Microbial fuel cell(MFC)is a kind of promising clean power supply energy equipment,but serious nonlinearities and disturbances exist when the MFC runs,and it is an important topic to guarantee that the output voltage ...Microbial fuel cell(MFC)is a kind of promising clean power supply energy equipment,but serious nonlinearities and disturbances exist when the MFC runs,and it is an important topic to guarantee that the output voltage reaches the setting value quickly and smoothly.Regulating the feeding flow is an effective way to achieve this goal,and especially,the satisfactory results can be achieved by regulating anode feeding flow.In this work,a feedforward fuzzy logic PID algorithm is proposed.The fuzzy logic system is introduced to deal with the non-linear dynamics of MFC,and corresponding PID parameters are calculated according to defuzzification.The magnitude value of the current density is used to simulate the value of the external load.The simulation results indicate that the MFC output voltage can track the setting value quickly and smoothly with the proposed feedforward fuzzy logic PID algorithm.The proposed algorithm is more efficient and robust with respect to anti-disturbance performance and tracking accuracy than other three control methods.展开更多
Face anti-spoofing is a relatively important part of the face recognition system,which has great significance for financial payment and access control systems.Aiming at the problems of unstable face alignment,complex ...Face anti-spoofing is a relatively important part of the face recognition system,which has great significance for financial payment and access control systems.Aiming at the problems of unstable face alignment,complex lighting,and complex structure of face anti-spoofing detection network,a novel method is presented using a combination of convolutional neural network and brightness equalization.Firstly,multi-task convolutional neural network(MTCNN)based on the cascade of three convolutional neural networks(CNNs),P-net,R-net,and O-net are used to achieve accurate positioning of the face,and the detected face bounding box is cropped by a specified multiple,then brightness equalization is adopted to perform brightness compensation on different brightness areas of the face image.Finally,data features are extracted and classification is given by utilizing a 12-layer convolution neural network.Experiments of the proposed algorithm were carried out on CASIA-FASD.The results show that the classification accuracy is relatively high,and the half total error rate(HTER)reaches 1.02%.展开更多
In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(...In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(FAHP) and artificial neural network(ANN) from the perspective of accuracy and quickness is proposed.An analytic hierarchy process model for the transformer risk assessment is built by analysis of the risk factors affecting the transformer risk level and the weight relation of each risk factor in transformer risk calculation is analyzed by application of fuzzy consistency judgment matrix;with utilization of adaptive ability and nonlinear mapping ability of the ANN,the risk factors with large weights are used as input of neutral network,and thus intelligent quantitative assessment of transformer risk is realized.The simulation result shows that the proposed method increases the speed and accuracy of the risk assessment and can provide feasible decision basis for the transformer risk management and maintenance decisions.展开更多
The problem of global robust asymptotical stability for a class of Takagi-Sugeno fuzzy neural networks（TSFNN） with discontinuous activation functions and time delays is investigated by using Lyapunov stability theor...The problem of global robust asymptotical stability for a class of Takagi-Sugeno fuzzy neural networks（TSFNN） with discontinuous activation functions and time delays is investigated by using Lyapunov stability theory.Based on linear matrix inequalities（LMIs）,we originally propose robust fuzzy control to guarantee the global robust asymptotical stability of TSFNNs.Compared with the existing literature,this paper removes the assumptions on the neuron activations such as Lipschitz conditions,bounded,monotonic increasing property or the right-limit value is bigger than the left one at the discontinuous point.Thus,the results are more general and wider.Finally,two numerical examples are given to show the effectiveness of the proposed stability results.展开更多
In order to overcome the phenomenon of image blur and edge loss in the process of collecting and transmitting medical image,a denoising method of medical image based on discrete wavelet transform(DWT)and modified medi...In order to overcome the phenomenon of image blur and edge loss in the process of collecting and transmitting medical image,a denoising method of medical image based on discrete wavelet transform(DWT)and modified median filter for medical image coupling denoising is proposed.The method is composed of four modules:image acquisition,image storage,image processing and image reconstruction.Image acquisition gets the medical image that contains Gaussian noise and impulse noise.Image storage includes the preservation of data and parameters of the original image and processed image.In the third module,the medical image is decomposed as four sub bands(LL,HL,LH,HH)by wavelet decomposition,where LL is low frequency,LH,HL,HH are respective for horizontal,vertical and in the diagonal line high frequency component.Using improved wavelet threshold to process high frequency coefficients and retain low frequency coefficients,the modified median filtering is performed on three high frequency sub bands after wavelet threshold processing.The last module is image reconstruction,which means getting the image after denoising by wavelet reconstruction.The advantage of this method is combining the advantages of median filter and wavelet to make the denoising effect better,not a simple combination of the two previous methods.With DWT and improved median filter coefficients coupling denoising,it is highly practical for high-precision medical images containing complex noises.The experimental results of proposed algorithm are compared with the results of median filter,wavelet transform,contourlet and DT-CWT,etc.According to visual evaluation index PSNR and SNR and Canny edge detection,in low noise images,PSNR and SNR increase by 10%–15%;in high noise images,PSNR and SNR increase by 2%–6%.The experimental results of the proposed algorithm achieved better acceptable results compared with other methods,which provides an important method for the diagnosis of medical condition.展开更多
The H_∞ performance analysis and controller design for linear networked control systems(NCSs) are presented.The NCSs are considered a linear continuous system with time-varying interval input delay by assuming that t...The H_∞ performance analysis and controller design for linear networked control systems(NCSs) are presented.The NCSs are considered a linear continuous system with time-varying interval input delay by assuming that the sensor is time-driven and the logic Zero-order-holder(ZOH) and controller are event-driven.Based on this model,the delay interval is divided into two equal subintervals for H_∞ performance analysis.An improved H_∞ stabilization condition is obtained in linear matrix inequalities(LMIs) framework by adequately considering the information about the bounds of the input delay to construct novel Lyapunov–Krasovskii functionals(LKFs).For the purpose of reducing the conservatism of the proposed results,the bounds of the LKFs differential cross terms are properly estimated without introducing any slack matrix variables.Moreover,the H_∞ controller is reasonably designed to guarantee the robust asymptotic stability for the linear NCSs with an H_∞ performance level γ.Numerical simulation examples are included to validate the reduced conservatism and effectiveness of our proposed method.展开更多
In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorith...In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorithm is used to identify the occupied subband set(OSS)and the idle subband set(ISS),and then the location and number information of the occupied channels are obtained according to the elements in the OSS.Compared with the classical BMSS methods based on the information theoretic criteria(ITC),the new method shows more excellent performance especially in the low signal-to-noise ratio(SNR)and the small sampling number scenarios,and more robust detection performance in noise uncertainty or unequal noise variance applications.Meanwhile,the new method performs more stablely than the ITC-based methods when the occupied subband number increases or the primary signals suffer multi-path fading.Simulation result verifies the effectiveness of the proposed method.展开更多
One-way roads have potential for improving vehicle speed and reducing traffic delay.Suffering from dense road network,most of adjacent intersections’distance on one-way roads becomes relatively close,which makes isol...One-way roads have potential for improving vehicle speed and reducing traffic delay.Suffering from dense road network,most of adjacent intersections’distance on one-way roads becomes relatively close,which makes isolated control of intersections inefficient in this scene.Thus,it is significant to develop coordinated control of multiple intersection signals on the one-way roads.This paper proposes a signal coordination control method that is suitable for one-way arterial roads.This method uses the cooperation technology of the vehicle infrastructure to collect intersection traffic information and share information among the intersections.Adaptive signal control system is adopted for each intersection in the coordination system,and the green light time is adjusted in real time based on the number of vehicles in queue.The offset and clearance time can be calculated according to the real-time traffic volume.The proposed method was verified with simulation results by VISSIM traffic simulation software.The results compared with other methods show that the coordinated control method proposed in this paper can effectively reduce the average delay of vehicles on the arterial roads and improve the traffic efficiency.展开更多
With the development of automation in smart grids,network reconfiguration is becoming a feasible approach for improving the operation of distribution systems.A novel reconfiguration strategy was presented to get the o...With the development of automation in smart grids,network reconfiguration is becoming a feasible approach for improving the operation of distribution systems.A novel reconfiguration strategy was presented to get the optimal configuration of improving economy of the system,and then identifying the important nodes.In this strategy,the objectives increase the node importance degree and decrease the active power loss subjected to operational constraints.A compound objective function with weight coefficients is formulated to balance the conflict of the objectives.Then a novel quantum particle swarm optimization based on loop switches hierarchical encoded was employed to address the compound objective reconfiguration problem.Its main contribution is the presentation of the hierarchical encoded scheme which is used to generate the population swarm particles of representing only radial connected solutions.Because the candidate solutions are feasible,the search efficiency would improve dramatically during the optimization process without tedious topology verification.To validate the proposed strategy,simulations are carried out on the test systems.The results are compared with other techniques in order to evaluate the performance of the proposed method.展开更多
An analytic electromagnetic calculation method for doubly fed induction generator(DFIG) in wind turbine system was presented. Based on the operation principles, steady state equivalent circuit and basic equations of D...An analytic electromagnetic calculation method for doubly fed induction generator(DFIG) in wind turbine system was presented. Based on the operation principles, steady state equivalent circuit and basic equations of DFIG, the modeling for electromagnetic calculation of DFIG was proposed. The electromagnetic calculation of DFIG was divided into three steps: the magnetic flux calculation, parameters derivation and performance checks. For each step, the detailed numeric calculation formulas were all derived. Combining the calculation formulas, the whole electromagnetic calculation procedure was established, which consisted of three iterative calculation loops, including magnetic saturation coefficient, electromotive force and total output power. All of the electromagnetic and performance data of DIFG can be calculated conveniently by the established calculation procedure, which can be used to evaluate the new designed machine. A 1.5 MW DFIG designed by the proposed procedure was built, for which the whole type tests including no-load test, load test and temperature rising test were carried out. The test results have shown that the DFIG satisfies technical requirements and the test data fit well with the calculation results which prove the correctness of the presented calculation method.展开更多
The performances of repaired image depend on the local information in the repaired area and the consistency between the repair directions with structural content.Image repair algorithm with texture information perform...The performances of repaired image depend on the local information in the repaired area and the consistency between the repair directions with structural content.Image repair algorithm with texture information performs well in repairing seriously damaged images,but it has bad performances when the images have the abundant structure information.The dual optimization image repair algorithm based on the linear structure and the optimal texture is proposed.The algorithm uses the double-constraint sparse model to reconstruct the missed information in large area in order to improve the clarity of repaired images.After adopting the preference of Criminisi priority,the image repair algorithm of self-similarity characteristics is proposed to improve the fault and fuzzy distortion phenomena in the repaired image.The results show that the proposed algorithm has more clarity in the image texture and structure and better effectiveness,and the peak signal-to-noise ratio of the repaired images by proposed algorithm is superior to that by other algorithms.展开更多
A model of correcting the nonlinear error of photoelectric displacement sensor was established based on the least square support vector machine.The parameters of the correcting nonlinear model,such as penalty factor a...A model of correcting the nonlinear error of photoelectric displacement sensor was established based on the least square support vector machine.The parameters of the correcting nonlinear model,such as penalty factor and kernel parameter,were optimized by chaos genetic algorithm.And the nonlinear correction of photoelectric displacement sensor based on least square support vector machine was applied.The application results reveal that error of photoelectric displacement sensor is less than 1.5%,which is rather satisfactory for nonlinear correction of photoelectric displacement sensor.展开更多
In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate tim...In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology.Then,the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space,and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space,Finally,the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model.Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.展开更多
A rate equation approach was presented for the exact computation of the three vertex degree correlations of the fixed act-size collaboration networks.Measurements of the three vertex degree correlations were based on ...A rate equation approach was presented for the exact computation of the three vertex degree correlations of the fixed act-size collaboration networks.Measurements of the three vertex degree correlations were based on a rate equation in the continuous degree and time approximation for the average degree of the nearest neighbors of vertices of degree k,with an appropriate boundary condition.The rate equation proposed can be generalized in more sophisticated growing network models,and also extended to deal with related correlation measurements.Finally,in order to check the theoretical prediction,a numerical example was solved to demonstrate the performance of the degree correlation function.展开更多
A novel grain boundary(GB) model characterized with different angles and positions in the nanowire was set up.By means of device simulator,the effects of grain boundary angle and location on the electrical performance...A novel grain boundary(GB) model characterized with different angles and positions in the nanowire was set up.By means of device simulator,the effects of grain boundary angle and location on the electrical performance of ZnO nanowire FET(Nanowire Field-Effect Transistor) with a wrap-around gate configuration,were explored.With the increase of the grain boundary angle,the electrical performance degrades gradually.When a grain boundary with a smaller angle,such as 5° GB,is located close to the source or drain electrode,the grain boundary is partially depleted by an electric field peak,which leads to the decrease of electron concentration and the degradation of transistor characteristics.When the 90° GB is located at the center of the nanowire,the action of the electric field is balanced out,so the electrical performance of transistor is better than that of the 90° GB located at the other positions.展开更多
Modeling method for the current control loop of a grid-connected PWM inverter with the LCL output filter was discussed.Firstly,the current control loop with the LCL inverter-side current as feedback was established.Th...Modeling method for the current control loop of a grid-connected PWM inverter with the LCL output filter was discussed.Firstly,the current control loop with the LCL inverter-side current as feedback was established.Then,parameters of PI controller were calculated on the basis of an equivalent controlled object.Finally,Norton equivalent circuit for the current control loop of grid-connected system was derived by integrating one control equation,which connected the PWM inverter output voltage and the LCL inverter-side current,with two circuit equations,separately using the LCL inverter-side current and the injected current as loop currents.With the induced Norton equivalent circuit,system-level resonant and unstable issues on real grid-connected system applied in weak distributed power systems can be easily analyzed.The validity of substituting Norton equivalent circuit for grid-connected system is verified by simulation and experiment.展开更多
To ensure the quality and safety of pure milk,detection method of typical preservative-potassium sorbate in milk was researched in this paper.Hyperspectral imaging technology was applied to realize rapid detection.Inf...To ensure the quality and safety of pure milk,detection method of typical preservative-potassium sorbate in milk was researched in this paper.Hyperspectral imaging technology was applied to realize rapid detection.Influence factors for hyperspectral data collection for milk samples were firstly researched,including height of sample,bottom color and sample filled up container or not.Pretreatment methods and variable selection algorithms were applied into original spectral data.Rapid detection models were built based on support vector machine method(SVM).Finally,standard normalized variable(SNV)-competitive adaptive reweighted sampling(CARS)and SVM model was chosen in this paper.The accuracies of calibration set and testing set were 0.97 and 0.97,respectively.Kappa coefficient of the model was 0.93.It could be seen that hyperspectral imaging technology could be used to detect for potassium sorbate in milk.Meanwhile,it also provided methodological supports for the rapid detection of other preservatives in milk.展开更多
基金Project(61563032)supported by the National Natural Science Foundation of ChinaProject(18JR3RA133)supported by Gansu Basic Research Innovation Group,China
文摘Microbial fuel cell(MFC)is a kind of promising clean power supply energy equipment,but serious nonlinearities and disturbances exist when the MFC runs,and it is an important topic to guarantee that the output voltage reaches the setting value quickly and smoothly.Regulating the feeding flow is an effective way to achieve this goal,and especially,the satisfactory results can be achieved by regulating anode feeding flow.In this work,a feedforward fuzzy logic PID algorithm is proposed.The fuzzy logic system is introduced to deal with the non-linear dynamics of MFC,and corresponding PID parameters are calculated according to defuzzification.The magnitude value of the current density is used to simulate the value of the external load.The simulation results indicate that the MFC output voltage can track the setting value quickly and smoothly with the proposed feedforward fuzzy logic PID algorithm.The proposed algorithm is more efficient and robust with respect to anti-disturbance performance and tracking accuracy than other three control methods.
基金Project(61671204)supported by National Natural Science Foundation of ChinaProject(2016WK2001)supported by Hunan Provincial Key R&D Plan,China。
文摘Face anti-spoofing is a relatively important part of the face recognition system,which has great significance for financial payment and access control systems.Aiming at the problems of unstable face alignment,complex lighting,and complex structure of face anti-spoofing detection network,a novel method is presented using a combination of convolutional neural network and brightness equalization.Firstly,multi-task convolutional neural network(MTCNN)based on the cascade of three convolutional neural networks(CNNs),P-net,R-net,and O-net are used to achieve accurate positioning of the face,and the detected face bounding box is cropped by a specified multiple,then brightness equalization is adopted to perform brightness compensation on different brightness areas of the face image.Finally,data features are extracted and classification is given by utilizing a 12-layer convolution neural network.Experiments of the proposed algorithm were carried out on CASIA-FASD.The results show that the classification accuracy is relatively high,and the half total error rate(HTER)reaches 1.02%.
基金Project(50977003) supported by the National Natural Science Foundation of China
文摘In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(FAHP) and artificial neural network(ANN) from the perspective of accuracy and quickness is proposed.An analytic hierarchy process model for the transformer risk assessment is built by analysis of the risk factors affecting the transformer risk level and the weight relation of each risk factor in transformer risk calculation is analyzed by application of fuzzy consistency judgment matrix;with utilization of adaptive ability and nonlinear mapping ability of the ANN,the risk factors with large weights are used as input of neutral network,and thus intelligent quantitative assessment of transformer risk is realized.The simulation result shows that the proposed method increases the speed and accuracy of the risk assessment and can provide feasible decision basis for the transformer risk management and maintenance decisions.
基金supported by the National Natural Science Foundation of China(6077504760835004)+2 种基金the National High Technology Research and Development Program of China(863 Program)(2007AA04Z244 2008AA04Z214)the Graduate Innovation Fundation of Hunan Province(CX2010B132)
文摘The problem of global robust asymptotical stability for a class of Takagi-Sugeno fuzzy neural networks（TSFNN） with discontinuous activation functions and time delays is investigated by using Lyapunov stability theory.Based on linear matrix inequalities（LMIs）,we originally propose robust fuzzy control to guarantee the global robust asymptotical stability of TSFNNs.Compared with the existing literature,this paper removes the assumptions on the neuron activations such as Lipschitz conditions,bounded,monotonic increasing property or the right-limit value is bigger than the left one at the discontinuous point.Thus,the results are more general and wider.Finally,two numerical examples are given to show the effectiveness of the proposed stability results.
基金Project(2016JJ4074)supported by the Natural Science Foundation of Hunan Province,ChinaProject(14C0920)supported by the Hunan Provincial Education Department,ChinaProject(61771191)supported by the National Natural Science Foundation of China
文摘In order to overcome the phenomenon of image blur and edge loss in the process of collecting and transmitting medical image,a denoising method of medical image based on discrete wavelet transform(DWT)and modified median filter for medical image coupling denoising is proposed.The method is composed of four modules:image acquisition,image storage,image processing and image reconstruction.Image acquisition gets the medical image that contains Gaussian noise and impulse noise.Image storage includes the preservation of data and parameters of the original image and processed image.In the third module,the medical image is decomposed as four sub bands(LL,HL,LH,HH)by wavelet decomposition,where LL is low frequency,LH,HL,HH are respective for horizontal,vertical and in the diagonal line high frequency component.Using improved wavelet threshold to process high frequency coefficients and retain low frequency coefficients,the modified median filtering is performed on three high frequency sub bands after wavelet threshold processing.The last module is image reconstruction,which means getting the image after denoising by wavelet reconstruction.The advantage of this method is combining the advantages of median filter and wavelet to make the denoising effect better,not a simple combination of the two previous methods.With DWT and improved median filter coefficients coupling denoising,it is highly practical for high-precision medical images containing complex noises.The experimental results of proposed algorithm are compared with the results of median filter,wavelet transform,contourlet and DT-CWT,etc.According to visual evaluation index PSNR and SNR and Canny edge detection,in low noise images,PSNR and SNR increase by 10%–15%;in high noise images,PSNR and SNR increase by 2%–6%.The experimental results of the proposed algorithm achieved better acceptable results compared with other methods,which provides an important method for the diagnosis of medical condition.
基金Supported by National Natural Science Foundation of China （60974148）, Program for New Century Excellent Talents in University （NCET-10-0097）, Sichuan Youth Science and Technology Fund （2011JQ0011）, Southwest University for Nationalities Construction Projects for Graduate Degree Programs （2011XWD-S0805）, and Southwest University for Nationalities Fundamental Research Funds for the Central Universities （12NZYTH01）
基金Project (61304046) supported by the National Natural Science Funds for Young Scholar of ChinaProject (F201242) supported by Natural Science Foundation of Heilongjiang Province,China
文摘The H_∞ performance analysis and controller design for linear networked control systems(NCSs) are presented.The NCSs are considered a linear continuous system with time-varying interval input delay by assuming that the sensor is time-driven and the logic Zero-order-holder(ZOH) and controller are event-driven.Based on this model,the delay interval is divided into two equal subintervals for H_∞ performance analysis.An improved H_∞ stabilization condition is obtained in linear matrix inequalities(LMIs) framework by adequately considering the information about the bounds of the input delay to construct novel Lyapunov–Krasovskii functionals(LKFs).For the purpose of reducing the conservatism of the proposed results,the bounds of the LKFs differential cross terms are properly estimated without introducing any slack matrix variables.Moreover,the H_∞ controller is reasonably designed to guarantee the robust asymptotic stability for the linear NCSs with an H_∞ performance level γ.Numerical simulation examples are included to validate the reduced conservatism and effectiveness of our proposed method.
基金Projects(61362018,61861019)supported by the National Natural Science Foundation of ChinaProject(1402041B)supported by the Jiangsu Province Postdoctoral Scientific Research Project,China+1 种基金Project(16A174)supported by the Scientific Research Fund of Hunan Provincial Education Department,ChinaProject([2016]283)supported by the Research Study and Innovative Experiment Project of College Students,China
文摘In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorithm is used to identify the occupied subband set(OSS)and the idle subband set(ISS),and then the location and number information of the occupied channels are obtained according to the elements in the OSS.Compared with the classical BMSS methods based on the information theoretic criteria(ITC),the new method shows more excellent performance especially in the low signal-to-noise ratio(SNR)and the small sampling number scenarios,and more robust detection performance in noise uncertainty or unequal noise variance applications.Meanwhile,the new method performs more stablely than the ITC-based methods when the occupied subband number increases or the primary signals suffer multi-path fading.Simulation result verifies the effectiveness of the proposed method.
基金Project(61503048)supported by the National Natural Science Foundation of ChinaProjects(16C0050,16C0062)supported by Scientific Research Project of Hunan Provincial Department of Education,China
文摘One-way roads have potential for improving vehicle speed and reducing traffic delay.Suffering from dense road network,most of adjacent intersections’distance on one-way roads becomes relatively close,which makes isolated control of intersections inefficient in this scene.Thus,it is significant to develop coordinated control of multiple intersection signals on the one-way roads.This paper proposes a signal coordination control method that is suitable for one-way arterial roads.This method uses the cooperation technology of the vehicle infrastructure to collect intersection traffic information and share information among the intersections.Adaptive signal control system is adopted for each intersection in the coordination system,and the green light time is adjusted in real time based on the number of vehicles in queue.The offset and clearance time can be calculated according to the real-time traffic volume.The proposed method was verified with simulation results by VISSIM traffic simulation software.The results compared with other methods show that the coordinated control method proposed in this paper can effectively reduce the average delay of vehicles on the arterial roads and improve the traffic efficiency.
基金Project(61102039)supported by the National Natural Science Foundation of ChinaProject(2014AA052600)supported by National Hi-tech Research and Development Plan,China
文摘With the development of automation in smart grids,network reconfiguration is becoming a feasible approach for improving the operation of distribution systems.A novel reconfiguration strategy was presented to get the optimal configuration of improving economy of the system,and then identifying the important nodes.In this strategy,the objectives increase the node importance degree and decrease the active power loss subjected to operational constraints.A compound objective function with weight coefficients is formulated to balance the conflict of the objectives.Then a novel quantum particle swarm optimization based on loop switches hierarchical encoded was employed to address the compound objective reconfiguration problem.Its main contribution is the presentation of the hierarchical encoded scheme which is used to generate the population swarm particles of representing only radial connected solutions.Because the candidate solutions are feasible,the search efficiency would improve dramatically during the optimization process without tedious topology verification.To validate the proposed strategy,simulations are carried out on the test systems.The results are compared with other techniques in order to evaluate the performance of the proposed method.
基金Project(2011DFA62240) supported by the International Scientific and Technological Cooperation Projects,ChinaProject(019945-SES6) supported by the European Union(EU)6th Framework Program UP-WIND Project,Denmark
文摘An analytic electromagnetic calculation method for doubly fed induction generator(DFIG) in wind turbine system was presented. Based on the operation principles, steady state equivalent circuit and basic equations of DFIG, the modeling for electromagnetic calculation of DFIG was proposed. The electromagnetic calculation of DFIG was divided into three steps: the magnetic flux calculation, parameters derivation and performance checks. For each step, the detailed numeric calculation formulas were all derived. Combining the calculation formulas, the whole electromagnetic calculation procedure was established, which consisted of three iterative calculation loops, including magnetic saturation coefficient, electromotive force and total output power. All of the electromagnetic and performance data of DIFG can be calculated conveniently by the established calculation procedure, which can be used to evaluate the new designed machine. A 1.5 MW DFIG designed by the proposed procedure was built, for which the whole type tests including no-load test, load test and temperature rising test were carried out. The test results have shown that the DFIG satisfies technical requirements and the test data fit well with the calculation results which prove the correctness of the presented calculation method.
基金Project(12GJ6055)supported by the Natural Science Foundation of Hunan Province,ChinaProject(2010FJ4107)supported by Hunan Provincial Science and Technology Department,China
文摘The performances of repaired image depend on the local information in the repaired area and the consistency between the repair directions with structural content.Image repair algorithm with texture information performs well in repairing seriously damaged images,but it has bad performances when the images have the abundant structure information.The dual optimization image repair algorithm based on the linear structure and the optimal texture is proposed.The algorithm uses the double-constraint sparse model to reconstruct the missed information in large area in order to improve the clarity of repaired images.After adopting the preference of Criminisi priority,the image repair algorithm of self-similarity characteristics is proposed to improve the fault and fuzzy distortion phenomena in the repaired image.The results show that the proposed algorithm has more clarity in the image texture and structure and better effectiveness,and the peak signal-to-noise ratio of the repaired images by proposed algorithm is superior to that by other algorithms.
基金Project(50925727) supported by the National Fund for Distinguish Young Scholars of ChinaProject(60876022) supported by the National Natural Science Foundation of China+1 种基金Project(2010FJ4141) supported by Hunan Provincial Science and Technology Foundation,ChinaProject supported by the Fund of the Key Construction Academic Subject (Optics) of Hunan Province,China
文摘A model of correcting the nonlinear error of photoelectric displacement sensor was established based on the least square support vector machine.The parameters of the correcting nonlinear model,such as penalty factor and kernel parameter,were optimized by chaos genetic algorithm.And the nonlinear correction of photoelectric displacement sensor based on least square support vector machine was applied.The application results reveal that error of photoelectric displacement sensor is less than 1.5%,which is rather satisfactory for nonlinear correction of photoelectric displacement sensor.
基金Project(61025015) supported by the National Natural Science Funds for Distinguished Young Scholars of ChinaProject(21106036) supported by the National Natural Science Foundation of China+2 种基金Project(200805331103) supported by Research Fund for the Doctoral Program of Higher Education of ChinaProject(NCET-08-0576) supported by Program for New Century Excellent Talents in Universities of ChinaProject(11B038) supported by Scientific Research Fund for the Excellent Youth Scholars of Hunan Provincial Education Department,China
文摘In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology.Then,the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space,and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space,Finally,the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model.Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.
基金Project(20090162110058) supported by the Research Fund for the Doctoral Program of Higher Education of ChinaProject(KJ101210) supported by the Foundation of Chongqing Municipal Education Committee,China Project(2009GK3010) supported by the Hunan Science & Technology Foundation,China
文摘A rate equation approach was presented for the exact computation of the three vertex degree correlations of the fixed act-size collaboration networks.Measurements of the three vertex degree correlations were based on a rate equation in the continuous degree and time approximation for the average degree of the nearest neighbors of vertices of degree k,with an appropriate boundary condition.The rate equation proposed can be generalized in more sophisticated growing network models,and also extended to deal with related correlation measurements.Finally,in order to check the theoretical prediction,a numerical example was solved to demonstrate the performance of the degree correlation function.
基金Project(60876022) supported by the National Natural Science Foundation of ChinaProject(50925727) supported by the National Natural Science Funds for Distinguished Young Scholars of China
文摘A novel grain boundary(GB) model characterized with different angles and positions in the nanowire was set up.By means of device simulator,the effects of grain boundary angle and location on the electrical performance of ZnO nanowire FET(Nanowire Field-Effect Transistor) with a wrap-around gate configuration,were explored.With the increase of the grain boundary angle,the electrical performance degrades gradually.When a grain boundary with a smaller angle,such as 5° GB,is located close to the source or drain electrode,the grain boundary is partially depleted by an electric field peak,which leads to the decrease of electron concentration and the degradation of transistor characteristics.When the 90° GB is located at the center of the nanowire,the action of the electric field is balanced out,so the electrical performance of transistor is better than that of the 90° GB located at the other positions.
基金Project(51307009)supported by the National Natural Science Foundation of ChinaProject(12JJ4045)supported by Hunan Provincial Natural Science Foundation,China+2 种基金Project(2011KFJJ003)supported by the Key Laboratory for Power Technology of Renewable Energy Sources of Hunan Province,ChinaProject(2011kfj14)supported by the Fund of Key Laboratory of Hunan Province about Power System Operation and Control,ChinaProject(454.13S-20)supported by the Enterprises’Postdoctoral Funds of Pudong Area of Shanghai,China
文摘Modeling method for the current control loop of a grid-connected PWM inverter with the LCL output filter was discussed.Firstly,the current control loop with the LCL inverter-side current as feedback was established.Then,parameters of PI controller were calculated on the basis of an equivalent controlled object.Finally,Norton equivalent circuit for the current control loop of grid-connected system was derived by integrating one control equation,which connected the PWM inverter output voltage and the LCL inverter-side current,with two circuit equations,separately using the LCL inverter-side current and the injected current as loop currents.With the induced Norton equivalent circuit,system-level resonant and unstable issues on real grid-connected system applied in weak distributed power systems can be easily analyzed.The validity of substituting Norton equivalent circuit for grid-connected system is verified by simulation and experiment.
基金Supported by the National Key Research and Development Program of China(2016YFD0700204-02)China Agriculture Research System(CARS-36)Heilongjiang Post-doctoral Subsidy Project of China(LBH-Z17020)。
文摘To ensure the quality and safety of pure milk,detection method of typical preservative-potassium sorbate in milk was researched in this paper.Hyperspectral imaging technology was applied to realize rapid detection.Influence factors for hyperspectral data collection for milk samples were firstly researched,including height of sample,bottom color and sample filled up container or not.Pretreatment methods and variable selection algorithms were applied into original spectral data.Rapid detection models were built based on support vector machine method(SVM).Finally,standard normalized variable(SNV)-competitive adaptive reweighted sampling(CARS)and SVM model was chosen in this paper.The accuracies of calibration set and testing set were 0.97 and 0.97,respectively.Kappa coefficient of the model was 0.93.It could be seen that hyperspectral imaging technology could be used to detect for potassium sorbate in milk.Meanwhile,it also provided methodological supports for the rapid detection of other preservatives in milk.
