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Nonextensive Entropy Econometrics for Low Frequency Series provides a new and robust powerlawbased, nonextensive entropy econometrics approach to the economic modelling of illbehaved inverse problems. Particular attention is paid to national accountbased general equilibrium models known for their relative complexity.In theoretical terms, the approach generalizes GibbsShannonGolan entropy models, which are useful for describing ergodic phenomena. In essence, this entropy econometrics approach constitutes a junction of two distinct concepts: Jayne’s maximum entropy principle and the Bayesian generalized method of moments. Rival econometric techniques are not conceptually adapted to solving complex inverse problems or are seriously limited when it comes to practical implementation. Recent literature showed that amplitude and frequency of macroeconomic fluctuations do not substantially diverge from many other extreme events, natural or humanrelated, once they are explained in the same time (or space) scale. Nonextensive entropy is a precious device for econometric modelling even in the case of low frequency series, since outputs evolving within the Gaussian attractor correspond to the Tsallis entropy limiting case of Tsallis qparameter around unity. This book introduces a subdiscipline called Nonextensive Entropy Econometrics or, using a recent expression, Superstar Generalised Econometrics. It demonstrates, using national accountsbased models, that this approach facilitates solving nonlinear, complex inverse problems, previously considered intractable, such as the constant elasticity of substitution class of functions. This new proposed approach could extend the frontier of theoretical and applied econometrics.
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Entropy theory has wide applications to a range of problems in the fields of environmental and water engineering, including river hydraulic geometry, fluvial hydraulics, water monitoring network design, river flow forecasting, floods and droughts, river network analysis, infiltration, soil moisture, sediment transport, surface water and groundwater quality modeling, ecosystems modeling, water distribution networks, environmental and water resources management, and parameter estimation. Such applications have used several different entropy formulations, such as Shannon, Tsallis, Reacutenyi Burg, Kolmogorov, Kapur, configurational, and relative entropies, which can be derived in time, space, or frequency domains. More recently, entropybased concepts have been coupled with other theories, including copula and wavelets, to study various issues associated with environmental and water resources systems. Recent studies indicate the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering, including establishing and explaining physical connections between theory and reality. The objective of this Special Issue is to provide a platform for compiling important recent and current research on the applications of entropy theory in environmental and water engineering. The contributions to this Special Issue have addressed many aspects associated with entropy theory applications and have shown the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering.
complexity  streamflow  water level  composite multiscale sample entropy  trend  Poyang Lake basin  fourparameter exponential gamma distribution  principle of maximum entropy  precipitation frequency analysis  methods of moments  maximum likelihood estimation  flood frequency analysis  generalized gamma (GG) distribution  principle of maximum entropy (POME)  entropy theory  principle of maximum entropy (POME)  GB2 distribution  flood frequency analysis  nonpoint source pollution  ANN  entropy weighting method  datascarce  multievents  spatiotemporal variability  soil water content  entropy  arid region  joint entropy  NDVI  temperature  precipitation  groundwater depth  Hei River basin  turbulent flow  canopy flow  randomness  coherent structures  Shannon entropy  Kolmogorov complexity  entropy  information transfer  optimization  radar  rainfall network  water resource carrying capacity  forewarning model  entropy of information  fuzzy analytic hierarchy process  projection pursuit  accelerating genetic algorithm  entropy production  conditional entropy production  stochastic processes  scaling  climacogram  turbulence  water resources vulnerability  connection entropy  changing environment  set pair analysis  Anhui Province  crossentropy minimization  land suitability evaluation  spatial optimization  monthly streamflow forecasting  Burg entropy  configurational entropy  entropy spectral analysis time series analysis  entropy  water monitoring  network design  hydrometric network  information theory  entropy applications  hydrological risk analysis  maximum entropycopula method  uncertainty  Loess Plateau  entropy  water engineering  Tsallis entropy  principle of maximum entropy  Lagrangian function  probability distribution function  flux concentration relation  uncertainty  information  informational entropy  variation of information  continuous probability distribution functions  confidence intervals  precipitation  variability  marginal entropy  crop yield  Hexi corridor  flow duration curve  Shannon entropy  entropy parameter  modeling  spatial and dynamics characteristic  hydrology  tropical rainfall  statistical scaling  Tsallis entropy  multiplicative cascades  BetaLognormal model  rainfall forecast  cross entropy  ant colony fuzzy clustering  combined forecast  information entropy  mutual information  kernel density estimation  ENSO  nonlinear relation  scaling laws  power laws  water distribution networks  robustness  flow entropy  entropy theory  frequency analysis  hydrometeorological extremes  Bayesian technique  rainfall  entropy ensemble filter  ensemble model simulation criterion  EEF method  bootstrap aggregating  bagging  bootstrap neural networks  El Niño  ENSO  neural network forecast  sea surface temperature  tropical Pacific  entropy  cross elasticity  mean annual runoff  water resources  resilience  quaternary catchment  complement  substitute  entropy theory  complex systems  hydraulics  hydrology  water engineering  environmental engineering
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Entropies and entropylike quantities play an increasing role in modern nonlinear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropybased coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.
experiment of design  empirical mode decomposition  signal analysis  similarity indices  synchronization analysis  auditory attention  entropy measure  linear discriminant analysis (LDA)  support vector machine (SVM)  auditory attention classifier  electroencephalography (EEG)  vague entropy  distance induced vague entropy  distance  complex fuzzy set  complex vague soft set  entropy, entropy visualization  entropy balance equation  Shannontype relations  multivariate analysis  machine learning evaluation  data transformation  sample entropy  treadmill walking  center of pressure displacement  dualtasking  analog circuit  fault diagnosis  cross wavelet transform  Tsallis entropy  parametric tdistributed stochastic neighbor embedding  support vector machine  information transfer  Chinese stock sectors  effective transfer entropy  market crash  system coupling  crossvisibility graphs  image entropy  geodesic distance  DempsterShafer evidence theory  uncertainty of basic probability assignment  belief entropy  plausibility transformation  weighted Hartley entropy  Shannon entropy  learning  information  novelty detection  nonprobabilistic entropy  learning systems  permutation entropy  embedded dimension  short time records  signal classification  relevance analysis  global optimization  metaheuristic  firefly algorithm  crossentropy method  coevolution  symbolic analysis  ordinal patterns  Permutation entropy  conditional entropy of ordinal patterns  KolmogorovSinai entropy  algorithmic complexity  information entropy  particle size distribution  selfsimilar measure  simulation  data analysis  entropy  entropy measures  automatic learning
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Image analysis is a fundamental task for extracting information from images acquired across a range of different devices. Since reliable quantitative results are requested, image analysis requires highly sophisticated numerical and analytical methods—particularly for applications in medicine, security, and remote sensing, where the results of the processing may consist of vitally important data. The contributions to this book provide a good overview of the most important demands and solutions concerning this research area. In particular, the reader will find image analysis applied for feature extraction, encryption and decryption of data, color segmentation, and in the support new technologies. In all the contributions, entropy plays a pivotal role.
image retrieval  multifeature fusion  entropy  relevance feedback  chaotic system  image encryption  permutationdiffusion  SHA256 hash value  dynamic index  entropy  keyframes  Shannon’s entropy  sign languages  video summarization  video skimming  image encryption  multipleimage encryption  twodimensional chaotic economic map  security analysis  image encryption  chaotic cryptography  cryptanalysis  chosenplaintext attack  image information entropy  blind image quality assessment (BIQA)  information entropy, natural scene statistics (NSS)  Weibull statistics  discrete cosine transform (DCT)  ultrasound  hepatic steatosis  Shannon entropy  fatty liver  metabolic syndrome  multiexposure image fusion  texture information entropy  adaptive selection  patch structure decomposition  image encryption  timedelay  random insertion  information entropy  chaotic map  uncertainty assessment  deep neural network  random forest  Shannon entropy  positron emission tomography  reconstruction  field of experts  additive manufacturing  3D prints  3D scanning  image entropy  depth maps  surface quality assessment  machine vision  image analysis  Arimoto entropy  freeform deformations  normalized divergence measure  gradient distributions  nonextensive entropy  nonrigid registration  pavement  macrotexture  3D digital imaging  entropy  decay trend  discrete entropy  infrared images  low contrast  multiscale tophat transform  image encryption  DNA encoding  chaotic cryptography  cryptanalysis  image privacy  computer aided diagnostics  colonoscopy  Rényi entropies  structural entropy  spatial filling factor  binary image  Cantor set  Hénon map  Minkowski island  primeindexed primes  Ramanujan primes  Kapur’s entropy  color image segmentation  whale optimization algorithm  differential evolution  hybrid algorithm  Otsu method  image encryption  dynamic filtering  DNA computing  3D Latin cube  permutation  diffusion  fuzzy entropy  electromagnetic field optimization  chaotic strategy  color image segmentation  multilevel thresholding  contrast enhancement  sigmoid  Tsallis statistics  qexponential  qsigmoid  qGaussian  ultrasound images  person reidentification  image analysis  hash layer  quantization loss  Hamming distance  crossentropy loss  image entropy  Shannon entropy  generalized entropies  image processing  image segmentation  medical imaging  remote sensing  security
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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 MixedInteger Programming to the most modern methods based on bioinspired 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.
Cable joint  internal defect  thermal probability density  power system optimization  optimal power flow  developed grew wolf optimizer  energy internet  prosumer  energy management  consensus  demand response  dayahead load forecasting  modular predictor  feature selection  microphasor measurement unit  mutual information theory  stochastic state estimation  twopoint estimation method  JAYA algorithm  multipopulation method (MP)  chaos optimization algorithm (COA)  economic load dispatch problem (ELD)  optimization methods  constrained parameter estimation  extended Kalman filter  power systems  C&I particle swarm optimization  ringdown detection  optimal reactive power dispatch  loss minimization  voltage deviation  hybrid method  tabu search  particle swarm optimization  artificial lighting  simulation  calibration  radiance  GenOpt  street light points  DC optimal power flow  power transfer distribution factors  generalized generation distribution factors  unit commitment  adaptive consensus algorithm  distributed heatelectricity energy management  eight searching subregions  islanded microgrid  dragonfly algorithm  metaheuristic  optimal power flow  particle swarm optimization  CCHP system  energy storage  offdesign performance  dynamic solving framework  battery energy storage system  micro grid  MILP  PCS efficiency  piecewise linear techniques  renewable energy sources  optimal operation  UC  demand bidding  demand response  genetic algorithm  load curtailment  optimization  hybrid renewable energy system  pumpedhydro energy storage  offgrid  optimization  HOMER software  rural electrification  subSaharan Africa  Cameroon  building energy management system  HVAC system  energy storage system  energy flow model  dependability  sustainability  data center  power architectures  optimization  AC/DC hybrid active distribution  hierarchical scheduling  multistakeholders  discrete wind driven optimization  multiobjective optimization  optimal power flow  metaheuristic  wind energy  photovoltaic  smart grid  transformerfault diagnosis  principal component analysis  particle swarm optimization  support vector machine  wind power  integration assessment  interactive load  considerable decomposition  controllable response  SOCP relaxations  optimal power flow  current margins  affine arithmetic  interval variables  optimizingscenarios method  power flow  wind power  active distribution system  virtual power plant  stochastic optimization  decentralized and collaborative optimization  genetic algorithm  multiobjective particle swarm optimization algorithm  artificial bee colony  IEEE Std. 802000  Schwarz’s equation  fuzzy algorithm  radial basis function  neural network  ETAP  distributed generations (DGs)  distribution network reconfiguration  runnerroot algorithm (RRA)  interturn shortedcircuit fault (ISCF)  strong track filter (STF)  linear discriminant analysis (LDA)  switched reluctance machine (SRM)  charging/discharging  electric vehicle  energy management  genetic algorithm  intelligent scatter search  electric vehicles  heterogeneous networks  demand uncertainty  power optimization  Stackelberg game  power system unit commitment  hybrid membrane computing  crossentropy  the genetic algorithm based P system  the biomimetic membrane computing  transient stability  twostage feature selection  particle encoding method  fitness function  power factor compensation  nonsinusoidal circuits  geometric algebra  evolutionary algorithms  electric power contracts  electric energy costs  cost minimization  evolutionary computation  bioinspired algorithms  congestion management  lowvoltage networks  multiobjective particle swarm optimization  affinity propagation clustering  optimal congestion threshold  optimization  magnetic field mitigation  overhead  underground  passive shielding  active shielding  MV/LV substation  n/a
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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 MixedInteger Programming to the most modern methods based on bioinspired 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.
Cable joint  internal defect  thermal probability density  power system optimization  optimal power flow  developed grew wolf optimizer  energy internet  prosumer  energy management  consensus  demand response  dayahead load forecasting  modular predictor  feature selection  microphasor measurement unit  mutual information theory  stochastic state estimation  twopoint estimation method  JAYA algorithm  multipopulation method (MP)  chaos optimization algorithm (COA)  economic load dispatch problem (ELD)  optimization methods  constrained parameter estimation  extended Kalman filter  power systems  C&I particle swarm optimization  ringdown detection  optimal reactive power dispatch  loss minimization  voltage deviation  hybrid method  tabu search  particle swarm optimization  artificial lighting  simulation  calibration  radiance  GenOpt  street light points  DC optimal power flow  power transfer distribution factors  generalized generation distribution factors  unit commitment  adaptive consensus algorithm  distributed heatelectricity energy management  eight searching subregions  islanded microgrid  dragonfly algorithm  metaheuristic  optimal power flow  particle swarm optimization  CCHP system  energy storage  offdesign performance  dynamic solving framework  battery energy storage system  micro grid  MILP  PCS efficiency  piecewise linear techniques  renewable energy sources  optimal operation  UC  demand bidding  demand response  genetic algorithm  load curtailment  optimization  hybrid renewable energy system  pumpedhydro energy storage  offgrid  optimization  HOMER software  rural electrification  subSaharan Africa  Cameroon  building energy management system  HVAC system  energy storage system  energy flow model  dependability  sustainability  data center  power architectures  optimization  AC/DC hybrid active distribution  hierarchical scheduling  multistakeholders  discrete wind driven optimization  multiobjective optimization  optimal power flow  metaheuristic  wind energy  photovoltaic  smart grid  transformerfault diagnosis  principal component analysis  particle swarm optimization  support vector machine  wind power  integration assessment  interactive load  considerable decomposition  controllable response  SOCP relaxations  optimal power flow  current margins  affine arithmetic  interval variables  optimizingscenarios method  power flow  wind power  active distribution system  virtual power plant  stochastic optimization  decentralized and collaborative optimization  genetic algorithm  multiobjective particle swarm optimization algorithm  artificial bee colony  IEEE Std. 802000  Schwarz’s equation  fuzzy algorithm  radial basis function  neural network  ETAP  distributed generations (DGs)  distribution network reconfiguration  runnerroot algorithm (RRA)  interturn shortedcircuit fault (ISCF)  strong track filter (STF)  linear discriminant analysis (LDA)  switched reluctance machine (SRM)  charging/discharging  electric vehicle  energy management  genetic algorithm  intelligent scatter search  electric vehicles  heterogeneous networks  demand uncertainty  power optimization  Stackelberg game  power system unit commitment  hybrid membrane computing  crossentropy  the genetic algorithm based P system  the biomimetic membrane computing  transient stability  twostage feature selection  particle encoding method  fitness function  power factor compensation  nonsinusoidal circuits  geometric algebra  evolutionary algorithms  electric power contracts  electric energy costs  cost minimization  evolutionary computation  bioinspired algorithms  congestion management  lowvoltage networks  multiobjective particle swarm optimization  affinity propagation clustering  optimal congestion threshold  optimization  magnetic field mitigation  overhead  underground  passive shielding  active shielding  MV/LV substation  n/a
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