This paper presents an all-parametric model of radar target in optic region, in which the localized scattering center's frequency and aspect angle dependent scattering level, distance and azimuth locations are mod...This paper presents an all-parametric model of radar target in optic region, in which the localized scattering center's frequency and aspect angle dependent scattering level, distance and azimuth locations are modeled as the feature vectors. And the traditional TLS-Prony algorithm is modified to extract these feature vectors. The analysis of Cramer-Rao bound shows that the modified algorithm not only improves the restriction of high signal-to-noise ratio(SNR)threshold of traditional TLS-Prony algorithm, but also is suitable to the extraction of big damped coefficients and high-resolution estimation of near separation poles. Finally, an illustrative example is presented to verify its practicability in the applications. The experimental results show that the method developed can not only recognize two airplane-like targets with similar shape at low SNR, but also compress the original radar data with high fidelity.展开更多
This paper introduced an integrated allocation model for distribution centers (DCs). The facility cost, inventory cost, transportation cost and service quality were considered in the model. An improved genetic algorit...This paper introduced an integrated allocation model for distribution centers (DCs). The facility cost, inventory cost, transportation cost and service quality were considered in the model. An improved genetic algorithm (IGA) was proposed to solve the problem. The improvement of IGA is based on the idea of adjusting crossover probability and mutation probability. The IGA is supplied by heuristic rules too. The simulation results show that the IGA is better than the standard GA(SGA) in search efficiency and equality.展开更多
To improve the measurement accuracy of structured laser for inner surface dimensions of a deep hole, a new method to extract the laser stripe center line is proposed. An improved adaptive genetic algorithm that can co...To improve the measurement accuracy of structured laser for inner surface dimensions of a deep hole, a new method to extract the laser stripe center line is proposed. An improved adaptive genetic algorithm that can converge rapidly and search the global optimum is used to determine the threshold for the laser stripe segmentation. And then NURBS interpolation which has a good local control capability is adopted to extract the laser stripe center line. Experiments show that the extracted laser stripe center line is stable and the diameter of the deep hole can be measured accurately.展开更多
The nesting problem involves arranging pieces on a plate to maximize use of material. A new scheme for 2D ir- regular-shaped nesting problem is proposed. The new scheme is based on the NFP (No Fit Polygon) algorithm a...The nesting problem involves arranging pieces on a plate to maximize use of material. A new scheme for 2D ir- regular-shaped nesting problem is proposed. The new scheme is based on the NFP (No Fit Polygon) algorithm and a new placement principle for pieces. The novel placement principle is to place a piece to the position with lowest gravity center based on NFP. In addition, genetic algorithm (GA) is adopted to find an efficient nesting sequence. The proposed scheme can deal with pieces with arbitrary rotation and containing region with holes, and achieves competitive results in experiment on benchmark datasets.展开更多
In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment a...In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.展开更多
It takes more time and is easier to fall into the local minimum value when using the traditional full-supervised learning algorithm to train RBFNN. Therefore, the paper proposes one algorithm to determine the RBFNN’s...It takes more time and is easier to fall into the local minimum value when using the traditional full-supervised learning algorithm to train RBFNN. Therefore, the paper proposes one algorithm to determine the RBFNN’s data center based on the improvement density method. First it uses the improved density method to select RBFNN’s data center, and calculates the expansion constant of each center, then only trains the network weight with the gradient descent method. To compare this method with full-supervised gradient descent method, the time not only has obvious reduction (including to choose data center’s time by density method), but also obtains better classification results when using the data set in UCI to carry on the test to the network.展开更多
文摘This paper presents an all-parametric model of radar target in optic region, in which the localized scattering center's frequency and aspect angle dependent scattering level, distance and azimuth locations are modeled as the feature vectors. And the traditional TLS-Prony algorithm is modified to extract these feature vectors. The analysis of Cramer-Rao bound shows that the modified algorithm not only improves the restriction of high signal-to-noise ratio(SNR)threshold of traditional TLS-Prony algorithm, but also is suitable to the extraction of big damped coefficients and high-resolution estimation of near separation poles. Finally, an illustrative example is presented to verify its practicability in the applications. The experimental results show that the method developed can not only recognize two airplane-like targets with similar shape at low SNR, but also compress the original radar data with high fidelity.
文摘This paper introduced an integrated allocation model for distribution centers (DCs). The facility cost, inventory cost, transportation cost and service quality were considered in the model. An improved genetic algorithm (IGA) was proposed to solve the problem. The improvement of IGA is based on the idea of adjusting crossover probability and mutation probability. The IGA is supplied by heuristic rules too. The simulation results show that the IGA is better than the standard GA(SGA) in search efficiency and equality.
基金the Excellent Young Teacher Foundation from Ministry of Education (203078)
文摘To improve the measurement accuracy of structured laser for inner surface dimensions of a deep hole, a new method to extract the laser stripe center line is proposed. An improved adaptive genetic algorithm that can converge rapidly and search the global optimum is used to determine the threshold for the laser stripe segmentation. And then NURBS interpolation which has a good local control capability is adopted to extract the laser stripe center line. Experiments show that the extracted laser stripe center line is stable and the diameter of the deep hole can be measured accurately.
基金Project (No. 60573146) supported by the National Natural ScienceFoundation of China
文摘The nesting problem involves arranging pieces on a plate to maximize use of material. A new scheme for 2D ir- regular-shaped nesting problem is proposed. The new scheme is based on the NFP (No Fit Polygon) algorithm and a new placement principle for pieces. The novel placement principle is to place a piece to the position with lowest gravity center based on NFP. In addition, genetic algorithm (GA) is adopted to find an efficient nesting sequence. The proposed scheme can deal with pieces with arbitrary rotation and containing region with holes, and achieves competitive results in experiment on benchmark datasets.
基金Project (70671039) supported by the National Natural Science Foundation of China
文摘In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.
文摘It takes more time and is easier to fall into the local minimum value when using the traditional full-supervised learning algorithm to train RBFNN. Therefore, the paper proposes one algorithm to determine the RBFNN’s data center based on the improvement density method. First it uses the improved density method to select RBFNN’s data center, and calculates the expansion constant of each center, then only trains the network weight with the gradient descent method. To compare this method with full-supervised gradient descent method, the time not only has obvious reduction (including to choose data center’s time by density method), but also obtains better classification results when using the data set in UCI to carry on the test to the network.
