To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a ...To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism.The acceleration curve and the residual vibration model of the follower were separately studied.A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration,and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration.Accordingly,corresponding motion curve design software and Simulink vibration model of the follower were developed respectively,and they were integrated into an automatic optimization platform with iSIGHT.The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm.An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve.Based on the follower’s new motion curve,the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion.The offset press that installed our new designed cam exhibited a lower vibration than the previous machine,and the maximum measured acceleration of the offset press at a printing speed of 15000 r/h is reduced by 7.7%.展开更多
In recent decades,the proliferation of email communication has markedly escalated,resulting in a concomitant surge in spam emails that congest networks and presenting security risks.This study introduces an innovative...In recent decades,the proliferation of email communication has markedly escalated,resulting in a concomitant surge in spam emails that congest networks and presenting security risks.This study introduces an innovative spam detection method utilizing the Horse Herd Optimization Algorithm(HHOA),designed for binary classification within multi⁃objective framework.The method proficiently identifies essential features,minimizing redundancy and improving classification precision.The suggested HHOA attained an impressive accuracy of 97.21%on the Kaggle email dataset,with precision of 94.30%,recall of 90.50%,and F1⁃score of 92.80%.Compared to conventional techniques,such as Support Vector Machine(93.89%accuracy),Random Forest(96.14%accuracy),and K⁃Nearest Neighbours(92.08%accuracy),HHOA exhibited enhanced performance with reduced computing complexity.The suggested method demonstrated enhanced feature selection efficiency,decreasing the number of selected features while maintaining high classification accuracy.The results underscore the efficacy of HHOA in spam identification and indicate its potential for further applications in practical email filtering systems.展开更多
This paper presents a numerical investigation of the potential aerodynamic benefits of using endwall contouring in a fairly aggressive duct with six struts based on the platform for endwall design optimization.The pla...This paper presents a numerical investigation of the potential aerodynamic benefits of using endwall contouring in a fairly aggressive duct with six struts based on the platform for endwall design optimization.The platform is constructed by integrating adaptive genetic algorithm（AGA）, design of experiments（DOE）, response surface methodology（RSM） based on the artificial neural network（ANN）, and a 3D Navier–Stokes solver.The visual analysis method based on DOE is used to define the design space and analyze the impact of the design parameters on the target function（response）.Optimization of the axisymmetric and the non-axisymmetric endwall contouring in an S-shaped duct is performed and evaluated to minimize the total pressure loss.The optimal ducts are found to reduce the hub corner separation and suppress the migration of the low momentum fluid.The non-axisymmetric endwall contouring is shown to remove the separation completely and reduce the net duct loss by 32.7%.展开更多
An optimization method for 3D blade and meridional contour of centrifugal or mixed-flow impeller based on the 3D viscous computational fluid dynamics(CFD)analysis is proposed.The blade is indirectly parameterized usin...An optimization method for 3D blade and meridional contour of centrifugal or mixed-flow impeller based on the 3D viscous computational fluid dynamics(CFD)analysis is proposed.The blade is indirectly parameterized using the angular momentum and calculated by inverse design method.The design variables are separated into two categories:the meridional contour design vari-ables and the blade design variables.Firstly,only the blade is optimized using genetic algorithm with the meridional contour remained constant.The artificial neural network(ANN)techniques with the training sample data schemed according to design of experiment theory are adopted to construct the response relation between the blade design variables and the impeller performance.Then,based on the ANN approximated relation between the meridional contour design variables and impeller per-formance,the meridional contour is optimized.Fewer design variables and less calculation effort is required in this method that may be widely used in the optimization of three-dimension impellers.An optimized impeller in a mixed-flow pump,where the head and the efficiency are enhanced by 12.9%and 4.5%respectively,confirms the validity of this newly proposed method.展开更多
An effective approach for optimizing the rotor contour for variable reluctance(VR)resolver is presented.Using this approach,the procedure for optimizing the rotor is divided into two parts:the establishment of initial...An effective approach for optimizing the rotor contour for variable reluctance(VR)resolver is presented.Using this approach,the procedure for optimizing the rotor is divided into two parts:the establishment of initial shape curve,and then computation for the optimization.In order to simplify the process of the former,a shape function is constructed.And the latter is carried out by Taguchi optimization method and finite element method(FEM).An example of a 3-10 VR resolver is used to present the procedure of the optimization,and the testing results confirmed the effectivity of the approach.展开更多
A gradient-based optimization method for producing a contoured beam by using a single-fed reflector antenna is presented. First, a quick and accurate pattern approximation formula based on physical optics(PO) is adopt...A gradient-based optimization method for producing a contoured beam by using a single-fed reflector antenna is presented. First, a quick and accurate pattern approximation formula based on physical optics(PO) is adopted to calculate the gradients of the directivity with respect to reflector's nodal displacements. Because the approximation formula is a linear function of nodal displacements, the gradient can be easily derived. Then, the method of the steepest descent is adopted, and an optimization iteration procedure is proposed. The iteration procedure includes two loops: an inner loop and an outer loop. In the inner loop, the gradient and pattern are calculated by matrix operation, which is very fast by using the pre-calculated data in the outer loop. In the outer loop, the ideal terms used in the inner loop to calculate the gradient and pattern are updated, and the real pattern is calculated by the PO method. Due to the high approximation accuracy, when the outer loop is performed once, the inner loop can be performed many times, which will save much time because the integration is replaced by matrix operation. In the end, a contoured beam covering the continental United States(CONUS) is designed, and simulation results show the effectiveness of the proposed algorithm.展开更多
Miniature air quality sensors are widely used in urban grid-based monitoring due to their flexibility in deployment and low cost.However,the raw data collected by these devices often suffer from low accuracy caused by...Miniature air quality sensors are widely used in urban grid-based monitoring due to their flexibility in deployment and low cost.However,the raw data collected by these devices often suffer from low accuracy caused by environmental interference and sensor drift,highlighting the need for effective calibration methods to improve data reliability.This study proposes a data correction method based on Bayesian Optimization Support Vector Regression(BO-SVR),which combines the nonlinear modeling capability of Support Vector Regression(SVR)with the efficient global hyperparameter search of Bayesian Optimization.By introducing cross-validation loss as the optimization objective and using Gaussian process modeling with an Expected Improvement acquisition strategy,the approach automatically determines optimal hyperparameters for accurate pollutant concentration prediction.Experiments on real-world micro-sensor datasets demonstrate that BO-SVR outperforms traditional SVR,grid search SVR,and random forest(RF)models across multiple pollutants,including PM_(2.5),PM_(10),CO,NO_(2),SO_(2),and O_(3).The proposed method achieves lower prediction residuals,higher fitting accuracy,and better generalization,offering an efficient and practical solution for enhancing the quality of micro-sensor air monitoring data.展开更多
[Objective] The aim was to study the feature extraction of stored-grain insects based on ant colony optimization and support vector machine algorithm, and to explore the feasibility of the feature extraction of stored...[Objective] The aim was to study the feature extraction of stored-grain insects based on ant colony optimization and support vector machine algorithm, and to explore the feasibility of the feature extraction of stored-grain insects. [Method] Through the analysis of feature extraction in the image recognition of the stored-grain insects, the recognition accuracy of the cross-validation training model in support vector machine （SVM） algorithm was taken as an important factor of the evaluation principle of feature extraction of stored-grain insects. The ant colony optimization （ACO） algorithm was applied to the automatic feature extraction of stored-grain insects. [Result] The algorithm extracted the optimal feature subspace of seven features from the 17 morphological features, including area and perimeter. The ninety image samples of the stored-grain insects were automatically recognized by the optimized SVM classifier, and the recognition accuracy was over 95%. [Conclusion] The experiment shows that the application of ant colony optimization to the feature extraction of grain insects is practical and feasible.展开更多
基金the Foshan Science and Technology Innovation Team Project(No.FS0AA-KJ919-4402-0060)the National Natural Science Foundation of China(No.62263018)。
文摘To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism.The acceleration curve and the residual vibration model of the follower were separately studied.A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration,and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration.Accordingly,corresponding motion curve design software and Simulink vibration model of the follower were developed respectively,and they were integrated into an automatic optimization platform with iSIGHT.The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm.An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve.Based on the follower’s new motion curve,the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion.The offset press that installed our new designed cam exhibited a lower vibration than the previous machine,and the maximum measured acceleration of the offset press at a printing speed of 15000 r/h is reduced by 7.7%.
文摘In recent decades,the proliferation of email communication has markedly escalated,resulting in a concomitant surge in spam emails that congest networks and presenting security risks.This study introduces an innovative spam detection method utilizing the Horse Herd Optimization Algorithm(HHOA),designed for binary classification within multi⁃objective framework.The method proficiently identifies essential features,minimizing redundancy and improving classification precision.The suggested HHOA attained an impressive accuracy of 97.21%on the Kaggle email dataset,with precision of 94.30%,recall of 90.50%,and F1⁃score of 92.80%.Compared to conventional techniques,such as Support Vector Machine(93.89%accuracy),Random Forest(96.14%accuracy),and K⁃Nearest Neighbours(92.08%accuracy),HHOA exhibited enhanced performance with reduced computing complexity.The suggested method demonstrated enhanced feature selection efficiency,decreasing the number of selected features while maintaining high classification accuracy.The results underscore the efficacy of HHOA in spam identification and indicate its potential for further applications in practical email filtering systems.
基金supported by the National Natural Science Foundation of China (Nos.51006005, 51236001)the National Basic Research Program of China (No.2012CB720201)the Fundamen tal Research Funds for the Central Universities of China
文摘This paper presents a numerical investigation of the potential aerodynamic benefits of using endwall contouring in a fairly aggressive duct with six struts based on the platform for endwall design optimization.The platform is constructed by integrating adaptive genetic algorithm（AGA）, design of experiments（DOE）, response surface methodology（RSM） based on the artificial neural network（ANN）, and a 3D Navier–Stokes solver.The visual analysis method based on DOE is used to define the design space and analyze the impact of the design parameters on the target function（response）.Optimization of the axisymmetric and the non-axisymmetric endwall contouring in an S-shaped duct is performed and evaluated to minimize the total pressure loss.The optimal ducts are found to reduce the hub corner separation and suppress the migration of the low momentum fluid.The non-axisymmetric endwall contouring is shown to remove the separation completely and reduce the net duct loss by 32.7%.
基金This project is supported by National Natural Science Foundation of China(No.50136030).
文摘An optimization method for 3D blade and meridional contour of centrifugal or mixed-flow impeller based on the 3D viscous computational fluid dynamics(CFD)analysis is proposed.The blade is indirectly parameterized using the angular momentum and calculated by inverse design method.The design variables are separated into two categories:the meridional contour design vari-ables and the blade design variables.Firstly,only the blade is optimized using genetic algorithm with the meridional contour remained constant.The artificial neural network(ANN)techniques with the training sample data schemed according to design of experiment theory are adopted to construct the response relation between the blade design variables and the impeller performance.Then,based on the ANN approximated relation between the meridional contour design variables and impeller per-formance,the meridional contour is optimized.Fewer design variables and less calculation effort is required in this method that may be widely used in the optimization of three-dimension impellers.An optimized impeller in a mixed-flow pump,where the head and the efficiency are enhanced by 12.9%and 4.5%respectively,confirms the validity of this newly proposed method.
文摘An effective approach for optimizing the rotor contour for variable reluctance(VR)resolver is presented.Using this approach,the procedure for optimizing the rotor is divided into two parts:the establishment of initial shape curve,and then computation for the optimization.In order to simplify the process of the former,a shape function is constructed.And the latter is carried out by Taguchi optimization method and finite element method(FEM).An example of a 3-10 VR resolver is used to present the procedure of the optimization,and the testing results confirmed the effectivity of the approach.
基金supported by the National Natural Science Foundation of China(51805399)the Fundamental Research Funds for the Central Universities(JB180403)+2 种基金the Chinese Academy of Sciences(CAS)"Light of West China" Program(2017-XBQNXZ-B-024)the National Basic Research Program of China(973 Program)(2015CB857100)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the CAS
文摘A gradient-based optimization method for producing a contoured beam by using a single-fed reflector antenna is presented. First, a quick and accurate pattern approximation formula based on physical optics(PO) is adopted to calculate the gradients of the directivity with respect to reflector's nodal displacements. Because the approximation formula is a linear function of nodal displacements, the gradient can be easily derived. Then, the method of the steepest descent is adopted, and an optimization iteration procedure is proposed. The iteration procedure includes two loops: an inner loop and an outer loop. In the inner loop, the gradient and pattern are calculated by matrix operation, which is very fast by using the pre-calculated data in the outer loop. In the outer loop, the ideal terms used in the inner loop to calculate the gradient and pattern are updated, and the real pattern is calculated by the PO method. Due to the high approximation accuracy, when the outer loop is performed once, the inner loop can be performed many times, which will save much time because the integration is replaced by matrix operation. In the end, a contoured beam covering the continental United States(CONUS) is designed, and simulation results show the effectiveness of the proposed algorithm.
文摘Miniature air quality sensors are widely used in urban grid-based monitoring due to their flexibility in deployment and low cost.However,the raw data collected by these devices often suffer from low accuracy caused by environmental interference and sensor drift,highlighting the need for effective calibration methods to improve data reliability.This study proposes a data correction method based on Bayesian Optimization Support Vector Regression(BO-SVR),which combines the nonlinear modeling capability of Support Vector Regression(SVR)with the efficient global hyperparameter search of Bayesian Optimization.By introducing cross-validation loss as the optimization objective and using Gaussian process modeling with an Expected Improvement acquisition strategy,the approach automatically determines optimal hyperparameters for accurate pollutant concentration prediction.Experiments on real-world micro-sensor datasets demonstrate that BO-SVR outperforms traditional SVR,grid search SVR,and random forest(RF)models across multiple pollutants,including PM_(2.5),PM_(10),CO,NO_(2),SO_(2),and O_(3).The proposed method achieves lower prediction residuals,higher fitting accuracy,and better generalization,offering an efficient and practical solution for enhancing the quality of micro-sensor air monitoring data.
基金Supported by the National Natural Science Foundation of China(31101085)the Program for Young Core Teachers of Colleges in Henan(2011GGJS-094)the Scientific Research Project for the High Level Talents,North China University of Water Conservancy and Hydroelectric Power~~
文摘[Objective] The aim was to study the feature extraction of stored-grain insects based on ant colony optimization and support vector machine algorithm, and to explore the feasibility of the feature extraction of stored-grain insects. [Method] Through the analysis of feature extraction in the image recognition of the stored-grain insects, the recognition accuracy of the cross-validation training model in support vector machine （SVM） algorithm was taken as an important factor of the evaluation principle of feature extraction of stored-grain insects. The ant colony optimization （ACO） algorithm was applied to the automatic feature extraction of stored-grain insects. [Result] The algorithm extracted the optimal feature subspace of seven features from the 17 morphological features, including area and perimeter. The ninety image samples of the stored-grain insects were automatically recognized by the optimized SVM classifier, and the recognition accuracy was over 95%. [Conclusion] The experiment shows that the application of ant colony optimization to the feature extraction of grain insects is practical and feasible.
