An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, m...An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, modified similarity measure was considered to gather nodes having similar characteristics. The similarity measure was needed to contain locafi0nal prices as well as regional coherency. In order to consider the two properties simultaneously, distance measure of fuzzy C-mean algorithm had to be modified. Regional clustering algorithm for interconnected power systems was designed based on the modified fuzzy C-mean algorithm. The proposed algorithm produces proper classification for the interconnected power system and the results are demonstrated in the example of IEEE 39-bus interconnected electricity system.展开更多
The error of the conventional velocity numerical integration algorithm was evaluated through the Taylor series expansion. It is revealed that neglecting the second- and higher-order terms of attitude increments will l...The error of the conventional velocity numerical integration algorithm was evaluated through the Taylor series expansion. It is revealed that neglecting the second- and higher-order terms of attitude increments will lead to the velocity numerical integration error, which is proportional to the triple cross product of the angular rate and specific force. A selection criterion for the velocity numerical integration algorithm was established for strapdown inertial navigation system (SINS) in spinning missiles. The spin angular rate with large amplitude will cause the accuracy of the conventional velocity numerical integration algorithm in SINS to decrease dramatically when the ballistic missile is spinning fast. Therefore, with the second- and higher-order terms of attitude increments considered, based on the rotation vector and the velocity translation vector, the velocity numerical integration algorithm was optimized for SINS in spinning ballistic missiles. The superiority of the optimized algorithm over the conventional one was analytically derived and validated by the simulation. The optimized algorithm turns out to be a better choice for SINS in spinning ballistic missiles and other high-precision navigation systems and high-maneuver applications.展开更多
In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indi...In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.展开更多
New sigma point filtering algorithms, including the unscented Kalman filter （UKF） and the divided difference filter （DDF）, are designed to solve the nonlinear filtering problem under the condition of correlated no...New sigma point filtering algorithms, including the unscented Kalman filter （UKF） and the divided difference filter （DDF）, are designed to solve the nonlinear filtering problem under the condition of correlated noises. Based on the minimum mean square error estimation theory, the nonlinear optimal predictive and correction recursive formulas under the hypothesis that the input noise is correlated with the measurement noise are derived and can be described in a unified framework. Then, UKF and DDF with correlated noises are proposed on the basis of approximation of the posterior mean and covariance in the unified framework by using unscented transformation and second order Stirling＇s interpolation. The proposed UKF and DDF with correlated noises break through the limitation that input noise and measurement noise must be assumed to be uneorrelated in standard UKF and DDF. Two simulation examples show the effectiveness and feasibility of new algorithms for dealing with nonlinear filtering issue with correlated noises.展开更多
In order to deal with the complex association relationships between classes in an object-oriented software system,a novel approach for identifying refactoring opportunities is proposed.The approach can be used to dete...In order to deal with the complex association relationships between classes in an object-oriented software system,a novel approach for identifying refactoring opportunities is proposed.The approach can be used to detect complex and duplicated many-to-many association relationships in source code,and to provide guidance for further refactoring.In the approach,source code is first transformed to an abstract syntax tree from which all data members of each class are extracted,then each class is characterized in connection with a set of association classes saving its data members.Next,classes in common associations are obtained by comparing different association classes sets in integrated analysis.Finally,on condition of pre-defined thresholds,all class sets in candidate for refactoring and their common association classes are saved and exported.This approach is tested on 4 projects.The results show that the precision is over 96%when the threshold is 3,and 100%when the threshold is 4.Meanwhile,this approach has good execution efficiency as the execution time taken for a project with more than 500 classes is less than 4 s,which also indicates that it can be applied to projects of different scales to identify their refactoring opportunities effectively.展开更多
An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter （SHAPF） to enhance its harmonic elimination performance. Based on the inverse system method, the d-axis a...An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter （SHAPF） to enhance its harmonic elimination performance. Based on the inverse system method, the d-axis and q-axis current dynamics of the SHAPF system were decoupled and linearized into two pseudolinear subsystems. Then, an optimal feedback controUer was designed for the pseudolinear system, and the stability condition of the resulting zero dynamics was presented. Under the control strategy, the current dynamics can asymptotically converge to their reference states and the zero dynamics can be bounded. Simulation results show that the proposed control strategy is robust against load variations and system parameter mismatches, its steady-state performance is better than that of the traditional linear control strategy.展开更多
基金Work supported by the Second Stage of Brain Korea 21 ProjectsWork(2010-0020163) supported by Priority Research Centers Program through the National Research Foundation (NRF) funded by the Ministry of Education,Science and Technology of Korea
文摘An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, modified similarity measure was considered to gather nodes having similar characteristics. The similarity measure was needed to contain locafi0nal prices as well as regional coherency. In order to consider the two properties simultaneously, distance measure of fuzzy C-mean algorithm had to be modified. Regional clustering algorithm for interconnected power systems was designed based on the modified fuzzy C-mean algorithm. The proposed algorithm produces proper classification for the interconnected power system and the results are demonstrated in the example of IEEE 39-bus interconnected electricity system.
基金Project supported in part by Program for New Century Excellent Talents in University (NCET) of China
文摘The error of the conventional velocity numerical integration algorithm was evaluated through the Taylor series expansion. It is revealed that neglecting the second- and higher-order terms of attitude increments will lead to the velocity numerical integration error, which is proportional to the triple cross product of the angular rate and specific force. A selection criterion for the velocity numerical integration algorithm was established for strapdown inertial navigation system (SINS) in spinning missiles. The spin angular rate with large amplitude will cause the accuracy of the conventional velocity numerical integration algorithm in SINS to decrease dramatically when the ballistic missile is spinning fast. Therefore, with the second- and higher-order terms of attitude increments considered, based on the rotation vector and the velocity translation vector, the velocity numerical integration algorithm was optimized for SINS in spinning ballistic missiles. The superiority of the optimized algorithm over the conventional one was analytically derived and validated by the simulation. The optimized algorithm turns out to be a better choice for SINS in spinning ballistic missiles and other high-precision navigation systems and high-maneuver applications.
基金Project(50774095) supported by the National Natural Science Foundation of ChinaProject(200449) supported by the National Outstanding Doctoral Dissertations Special Funds of China
文摘In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.
基金Projects(61135001, 61075029, 61074155) supported by the National Natural Science Foundation of ChinaProject(20110491690) supported by the Postdocteral Science Foundation of China
文摘New sigma point filtering algorithms, including the unscented Kalman filter （UKF） and the divided difference filter （DDF）, are designed to solve the nonlinear filtering problem under the condition of correlated noises. Based on the minimum mean square error estimation theory, the nonlinear optimal predictive and correction recursive formulas under the hypothesis that the input noise is correlated with the measurement noise are derived and can be described in a unified framework. Then, UKF and DDF with correlated noises are proposed on the basis of approximation of the posterior mean and covariance in the unified framework by using unscented transformation and second order Stirling＇s interpolation. The proposed UKF and DDF with correlated noises break through the limitation that input noise and measurement noise must be assumed to be uneorrelated in standard UKF and DDF. Two simulation examples show the effectiveness and feasibility of new algorithms for dealing with nonlinear filtering issue with correlated noises.
文摘In order to deal with the complex association relationships between classes in an object-oriented software system,a novel approach for identifying refactoring opportunities is proposed.The approach can be used to detect complex and duplicated many-to-many association relationships in source code,and to provide guidance for further refactoring.In the approach,source code is first transformed to an abstract syntax tree from which all data members of each class are extracted,then each class is characterized in connection with a set of association classes saving its data members.Next,classes in common associations are obtained by comparing different association classes sets in integrated analysis.Finally,on condition of pre-defined thresholds,all class sets in candidate for refactoring and their common association classes are saved and exported.This approach is tested on 4 projects.The results show that the precision is over 96%when the threshold is 3,and 100%when the threshold is 4.Meanwhile,this approach has good execution efficiency as the execution time taken for a project with more than 500 classes is less than 4 s,which also indicates that it can be applied to projects of different scales to identify their refactoring opportunities effectively.
基金Project(61174068)supported by the National Natural Science Foundation of China
文摘An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter （SHAPF） to enhance its harmonic elimination performance. Based on the inverse system method, the d-axis and q-axis current dynamics of the SHAPF system were decoupled and linearized into two pseudolinear subsystems. Then, an optimal feedback controUer was designed for the pseudolinear system, and the stability condition of the resulting zero dynamics was presented. Under the control strategy, the current dynamics can asymptotically converge to their reference states and the zero dynamics can be bounded. Simulation results show that the proposed control strategy is robust against load variations and system parameter mismatches, its steady-state performance is better than that of the traditional linear control strategy.
