagnosis.

Technology: general issues --- History of engineering & technology --- process monitoring --- dynamics --- variable time lag --- dynamic autoregressive latent variables model --- sintering process --- hammerstein output-error systems --- auxiliary model --- multi-innovation identification theory --- fractional-order calculus theory --- canonical variate analysis --- disturbance detection --- power transmission system --- k-nearest neighbor analysis --- statistical local analysis --- intelligent fault diagnosis --- stacked pruning sparse denoising autoencoder --- convolutional neural network --- anti-noise --- flywheel fault diagnosis --- belief rule base --- fuzzy fault tree analysis --- Bayesian network --- evidential reasoning --- aluminum reduction process --- alumina concentration --- subspace identification --- distributed predictive control --- spatiotemporal feature fusion --- gated recurrent unit --- attention mechanism --- fault diagnosis --- evidential reasoning rule --- system modelling --- information transformation --- parameter optimization --- event-triggered control --- interval type-2 Takagi–Sugeno fuzzy model --- nonlinear networked systems --- filter --- gearbox fault diagnosis --- convolution fusion --- state identification --- PSO --- wavelet mutation --- LSSVM --- data-driven --- operational optimization --- case-based reasoning --- local outlier factor --- abnormal case removal --- bearing fault detection --- deep residual network --- data augmentation --- canonical correlation analysis --- just-in-time learning --- fault detection --- high-speed trains --- autonomous underwater vehicle --- thruster fault diagnostics --- fault tolerant control --- robust optimization --- ocean currents --- n/a --- interval type-2 Takagi-Sugeno fuzzy model

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The Special Issue presents almost 40 papers on recent research in modeling of pyrometallurgical systems, including physical models, first-principles models, detailed CFD and DEM models as well as statistical models or models based on machine learning. The models cover the whole production chain from raw materials processing through the reduction and conversion unit processes to ladle treatment, casting, and rolling. The papers illustrate how models can be used for shedding light on complex and inaccessible processes characterized by high temperatures and hostile environment, in order to improve process performance, product quality, or yield and to reduce the requirements of virgin raw materials and to suppress harmful emissions.

steelmaking --- oxygen consumption --- GPR --- prediction model --- secondary refining --- water model --- mixing time --- slag entrapment --- stainless steel slag --- heating time --- Cr2O3 --- spinel --- crystal size --- processing maps --- nickel-based alloy --- flow behavior --- arrhenius equation --- hearth --- drainage --- PCA --- analysis tool --- pattern --- tapholes --- blast furnace --- coke --- carbon solution loss --- numerical simulation --- pellet pile --- Discrete Element Method --- porosity distribution --- angle of repose --- coordination number --- bubble motion --- interfacial phenomena --- entrainment --- moving path --- arsenopyrite --- arsenic removal --- mechanism --- roasting --- arsenate --- dust ash --- arsenic recovery --- titanium distribution ratio --- thermodynamic model --- ion–molecule coexistence theory --- LF refining slags --- electric arc furnace --- simulation --- process model --- COREX --- raceway zone --- gas flow --- COREX melter gasifier --- mixed charging --- burden layer structure --- burden pile width --- DEM --- burden distribution --- particle flow --- validation --- tire cord steel --- TiN inclusion --- solidification --- segregation models --- hot rolling --- TOU electricity pricing --- hot rolling planning --- genetic algorithm --- C-H2 smelting reduction furnace --- double-row side nozzles --- dimensional analysis --- multiple linear regression --- ironmaking blast furnace --- coke bed --- trickle flow --- molten slag --- liquid iron --- SPH --- charging system --- mathematical model --- radar data --- main trough --- transient fluid of hot metal and molten slag --- wall shear stress --- conjugate heat transfer --- refractory --- shape rolling --- flat rolling --- wire rod --- temperature distribution --- machine learning --- artificial intelligence --- neural network --- BOS reactor --- copper smelting --- SKS --- Shuikoushan process --- oxygen bottom blown --- gated recurrent unit --- support vector data description --- time sequence prediction --- fault detection and identification --- Lignite --- microwave and ultrasound modification --- structural characterization --- 3D molecular model --- structural simulation --- coke combustion rate --- charcoal combustion rate --- iron ore sintering process --- biomass --- quasi-particle --- quasi-particle structure --- monomer blended fuel --- quasi-particle fuel --- apparent activation energy --- coupling effect --- dynamic model --- basic oxygen furnace --- computational fluid dynamics --- CFD–DEM --- coalescence --- settling --- funneling flow --- horizontal single belt casting process (HSBC) --- computational fluid dynamics (CFD) --- double impingement feeding system --- supersonic coherent jet --- decarburization --- steel refining --- EAF --- CFD --- mass transfer coefficient --- physical modeling --- mathematical modeling --- kinetic models --- natural gas --- fuel injection --- combustion --- RAFT --- roll design --- flat-rolled wire --- strain inhomogeneity --- normal pressure --- macroscopic shear bands --- numerical model --- dual gas injection --- slag eye --- electrical energy consumption --- Electric Arc Furnace --- scrap melting --- statistical modeling --- raceway evolution --- raceway size --- flow pattern --- Eulerian multiphase flow --- blast furnace hearth --- dead man --- iron and slag flow --- lining wear --- hearth drainage --- Industry 4.0 --- copper smelter --- nickel-copper smelter --- radiometric sensors --- Peirce-smith converting --- matte-slag chemistry --- discrete event simulation --- adaptive finite differences --- n/a --- ion-molecule coexistence theory --- CFD-DEM