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The impacts of climate change on water resource management, as well as increasingly severe natural disasters over the last decades, have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resource management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modeling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modeling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue will not only advance water sciences but also help policymakers to achieve more sustainable and effective water resource management.
Research & information: general --- water resources management --- landslide --- dammed lake --- flood risk --- time-varying parameter --- GR4J model --- changing environments --- temporal transferability --- western China --- cascade hydropower reservoirs --- multi-objective optimization --- TOPSIS --- gravitational search algorithm --- opposition learning --- partial mutation --- elastic-ball modification --- Snowmelt Runoff Model --- parameter uncertainty --- data-scarce deglaciating river basin --- climate change impacts --- generalized likelihood uncertainty estimation --- Yangtze River --- cascade reservoirs --- impoundment operation --- GloFAS-Seasonal --- forecast evaluation --- small and medium-scale rivers --- highly urbanized area --- flood control --- whole region perspective --- coupled models --- flood-risk map --- hydrodynamic modelling --- Sequential Gaussian Simulation --- urban stormwater --- probabilistic forecast --- Unscented Kalman Filter --- artificial neural networks --- Three Gorges Reservoir --- Mahalanobis-Taguchi System --- grey entropy method --- signal-to-noise ratio --- degree of balance and approach --- interval number --- multi-objective optimal operation model --- feasible search space --- Pareto-front optimal solution set --- loss–benefit ratio of ecology and power generation --- elasticity coefficient --- empirical mode decomposition --- Hushan reservoir --- data synthesis --- urban hydrological model --- Generalized Likelihood Uncertainty Estimation (GLUE) --- Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) --- uncertainty analysis --- NDVI --- Yarlung Zangbo River --- machine learning model --- random forest --- Internet of Things (IoT) --- regional flood inundation depth --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- artificial intelligence --- machine learning --- multi-objective reservoir operation --- hydrologic forecasting --- uncertainty --- risk --- water resources management --- landslide --- dammed lake --- flood risk --- time-varying parameter --- GR4J model --- changing environments --- temporal transferability --- western China --- cascade hydropower reservoirs --- multi-objective optimization --- TOPSIS --- gravitational search algorithm --- opposition learning --- partial mutation --- elastic-ball modification --- Snowmelt Runoff Model --- parameter uncertainty --- data-scarce deglaciating river basin --- climate change impacts --- generalized likelihood uncertainty estimation --- Yangtze River --- cascade reservoirs --- impoundment operation --- GloFAS-Seasonal --- forecast evaluation --- small and medium-scale rivers --- highly urbanized area --- flood control --- whole region perspective --- coupled models --- flood-risk map --- hydrodynamic modelling --- Sequential Gaussian Simulation --- urban stormwater --- probabilistic forecast --- Unscented Kalman Filter --- artificial neural networks --- Three Gorges Reservoir --- Mahalanobis-Taguchi System --- grey entropy method --- signal-to-noise ratio --- degree of balance and approach --- interval number --- multi-objective optimal operation model --- feasible search space --- Pareto-front optimal solution set --- loss–benefit ratio of ecology and power generation --- elasticity coefficient --- empirical mode decomposition --- Hushan reservoir --- data synthesis --- urban hydrological model --- Generalized Likelihood Uncertainty Estimation (GLUE) --- Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) --- uncertainty analysis --- NDVI --- Yarlung Zangbo River --- machine learning model --- random forest --- Internet of Things (IoT) --- regional flood inundation depth --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- artificial intelligence --- machine learning --- multi-objective reservoir operation --- hydrologic forecasting --- uncertainty --- risk
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The impacts of climate change on water resource management, as well as increasingly severe natural disasters over the last decades, have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resource management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modeling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modeling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue will not only advance water sciences but also help policymakers to achieve more sustainable and effective water resource management.
Research & information: general --- water resources management --- landslide --- dammed lake --- flood risk --- time-varying parameter --- GR4J model --- changing environments --- temporal transferability --- western China --- cascade hydropower reservoirs --- multi-objective optimization --- TOPSIS --- gravitational search algorithm --- opposition learning --- partial mutation --- elastic-ball modification --- Snowmelt Runoff Model --- parameter uncertainty --- data-scarce deglaciating river basin --- climate change impacts --- generalized likelihood uncertainty estimation --- Yangtze River --- cascade reservoirs --- impoundment operation --- GloFAS-Seasonal --- forecast evaluation --- small and medium-scale rivers --- highly urbanized area --- flood control --- whole region perspective --- coupled models --- flood-risk map --- hydrodynamic modelling --- Sequential Gaussian Simulation --- urban stormwater --- probabilistic forecast --- Unscented Kalman Filter --- artificial neural networks --- Three Gorges Reservoir --- Mahalanobis-Taguchi System --- grey entropy method --- signal-to-noise ratio --- degree of balance and approach --- interval number --- multi-objective optimal operation model --- feasible search space --- Pareto-front optimal solution set --- loss–benefit ratio of ecology and power generation --- elasticity coefficient --- empirical mode decomposition --- Hushan reservoir --- data synthesis --- urban hydrological model --- Generalized Likelihood Uncertainty Estimation (GLUE) --- Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) --- uncertainty analysis --- NDVI --- Yarlung Zangbo River --- machine learning model --- random forest --- Internet of Things (IoT) --- regional flood inundation depth --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- artificial intelligence --- machine learning --- multi-objective reservoir operation --- hydrologic forecasting --- uncertainty --- risk
Choose an application
The impacts of climate change on water resource management, as well as increasingly severe natural disasters over the last decades, have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resource management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modeling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modeling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue will not only advance water sciences but also help policymakers to achieve more sustainable and effective water resource management.
water resources management --- landslide --- dammed lake --- flood risk --- time-varying parameter --- GR4J model --- changing environments --- temporal transferability --- western China --- cascade hydropower reservoirs --- multi-objective optimization --- TOPSIS --- gravitational search algorithm --- opposition learning --- partial mutation --- elastic-ball modification --- Snowmelt Runoff Model --- parameter uncertainty --- data-scarce deglaciating river basin --- climate change impacts --- generalized likelihood uncertainty estimation --- Yangtze River --- cascade reservoirs --- impoundment operation --- GloFAS-Seasonal --- forecast evaluation --- small and medium-scale rivers --- highly urbanized area --- flood control --- whole region perspective --- coupled models --- flood-risk map --- hydrodynamic modelling --- Sequential Gaussian Simulation --- urban stormwater --- probabilistic forecast --- Unscented Kalman Filter --- artificial neural networks --- Three Gorges Reservoir --- Mahalanobis-Taguchi System --- grey entropy method --- signal-to-noise ratio --- degree of balance and approach --- interval number --- multi-objective optimal operation model --- feasible search space --- Pareto-front optimal solution set --- loss–benefit ratio of ecology and power generation --- elasticity coefficient --- empirical mode decomposition --- Hushan reservoir --- data synthesis --- urban hydrological model --- Generalized Likelihood Uncertainty Estimation (GLUE) --- Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) --- uncertainty analysis --- NDVI --- Yarlung Zangbo River --- machine learning model --- random forest --- Internet of Things (IoT) --- regional flood inundation depth --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- artificial intelligence --- machine learning --- multi-objective reservoir operation --- hydrologic forecasting --- uncertainty --- risk
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In recent years, power converters have played an important role in power electronics technology for different applications, such as renewable energy systems, electric vehicles, pulsed power generation, and biomedical sciences. Power converters, in the realm of power electronics, are becoming essential for generating electrical power energy in various ways. This Special Issue focuses on the development of novel power converter topologies in power electronics. The topics of interest include, but are not limited to: Z-source converters; multilevel power converter topologies; switched-capacitor-based power converters; power converters for battery management systems; power converters in wireless power transfer techniques; the reliability of power conversion systems; and modulation techniques for advanced power converters.
History of engineering & technology --- current source converter --- power decoupling --- power ripple --- computational complexity --- direct power control --- finite control set model predictive control --- PI controllers --- space vector modulation --- three-level T-type inverter --- input current ripple --- voltage multiplier --- shoot through state --- quasi-switched boost inverter --- Z-source inverter --- transformerless --- SEPIC converter --- single phase --- cascaded H-bridge inverter --- three-phase inverter --- Z-source network --- quasi-switched-boost network --- shoot-through --- quasi-z-source inverter --- grid-tied --- leakage current --- power efficiency --- counter-based --- one-comparator --- PWFM --- PWM --- PFM --- dc converter --- full bridge converter --- zero voltage operation --- multilevel inverter --- Pulse Width Modulation --- minimal number of commutations --- state machine --- Neutral Point Clamped Converter --- power converters --- EMI --- intelligent control --- classical gate driver --- interference sources --- carrier-based pulse width modulation --- offset function --- switching loss reduction --- H-bridge five-level inverter --- electromagnetic compatibility (EMC) --- switching model power supply (SMPS) --- conducted emission --- parametric modeling method --- vector fitting algorithm --- full-power testing --- high-power --- individual phase --- operation test --- static synchronous compensator (STATCOM) --- bidirectional DC/DC converter (BDC) --- dual mode operation --- current sharing --- multiplexed modulation --- low-voltage and high-current --- Lyapunov algorithm --- current sharing control --- confluence plate --- state feedback linearization --- grid-connected inverter --- LCL filter --- inductive power transfer (IPT) --- three-bridge switching --- constant current (CC) --- constant voltage (CV) --- fixed frequency --- fractional order elements --- high-frequency switching --- wireless power transmission --- active balance circuit --- bi-directional converter --- lithium battery --- series-connected battery --- fast charging --- motor drives --- full-bridge Buck inverter --- DC motor --- mathematical model --- differential flatness --- time-varying duty cycle --- circuit simulation --- experimental validation --- current source inverter --- common-mode voltage --- diode clamped multilevel inverter --- flying capacitor multilevel inverter --- cascade H bridge multilevel inverter --- total harmonic distortion --- PWM control techniques --- PSCAD/MULTISIM simulation --- model predictive control (MPC) --- neutral-point clamped (NPC) inverter --- disturbance observer --- parameter uncertainty --- stability analysis --- power factor adjustment --- matrix rectifier --- peak-current-mode (PCM) control --- boost converter --- stability --- parameter perturbation --- target period orbit tracking --- space-vector pulse-width modulation --- common-mode voltage elimination --- quasi-switched boost --- impedance network --- add-on pulse charger --- quick charge --- pulse charging --- Li-ion battery --- full bridge (FB) --- modular multilevel dc-dc converters (MMDCs) --- zero-voltage switching (ZVS) --- zero-current switching (ZCS) --- Photovoltaics --- Z-Source --- Current-fed --- Medium-Frequency --- Power-Imbalance --- harmonic --- RPWM --- selective voltage harmonic elimination --- single-phase inverter --- n/a
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In recent years, power converters have played an important role in power electronics technology for different applications, such as renewable energy systems, electric vehicles, pulsed power generation, and biomedical sciences. Power converters, in the realm of power electronics, are becoming essential for generating electrical power energy in various ways. This Special Issue focuses on the development of novel power converter topologies in power electronics. The topics of interest include, but are not limited to: Z-source converters; multilevel power converter topologies; switched-capacitor-based power converters; power converters for battery management systems; power converters in wireless power transfer techniques; the reliability of power conversion systems; and modulation techniques for advanced power converters.
current source converter --- power decoupling --- power ripple --- computational complexity --- direct power control --- finite control set model predictive control --- PI controllers --- space vector modulation --- three-level T-type inverter --- input current ripple --- voltage multiplier --- shoot through state --- quasi-switched boost inverter --- Z-source inverter --- transformerless --- SEPIC converter --- single phase --- cascaded H-bridge inverter --- three-phase inverter --- Z-source network --- quasi-switched-boost network --- shoot-through --- quasi-z-source inverter --- grid-tied --- leakage current --- power efficiency --- counter-based --- one-comparator --- PWFM --- PWM --- PFM --- dc converter --- full bridge converter --- zero voltage operation --- multilevel inverter --- Pulse Width Modulation --- minimal number of commutations --- state machine --- Neutral Point Clamped Converter --- power converters --- EMI --- intelligent control --- classical gate driver --- interference sources --- carrier-based pulse width modulation --- offset function --- switching loss reduction --- H-bridge five-level inverter --- electromagnetic compatibility (EMC) --- switching model power supply (SMPS) --- conducted emission --- parametric modeling method --- vector fitting algorithm --- full-power testing --- high-power --- individual phase --- operation test --- static synchronous compensator (STATCOM) --- bidirectional DC/DC converter (BDC) --- dual mode operation --- current sharing --- multiplexed modulation --- low-voltage and high-current --- Lyapunov algorithm --- current sharing control --- confluence plate --- state feedback linearization --- grid-connected inverter --- LCL filter --- inductive power transfer (IPT) --- three-bridge switching --- constant current (CC) --- constant voltage (CV) --- fixed frequency --- fractional order elements --- high-frequency switching --- wireless power transmission --- active balance circuit --- bi-directional converter --- lithium battery --- series-connected battery --- fast charging --- motor drives --- full-bridge Buck inverter --- DC motor --- mathematical model --- differential flatness --- time-varying duty cycle --- circuit simulation --- experimental validation --- current source inverter --- common-mode voltage --- diode clamped multilevel inverter --- flying capacitor multilevel inverter --- cascade H bridge multilevel inverter --- total harmonic distortion --- PWM control techniques --- PSCAD/MULTISIM simulation --- model predictive control (MPC) --- neutral-point clamped (NPC) inverter --- disturbance observer --- parameter uncertainty --- stability analysis --- power factor adjustment --- matrix rectifier --- peak-current-mode (PCM) control --- boost converter --- stability --- parameter perturbation --- target period orbit tracking --- space-vector pulse-width modulation --- common-mode voltage elimination --- quasi-switched boost --- impedance network --- add-on pulse charger --- quick charge --- pulse charging --- Li-ion battery --- full bridge (FB) --- modular multilevel dc-dc converters (MMDCs) --- zero-voltage switching (ZVS) --- zero-current switching (ZCS) --- Photovoltaics --- Z-Source --- Current-fed --- Medium-Frequency --- Power-Imbalance --- harmonic --- RPWM --- selective voltage harmonic elimination --- single-phase inverter --- n/a
Choose an application
In recent years, power converters have played an important role in power electronics technology for different applications, such as renewable energy systems, electric vehicles, pulsed power generation, and biomedical sciences. Power converters, in the realm of power electronics, are becoming essential for generating electrical power energy in various ways. This Special Issue focuses on the development of novel power converter topologies in power electronics. The topics of interest include, but are not limited to: Z-source converters; multilevel power converter topologies; switched-capacitor-based power converters; power converters for battery management systems; power converters in wireless power transfer techniques; the reliability of power conversion systems; and modulation techniques for advanced power converters.
History of engineering & technology --- current source converter --- power decoupling --- power ripple --- computational complexity --- direct power control --- finite control set model predictive control --- PI controllers --- space vector modulation --- three-level T-type inverter --- input current ripple --- voltage multiplier --- shoot through state --- quasi-switched boost inverter --- Z-source inverter --- transformerless --- SEPIC converter --- single phase --- cascaded H-bridge inverter --- three-phase inverter --- Z-source network --- quasi-switched-boost network --- shoot-through --- quasi-z-source inverter --- grid-tied --- leakage current --- power efficiency --- counter-based --- one-comparator --- PWFM --- PWM --- PFM --- dc converter --- full bridge converter --- zero voltage operation --- multilevel inverter --- Pulse Width Modulation --- minimal number of commutations --- state machine --- Neutral Point Clamped Converter --- power converters --- EMI --- intelligent control --- classical gate driver --- interference sources --- carrier-based pulse width modulation --- offset function --- switching loss reduction --- H-bridge five-level inverter --- electromagnetic compatibility (EMC) --- switching model power supply (SMPS) --- conducted emission --- parametric modeling method --- vector fitting algorithm --- full-power testing --- high-power --- individual phase --- operation test --- static synchronous compensator (STATCOM) --- bidirectional DC/DC converter (BDC) --- dual mode operation --- current sharing --- multiplexed modulation --- low-voltage and high-current --- Lyapunov algorithm --- current sharing control --- confluence plate --- state feedback linearization --- grid-connected inverter --- LCL filter --- inductive power transfer (IPT) --- three-bridge switching --- constant current (CC) --- constant voltage (CV) --- fixed frequency --- fractional order elements --- high-frequency switching --- wireless power transmission --- active balance circuit --- bi-directional converter --- lithium battery --- series-connected battery --- fast charging --- motor drives --- full-bridge Buck inverter --- DC motor --- mathematical model --- differential flatness --- time-varying duty cycle --- circuit simulation --- experimental validation --- current source inverter --- common-mode voltage --- diode clamped multilevel inverter --- flying capacitor multilevel inverter --- cascade H bridge multilevel inverter --- total harmonic distortion --- PWM control techniques --- PSCAD/MULTISIM simulation --- model predictive control (MPC) --- neutral-point clamped (NPC) inverter --- disturbance observer --- parameter uncertainty --- stability analysis --- power factor adjustment --- matrix rectifier --- peak-current-mode (PCM) control --- boost converter --- stability --- parameter perturbation --- target period orbit tracking --- space-vector pulse-width modulation --- common-mode voltage elimination --- quasi-switched boost --- impedance network --- add-on pulse charger --- quick charge --- pulse charging --- Li-ion battery --- full bridge (FB) --- modular multilevel dc-dc converters (MMDCs) --- zero-voltage switching (ZVS) --- zero-current switching (ZCS) --- Photovoltaics --- Z-Source --- Current-fed --- Medium-Frequency --- Power-Imbalance --- harmonic --- RPWM --- selective voltage harmonic elimination --- single-phase inverter --- current source converter --- power decoupling --- power ripple --- computational complexity --- direct power control --- finite control set model predictive control --- PI controllers --- space vector modulation --- three-level T-type inverter --- input current ripple --- voltage multiplier --- shoot through state --- quasi-switched boost inverter --- Z-source inverter --- transformerless --- SEPIC converter --- single phase --- cascaded H-bridge inverter --- three-phase inverter --- Z-source network --- quasi-switched-boost network --- shoot-through --- quasi-z-source inverter --- grid-tied --- leakage current --- power efficiency --- counter-based --- one-comparator --- PWFM --- PWM --- PFM --- dc converter --- full bridge converter --- zero voltage operation --- multilevel inverter --- Pulse Width Modulation --- minimal number of commutations --- state machine --- Neutral Point Clamped Converter --- power converters --- EMI --- intelligent control --- classical gate driver --- interference sources --- carrier-based pulse width modulation --- offset function --- switching loss reduction --- H-bridge five-level inverter --- electromagnetic compatibility (EMC) --- switching model power supply (SMPS) --- conducted emission --- parametric modeling method --- vector fitting algorithm --- full-power testing --- high-power --- individual phase --- operation test --- static synchronous compensator (STATCOM) --- bidirectional DC/DC converter (BDC) --- dual mode operation --- current sharing --- multiplexed modulation --- low-voltage and high-current --- Lyapunov algorithm --- current sharing control --- confluence plate --- state feedback linearization --- grid-connected inverter --- LCL filter --- inductive power transfer (IPT) --- three-bridge switching --- constant current (CC) --- constant voltage (CV) --- fixed frequency --- fractional order elements --- high-frequency switching --- wireless power transmission --- active balance circuit --- bi-directional converter --- lithium battery --- series-connected battery --- fast charging --- motor drives --- full-bridge Buck inverter --- DC motor --- mathematical model --- differential flatness --- time-varying duty cycle --- circuit simulation --- experimental validation --- current source inverter --- common-mode voltage --- diode clamped multilevel inverter --- flying capacitor multilevel inverter --- cascade H bridge multilevel inverter --- total harmonic distortion --- PWM control techniques --- PSCAD/MULTISIM simulation --- model predictive control (MPC) --- neutral-point clamped (NPC) inverter --- disturbance observer --- parameter uncertainty --- stability analysis --- power factor adjustment --- matrix rectifier --- peak-current-mode (PCM) control --- boost converter --- stability --- parameter perturbation --- target period orbit tracking --- space-vector pulse-width modulation --- common-mode voltage elimination --- quasi-switched boost --- impedance network --- add-on pulse charger --- quick charge --- pulse charging --- Li-ion battery --- full bridge (FB) --- modular multilevel dc-dc converters (MMDCs) --- zero-voltage switching (ZVS) --- zero-current switching (ZCS) --- Photovoltaics --- Z-Source --- Current-fed --- Medium-Frequency --- Power-Imbalance --- harmonic --- RPWM --- selective voltage harmonic elimination --- single-phase inverter
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