According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are comput...According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are computed to determine the time delay and the embedding dimension.Due to different features of the data,data mining algorithm is conducted to classify the data into different groups.Redundant information is eliminated by the advantage of data mining technology,and the historical loads that have highly similar features with the forecasting day are searched by the system.As a result,the training data can be decreased and the computing speed can also be improved when constructing support vector machine(SVM) model.Then,SVM algorithm is used to predict power load with parameters that get in pretreatment.In order to prove the effectiveness of the new model,the calculation with data mining SVM algorithm is compared with that of single SVM and back propagation network.It can be seen that the new DSVM algorithm effectively improves the forecast accuracy by 0.75%,1.10% and 1.73% compared with SVM for two random dimensions of 11-dimension,14-dimension and BP network,respectively.This indicates that the DSVM gains perfect improvement effect in the short-term power load forecasting.展开更多
Particle size distributions of obtained samples from several sampling campaigns were determined and raw data were mass balanced before being used in simulation studies.After determination of breakage function,selectio...Particle size distributions of obtained samples from several sampling campaigns were determined and raw data were mass balanced before being used in simulation studies.After determination of breakage function,selection function,Bond work index,residence time distribution parameters,and Whiten's model parameters for air separators and diaphragms between the two compartments of tube ball mills,performance of the circuits was simulated for given throughputs and feed particle size distribution.Whiten's model parameters were determined by GA(genetic algorithm) toolbox of MATLAB software.Based on implemented models for modeling and simulation,optimization of circuits was carried out.It increased nearly 10.5% and 15.8% in fresh feed capacity input to each tube ball mill.In addition,circulating load ratios of circuits are modified to 118% and 127% from low level of 57% and 22%,respectively,and also cut points of air separators are adjusted at 30 and 40 μm from high range of 53 and 97 μm,respectively.All applications helped in well-operation and energy consumption reduction of equipments.展开更多
Many industry processes can be described as Hammerstein-Wiener nonlinear systems. In this work, an improved constrained model predictive control algorithm is presented for Hammerstein-Wiener systems. In the new approa...Many industry processes can be described as Hammerstein-Wiener nonlinear systems. In this work, an improved constrained model predictive control algorithm is presented for Hammerstein-Wiener systems. In the new approach, the maximum and minimum of partial derivative for input and output nonlinearities are solved in the neighbourhood of the equilibrium. And several parameter-dependent Lyapunov functions, each one corresponding to a different vertex of polytopic descriptions models, are introduced to analyze the stability of Hammerstein-Wiener systems, but only one Lyapunov function is utilized to analyze system stability like the traditional method. Consequently, the conservation of the traditional quadratic stability is removed, and the terminal regions are enlarged. Simulation and field trial results show that the proposed algorithm is valid. It has higher control precision and shorter blowing time than the traditional approach.展开更多
A novel multiple watermarks cooperative authentication algorithm was presented for image contents authentication.This algorithm is able to extract multiple features from the image wavelet domain,which is based on that...A novel multiple watermarks cooperative authentication algorithm was presented for image contents authentication.This algorithm is able to extract multiple features from the image wavelet domain,which is based on that the t watermarks are generated.Moreover,a new watermark embedding method,using the space geometric model,was proposed,in order to effectively tackle with the mutual influences problem among t watermarks.Specifically,the incidental tampering location,the classification of intentional content tampering and the incidental modification can be achieved via mutual cooperation of the t watermarks.Both the theoretical analysis and simulations results validate the feasibility and efficacy of the proposed algorithm.展开更多
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
基金Project(70671039) supported by the National Natural Science Foundation of China
文摘According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are computed to determine the time delay and the embedding dimension.Due to different features of the data,data mining algorithm is conducted to classify the data into different groups.Redundant information is eliminated by the advantage of data mining technology,and the historical loads that have highly similar features with the forecasting day are searched by the system.As a result,the training data can be decreased and the computing speed can also be improved when constructing support vector machine(SVM) model.Then,SVM algorithm is used to predict power load with parameters that get in pretreatment.In order to prove the effectiveness of the new model,the calculation with data mining SVM algorithm is compared with that of single SVM and back propagation network.It can be seen that the new DSVM algorithm effectively improves the forecast accuracy by 0.75%,1.10% and 1.73% compared with SVM for two random dimensions of 11-dimension,14-dimension and BP network,respectively.This indicates that the DSVM gains perfect improvement effect in the short-term power load forecasting.
基金financially supported by University of Tehran under contract number 450/51027041 with Iran Ministry of Industries and Mines
文摘Particle size distributions of obtained samples from several sampling campaigns were determined and raw data were mass balanced before being used in simulation studies.After determination of breakage function,selection function,Bond work index,residence time distribution parameters,and Whiten's model parameters for air separators and diaphragms between the two compartments of tube ball mills,performance of the circuits was simulated for given throughputs and feed particle size distribution.Whiten's model parameters were determined by GA(genetic algorithm) toolbox of MATLAB software.Based on implemented models for modeling and simulation,optimization of circuits was carried out.It increased nearly 10.5% and 15.8% in fresh feed capacity input to each tube ball mill.In addition,circulating load ratios of circuits are modified to 118% and 127% from low level of 57% and 22%,respectively,and also cut points of air separators are adjusted at 30 and 40 μm from high range of 53 and 97 μm,respectively.All applications helped in well-operation and energy consumption reduction of equipments.
基金Project(61074074) supported by the National Natural Science Foundation,ChinaProject(KT2012C01J0401) supported by the Group Innovative Fund,China
文摘Many industry processes can be described as Hammerstein-Wiener nonlinear systems. In this work, an improved constrained model predictive control algorithm is presented for Hammerstein-Wiener systems. In the new approach, the maximum and minimum of partial derivative for input and output nonlinearities are solved in the neighbourhood of the equilibrium. And several parameter-dependent Lyapunov functions, each one corresponding to a different vertex of polytopic descriptions models, are introduced to analyze the stability of Hammerstein-Wiener systems, but only one Lyapunov function is utilized to analyze system stability like the traditional method. Consequently, the conservation of the traditional quadratic stability is removed, and the terminal regions are enlarged. Simulation and field trial results show that the proposed algorithm is valid. It has higher control precision and shorter blowing time than the traditional approach.
基金Project(2012BAH09B02) supported by the National Science and Technology Support Program,ChinaProjects(12JJ3068,12JJ2041) supported by the Natural Science Fundation of Hunan Province,China
文摘A novel multiple watermarks cooperative authentication algorithm was presented for image contents authentication.This algorithm is able to extract multiple features from the image wavelet domain,which is based on that the t watermarks are generated.Moreover,a new watermark embedding method,using the space geometric model,was proposed,in order to effectively tackle with the mutual influences problem among t watermarks.Specifically,the incidental tampering location,the classification of intentional content tampering and the incidental modification can be achieved via mutual cooperation of the t watermarks.Both the theoretical analysis and simulations results validate the feasibility and efficacy of the proposed algorithm.
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.
