A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decom...A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.展开更多
Taking the ratio of heat transfer area to net power and heat recovery efficiency into account, a multi-objective mathematical model was developed for organic Rankine cycle （ORC）. Working fluids considered were R123,...Taking the ratio of heat transfer area to net power and heat recovery efficiency into account, a multi-objective mathematical model was developed for organic Rankine cycle （ORC）. Working fluids considered were R123, R134a, R141b, R227ea and R245fa. Under the given conditions, the parameters including evaporating and condensing pressures, working fluid and cooling water velocities were optimized by simulated annealing algorithm. The results show that the optimal evaporating pressure increases with the heat source temperature increasing. Compared with other working fluids, R123 is the best choice for the temperature range of 100--180℃ and R141 b shows better performance when the temperature is higher than 180 ℃. Economic characteristic of system decreases rapidly with the decrease of heat source temperature. ORC system is uneconomical for the heat source temperature lower than 100℃.展开更多
In order to study the variation of machine tools’dynamic characteristics in the manufacturing space,a Kriging approximate model is proposed.Finite element method(FEM)is employed on the platform of ANSYS to establish ...In order to study the variation of machine tools’dynamic characteristics in the manufacturing space,a Kriging approximate model is proposed.Finite element method(FEM)is employed on the platform of ANSYS to establish finite element(FE)model with the dynamic characteristic of combined interface for a milling machine,which is newly designed for producing aero engine blades by a certain enterprise group in China.The stiffness and damping of combined interfaces are adjusted by using adaptive simulated annealing algorithm with the optimizing software of iSIGHT in the process of FE model update according to experimental modal analysis(EMA)results.The Kriging approximate model is established according to the finite element analysis results utilizing orthogonal design samples by taking into account of the range of configuration parameters.On the basis of the Kriging approximate model,the response surfaces between key response parameter and configuration parameters are obtained.The results indicate that configuration parameters have great effects on dynamic characteristics of machine tools,and the Kriging approximate model is an effective and rapid method for estimating dynamic characteristics of machine tools in the manufacturing space.展开更多
Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting hea...Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting head, and the rotate speed） are chosen as the optimized parameters. According to the force on the cutting pick, the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head, the optimized design model of collecting head is built. Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 era, then making use of the improved simulated annealing genetic algorithm （SAGA）, the corresponding optimized result can be obtained. At the same time, in order to speed up the controlling of collecting head, the optimization results are analyzed using the regression analysis method, and the conclusion of the second parameter of the seabed microtopography is drawn.展开更多
For deposit body medium, the internal structural properties may be the controlling factors for the strength of the material and the mechanical response. Based on the results of soil-rock meso-statistics using digital ...For deposit body medium, the internal structural properties may be the controlling factors for the strength of the material and the mechanical response. Based on the results of soil-rock meso-statistics using digital imaging, a simulated annealing algorithm is adopted to expand the meso-structural features of deposit bodies in 3D. The construction of the 3D meso-structure of a deposit body is achieved, and then the particle flow analysis program PFC3 D is used to simulate the mechanical properties of the deposit body. It is shown that with a combination of the simulated annealing algorithm and the statistical feature functions, the randomness and heterogeneity of the rock distribution in the 3D inner structure of deposit body medium can be realized, and the reconstructed structural features of the deposit medium can match the features of the digital images well. The spatial utilizations and the compacting effects of the body-centered cubic, hexagonal close and face-centered packing models are high, so these structures can be applied in the simulations of the deposit structures. However, the shear features of the deposit medium vary depending on the different model constructive modes. Rocks, which are the backbone of the deposit, are the factors that determine the shear strength and deformation modulus of the deposit body. The modeling method proposed is useful for the construction of 3D meso-scope models from 2D meso-scope statistics and can be used for studying the mechanical properties of mixed media, such as deposit bodies.展开更多
Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to th...Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to the analysis with support vector machine method, the drawback of determining the parameters only by experts' experience should be improved. After a detailed description of the methodology of SVM and simulated annealing, an improved algorithm was proposed for the automatic optimization of parameters using SVM method. An example has proved that the proposed method can efficiently select the parameters of the SVM method. And by optimizing the parameters, the forecasting accuracy of the max wind velocity increases by 34.45%, which indicates that the new SASVM model improves the forecasting accuracy.展开更多
文摘A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.
基金Project(2009GK2009) supported by Science and Technology Department Funds of Hunan Province,ChinaProject(08C26224302178) supported by Innovation Fund for Technology Based Firms of China
文摘Taking the ratio of heat transfer area to net power and heat recovery efficiency into account, a multi-objective mathematical model was developed for organic Rankine cycle （ORC）. Working fluids considered were R123, R134a, R141b, R227ea and R245fa. Under the given conditions, the parameters including evaporating and condensing pressures, working fluid and cooling water velocities were optimized by simulated annealing algorithm. The results show that the optimal evaporating pressure increases with the heat source temperature increasing. Compared with other working fluids, R123 is the best choice for the temperature range of 100--180℃ and R141 b shows better performance when the temperature is higher than 180 ℃. Economic characteristic of system decreases rapidly with the decrease of heat source temperature. ORC system is uneconomical for the heat source temperature lower than 100℃.
基金Project(2009ZX04001-073)supported by the Important National Science&Technology Specific Projects of ChinaProject(51105025)supported by the National Natural Science Foundation of China
文摘In order to study the variation of machine tools’dynamic characteristics in the manufacturing space,a Kriging approximate model is proposed.Finite element method(FEM)is employed on the platform of ANSYS to establish finite element(FE)model with the dynamic characteristic of combined interface for a milling machine,which is newly designed for producing aero engine blades by a certain enterprise group in China.The stiffness and damping of combined interfaces are adjusted by using adaptive simulated annealing algorithm with the optimizing software of iSIGHT in the process of FE model update according to experimental modal analysis(EMA)results.The Kriging approximate model is established according to the finite element analysis results utilizing orthogonal design samples by taking into account of the range of configuration parameters.On the basis of the Kriging approximate model,the response surfaces between key response parameter and configuration parameters are obtained.The results indicate that configuration parameters have great effects on dynamic characteristics of machine tools,and the Kriging approximate model is an effective and rapid method for estimating dynamic characteristics of machine tools in the manufacturing space.
基金Project(50875265) supported by the National Natural Science Foundation of ChinaProject(20080440992) supported by the Postdoctoral Science Foundation of ChinaProject(2009SK3159) supported by the Technology Support Plan of Hunan Province,China
文摘Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting head, and the rotate speed） are chosen as the optimized parameters. According to the force on the cutting pick, the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head, the optimized design model of collecting head is built. Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 era, then making use of the improved simulated annealing genetic algorithm （SAGA）, the corresponding optimized result can be obtained. At the same time, in order to speed up the controlling of collecting head, the optimization results are analyzed using the regression analysis method, and the conclusion of the second parameter of the seabed microtopography is drawn.
基金Projects(51309089,11202063)supported by the National Natural Science Foundation of ChinaProject(2013BAB06B01)supported by the National High Technology Research and Development Program of China+1 种基金Project(2015CB057903)supported by the National Basic Research Program of ChinaProject(BK20130846)supported by Natural Science Foundation of Jiangsu Province,China
文摘For deposit body medium, the internal structural properties may be the controlling factors for the strength of the material and the mechanical response. Based on the results of soil-rock meso-statistics using digital imaging, a simulated annealing algorithm is adopted to expand the meso-structural features of deposit bodies in 3D. The construction of the 3D meso-structure of a deposit body is achieved, and then the particle flow analysis program PFC3 D is used to simulate the mechanical properties of the deposit body. It is shown that with a combination of the simulated annealing algorithm and the statistical feature functions, the randomness and heterogeneity of the rock distribution in the 3D inner structure of deposit body medium can be realized, and the reconstructed structural features of the deposit medium can match the features of the digital images well. The spatial utilizations and the compacting effects of the body-centered cubic, hexagonal close and face-centered packing models are high, so these structures can be applied in the simulations of the deposit structures. However, the shear features of the deposit medium vary depending on the different model constructive modes. Rocks, which are the backbone of the deposit, are the factors that determine the shear strength and deformation modulus of the deposit body. The modeling method proposed is useful for the construction of 3D meso-scope models from 2D meso-scope statistics and can be used for studying the mechanical properties of mixed media, such as deposit bodies.
基金Project(71071052) supported by the National Natural Science Foundation of ChinaProject(JB2011097) supported by the Fundamental Research Funds for the Central Universities of China
文摘Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to the analysis with support vector machine method, the drawback of determining the parameters only by experts' experience should be improved. After a detailed description of the methodology of SVM and simulated annealing, an improved algorithm was proposed for the automatic optimization of parameters using SVM method. An example has proved that the proposed method can efficiently select the parameters of the SVM method. And by optimizing the parameters, the forecasting accuracy of the max wind velocity increases by 34.45%, which indicates that the new SASVM model improves the forecasting accuracy.
