The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of...The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of soil.In order to save computing time during parameter inversion,a new procedure to compute the calculated strains is presented by multi-linear simplification approach instead of finite element method(FEM).The real-coded hybrid genetic algorithm is developed by combining normal genetic algorithm with gradient-based optimization algorithm.The numerical and experimental results for conditioned soil are compared.The forecast strains based on identified nonlinear constitutive model of soil agree well with observed ones.The effectiveness and accuracy of proposed parameter estimation approach are validated.展开更多
Wind-power （WP） estimation is necessary for power system in several operations, which are as the optimal power flow between conventional units and wind farms, generators scheduling, and electricity market bidding. E...Wind-power （WP） estimation is necessary for power system in several operations, which are as the optimal power flow between conventional units and wind farms, generators scheduling, and electricity market bidding. Estimating the output power of a wind energy conversion unit （WEC） mainly bases on the incident wind speed at the unit site by using the power characteristic curve. In addition, several time-series models have been using in wind speed forecasting. These models are characterized with requiring a large set of data. In order to prevent from the wind speed measurement and the need of a precise wind turbine model, an novel method basing on neural network and the grey predictor model GM （1,1） is proposed. Though the method, the estimating model can be built only by using the experimental data, which are obtained from the WP system in laboratory. The effectiveness of the estimating model is confirmed by the simulation results.展开更多
Measurement of the volume of gas adsorbed per unit mass of coal with increasing pressure at a constant temperature produces an isotherm that describes the gas storage capacity of this type of coal. The accurate testin...Measurement of the volume of gas adsorbed per unit mass of coal with increasing pressure at a constant temperature produces an isotherm that describes the gas storage capacity of this type of coal. The accurate testing and interpretation of coal sorption isotherm plays an important role in the areas of coal mine methane drainage, coalbed methane （CBM） reservoir resource assessment, enhanced coalbed methane （ECBM） recovery, as well as the carbon dioxide （CO2） sequestration in deep coal seams or similar geological formations. Different coal sorption isotherm testing apparatus and associated calculation methods are critically reviewed and presented in this paper. These include both volumetric and gravimetric based methods, as well as experimental sorption tests with confining stress and direction sorption methods. The volumetric techniques utilise experimental apparatus with sample cell and injection pump and that with both sample cell and reference cell. Whilst the gravimetric approachesinclude methods with sample cell and suspension magnetic balance and that with both sample cell and reference cell. Different testing methods are compared and discussed in this study. A unique in-house-built coal sorption isotherm testing apparatus at the University of Wollongong was presented together with the calculation method, procedures and experimental results. The isotherm results can be calculated by both Soave-Redlich-Kwong （SRK） equation and calibration cure methods which can be used directly to convert the volume of adsorbed gas in different test conditions to standard condition （NTP）.展开更多
This paper present a simulation study of an evolutionary algorithms, Particle Swarm Optimization PSO algorithm to optimize likelihood function of ARMA（1, 1） model, where maximizing likelihood function is equivalent ...This paper present a simulation study of an evolutionary algorithms, Particle Swarm Optimization PSO algorithm to optimize likelihood function of ARMA（1, 1） model, where maximizing likelihood function is equivalent to maximizing its logarithm, so the objective function ＇obj.fun＇ is maximizing log-likelihood function. Monte Carlo method adapted for implementing and designing the experiments of this simulation. This study including a comparison among three versions of PSO algorithm “Constriction coefficient CCPSO, Inertia weight IWPSO, and Fully Informed FIPSO”, the experiments designed by setting different values of model parameters al, bs sample size n, moreover the parameters of PSO algorithms. MSE used as test statistic to measure the efficiency PSO to estimate model. The results show the ability of PSO to estimate ARMA＇ s parameters, and the minimum values of MSE getting for COPSO.展开更多
基金Project(2007CB714006) supported by the National Basic Research Program of China Project(90815023) supported by the National Natural Science Foundation of China
文摘The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of soil.In order to save computing time during parameter inversion,a new procedure to compute the calculated strains is presented by multi-linear simplification approach instead of finite element method(FEM).The real-coded hybrid genetic algorithm is developed by combining normal genetic algorithm with gradient-based optimization algorithm.The numerical and experimental results for conditioned soil are compared.The forecast strains based on identified nonlinear constitutive model of soil agree well with observed ones.The effectiveness and accuracy of proposed parameter estimation approach are validated.
文摘Wind-power （WP） estimation is necessary for power system in several operations, which are as the optimal power flow between conventional units and wind farms, generators scheduling, and electricity market bidding. Estimating the output power of a wind energy conversion unit （WEC） mainly bases on the incident wind speed at the unit site by using the power characteristic curve. In addition, several time-series models have been using in wind speed forecasting. These models are characterized with requiring a large set of data. In order to prevent from the wind speed measurement and the need of a precise wind turbine model, an novel method basing on neural network and the grey predictor model GM （1,1） is proposed. Though the method, the estimating model can be built only by using the experimental data, which are obtained from the WP system in laboratory. The effectiveness of the estimating model is confirmed by the simulation results.
文摘Measurement of the volume of gas adsorbed per unit mass of coal with increasing pressure at a constant temperature produces an isotherm that describes the gas storage capacity of this type of coal. The accurate testing and interpretation of coal sorption isotherm plays an important role in the areas of coal mine methane drainage, coalbed methane （CBM） reservoir resource assessment, enhanced coalbed methane （ECBM） recovery, as well as the carbon dioxide （CO2） sequestration in deep coal seams or similar geological formations. Different coal sorption isotherm testing apparatus and associated calculation methods are critically reviewed and presented in this paper. These include both volumetric and gravimetric based methods, as well as experimental sorption tests with confining stress and direction sorption methods. The volumetric techniques utilise experimental apparatus with sample cell and injection pump and that with both sample cell and reference cell. Whilst the gravimetric approachesinclude methods with sample cell and suspension magnetic balance and that with both sample cell and reference cell. Different testing methods are compared and discussed in this study. A unique in-house-built coal sorption isotherm testing apparatus at the University of Wollongong was presented together with the calculation method, procedures and experimental results. The isotherm results can be calculated by both Soave-Redlich-Kwong （SRK） equation and calibration cure methods which can be used directly to convert the volume of adsorbed gas in different test conditions to standard condition （NTP）.
文摘This paper present a simulation study of an evolutionary algorithms, Particle Swarm Optimization PSO algorithm to optimize likelihood function of ARMA（1, 1） model, where maximizing likelihood function is equivalent to maximizing its logarithm, so the objective function ＇obj.fun＇ is maximizing log-likelihood function. Monte Carlo method adapted for implementing and designing the experiments of this simulation. This study including a comparison among three versions of PSO algorithm “Constriction coefficient CCPSO, Inertia weight IWPSO, and Fully Informed FIPSO”, the experiments designed by setting different values of model parameters al, bs sample size n, moreover the parameters of PSO algorithms. MSE used as test statistic to measure the efficiency PSO to estimate model. The results show the ability of PSO to estimate ARMA＇ s parameters, and the minimum values of MSE getting for COPSO.
