Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest developments and achievements in both theoretical and pra...Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest developments and achievements in both theoretical and practical aspects of systems engineering,electronics and related research areas.The journal welcomes high quality original papers from a wide range of countries.The scope of the journal includes systems engineering,military systems,electronic technology,defense electronic technology,control theory and practice,software algorithm and simulation,reliability,computer development and application,and other topics in all related fields.展开更多
Titanium-based semiconductors are known for their high chemical stability and suitable band gap widths.However,the conventional experimental screening methods are inefficient due to the wide variety of materials.To sp...Titanium-based semiconductors are known for their high chemical stability and suitable band gap widths.However,the conventional experimental screening methods are inefficient due to the wide variety of materials.To speed up the selection process,this work focuses on interpretable feature learning and band gap prediction for titanium-based semiconductors.First,titanium compounds were selected from the Materials Project database by machine learning,and elemental features were extracted using the Magpie descriptors.Then,principal component analysis(PCA)was applied to reduce the data dimensionality,creating a representative dataset.Meantime,heatmaps and SHAP(SHapley Additive exPlanations)methods were used to demonstrate the influence of key features such as electronegativity,covalent radius,period number,and unit cell volume on the bandgap,understanding the relationship between the material’s properties and performance.After comparing different machine learning models,including Random Forest(RF),Support Vector Machines(SVM),Linear Regression(LR),and Gradient Boosting Regression(GBR),the RF was found to be the most accurate for band gap prediction.Finally,the model performance was improved through parameter tuning,showing high accuracy.These findings provide strong data support and design guidance for the development of materials in fields like photocatalysis and solar cells.展开更多
This paper presents the design of an experimental battlefield dynamic scanning and staring imaging system based on a fast steering mirror(FSM), which is capable of real-time monitoring of hot targets and wide-area rec...This paper presents the design of an experimental battlefield dynamic scanning and staring imaging system based on a fast steering mirror(FSM), which is capable of real-time monitoring of hot targets and wide-area reconnaissance of hot regions. First,the working principle and working sequence of the FSM are briefly analyzed. The mathematical model of the FSM system is built by modeling its dynamic and electrical properties, and the rationality of the model is validated by means of model identification. Second,the influence of external sources of disturbance such as the carrier and moment on the control precision of the FSM is effectively suppressed by the jointly controlling of proportional integral(PI)and disturbance observer(DOB), thus realizing a high precision and strong robustness control of the FSM system. Then, this paper designs an experimental prototype and introduces a special optical structure to enable the infrared camera to share the FSM with the visible light camera. Finally, the influence of the velocity difference between the mirror of the FSM and the rotating platform on the imaging quality of the system is experimentally analyzed by using the image sharpness evaluation method based on point sharpness. A good dynamic scanning and staring imaging result is achieved when the velocity of these two components correspond.展开更多
Considering the relatively poor robustness of quality scores for different types of distortion and the lack of mechanism for determining distortion types, a no-reference image quality assessment(NR-IQA) method based o...Considering the relatively poor robustness of quality scores for different types of distortion and the lack of mechanism for determining distortion types, a no-reference image quality assessment(NR-IQA) method based on the Ada Boost BP neural network in the wavelet domain(WABNN) is proposed. A 36-dimensional image feature vector is constructed by extracting natural scene statistics(NSS) features and local information entropy features of the distorted image wavelet sub-band coefficients in three scales. The ABNN classifier is obtained by learning the relationship between image features and distortion types. The ABNN scorer is obtained by learning the relationship between image features and image quality scores. A series of contrast experiments are carried out in the laboratory of image and video engineering(LIVE) database and TID2013 database. Experimental results show the high accuracy of the distinguishing distortion type, the high consistency with subjective scores and the high robustness of the method for distorted images. Experiment results also show the independence of the database and the relatively high operation efficiency of this method.展开更多
A new normalized least mean square(NLMS) adaptive filter is first derived from a cost function, which incorporates the conventional one of the NLMS with a minimum-disturbance(MD)constraint. A variable regularization f...A new normalized least mean square(NLMS) adaptive filter is first derived from a cost function, which incorporates the conventional one of the NLMS with a minimum-disturbance(MD)constraint. A variable regularization factor(RF) is then employed to control the contribution made by the MD constraint in the cost function. Analysis results show that the RF can be taken as a combination of the step size and regularization parameter in the conventional NLMS. This implies that these parameters can be jointly controlled by simply tuning the RF as the proposed algorithm does. It also demonstrates that the RF can accelerate the convergence rate of the proposed algorithm and its optimal value can be obtained by minimizing the squared noise-free posteriori error. A method for automatically determining the value of the RF is also presented, which is free of any prior knowledge of the noise. While simulation results verify the analytical ones, it is also illustrated that the performance of the proposed algorithm is superior to the state-of-art ones in both the steady-state misalignment and the convergence rate. A novel algorithm is proposed to solve some problems. Simulation results show the effectiveness of the proposed algorithm.展开更多
Inference are considered for the dependence competing risks model by using the Marshal-Olkin bivariate exponential distribution. Under generalized progressively hybrid censoring with partially observed failure causes,...Inference are considered for the dependence competing risks model by using the Marshal-Olkin bivariate exponential distribution. Under generalized progressively hybrid censoring with partially observed failure causes, the maximum likelihood estimators are established, and the approximate confidence intervals are also constructed via the observed Fisher information matrix.Moreover, Bayes estimates and highest probability density credible intervals are presented and the importance sampling technique is used to compute corresponding results. Finally, the numerical analysis is proposed for illustration.展开更多
The paper presents the conceptual and operational basis of the creation of IDSS based on our recent research experience. In this paper, an intelligent decision support system, IDSS is defined as: any interactive syste...The paper presents the conceptual and operational basis of the creation of IDSS based on our recent research experience. In this paper, an intelligent decision support system, IDSS is defined as: any interactive system that is specially designed to improve the decision making of its user by extending the user's cognitive decision making abilities. As a result, this view of man-machine joint cognitive system stresses the need to use computational technology to aid the user in the decision making process. And the human's role is to achieve total systems's objectives. The paper outlines the designing procedure in successive steps. First, the decision maker's cognitive needs for decision support are identified. Second, the computationally realizable support functions are defined that could be provided by IDSS. Then, the specific techniques that would best fill the decision needs are discussed. And finally, for system implementation the modern computational technology infrastructure is emphasized.展开更多
While moving ahead with the object detection technology, especially deep neural networks, many related tasks, such as medical application and industrial automation, have achieved great success. However, the detection ...While moving ahead with the object detection technology, especially deep neural networks, many related tasks, such as medical application and industrial automation, have achieved great success. However, the detection of objects with multiple aspect ratios and scales is still a key problem. This paper proposes a top-down and bottom-up feature pyramid network(TDBU-FPN),which combines multi-scale feature representation and anchor generation at multiple aspect ratios. First, in order to build the multi-scale feature map, this paper puts a number of fully convolutional layers after the backbone. Second, to link neighboring feature maps, top-down and bottom-up flows are adopted to introduce context information via top-down flow and supplement suboriginal information via bottom-up flow. The top-down flow refers to the deconvolution procedure, and the bottom-up flow refers to the pooling procedure. Third, the problem of adapting different object aspect ratios is tackled via many anchor shapes with different aspect ratios on each multi-scale feature map. The proposed method is evaluated on the pattern analysis, statistical modeling and computational learning visual object classes(PASCAL VOC)dataset and reaches an accuracy of 79%, which exhibits a 1.8% improvement with a detection speed of 23 fps.展开更多
To solve the problem of distributed tasks-platforms scheduling in holonic command and control(C2) organization,the basic elements of the organization are analyzed firstly and the formal description of organizational e...To solve the problem of distributed tasks-platforms scheduling in holonic command and control(C2) organization,the basic elements of the organization are analyzed firstly and the formal description of organizational elements and structure is provided. Based on the improvement of task execution quality,a single task resource scheduling model is established and the solving method based on the m-best algorithm is proposed. For the problem of tactical decision-holon cannot handle tasks with low priority effectively, a distributed resource scheduling collaboration mechanism based on platform pricing and a platform exchange mechanism based on resource capacities are designed. Finally,a series of experiments are designed to prove the effectiveness of these methods. The results show that the proposed distributed scheduling methods can realize the effective balance of platform resources.展开更多
How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classif...How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.展开更多
A smart homing guidance strategy with control saturation against a target-defender team is derived. It is noteworthy that a cooperative strategy of the target-defender team is applied,which has been proved more challe...A smart homing guidance strategy with control saturation against a target-defender team is derived. It is noteworthy that a cooperative strategy of the target-defender team is applied,which has been proved more challenging for the homing guidance.The defender missile is launched by the target and guided by a cooperative augmented proportional navigation(APN). At the same time, the target performs a one-switch maneuver to cooperate and minimize the defender's acceleration requirement. The problem is analyzed for arbitrary-order linear dynamics of the agents in the linearized form but validated by the mathematical simulations by using nonlinear kinematics. The perfect information of three agents' states is assumed. Then, a method to deal with the target-defender team is proposed. It contains a combined performance index penalizing the miss distance relative to the target and energy consumption in the whole duration. Besides, the specific miss distance related to the defender is regarded as an inequality constraint. An analytical solution for the smart guidance strategy against the APN guided defender is derived. Meanwhile, the control saturations are introduced to get more realistic and reasonable insights to this practical target-missile-defender problem. A simple but effective iterative searching technique is proposed to determine the saturation time points. The solution provides an optimal homing strategy to evade the defender with a specific miss distance and intercept the target with the minimum miss distance in the minimum energy manner. Nonlinear two-dimensional simulation results are used to validate the theoretical analysis. By comparison with the optimal differential game guidance(ODGG) and the combined minimum effort guidance(CMEG), the superiority of this smart guidance strategy is concluded.展开更多
This paper presents a brief summary of the three development stages of investigation on the transpiration cooling and its control for aircraft, missiles and electromagnetic gun, then the control problem of the distrib...This paper presents a brief summary of the three development stages of investigation on the transpiration cooling and its control for aircraft, missiles and electromagnetic gun, then the control problem of the distributed parameters system with a moving boundary is derived. It introduces the mathematical model of the transpiration cooling control, its control characteristics, and the present situation of the experimental and theoretical study on this problem. This paper also describes the main study results and the existing problems. The prospective application is also reported. The major references in every developing stage are listed systematically for further study.展开更多
In this paper two classes of equivalence transform methods for solving ordinary differential equations are proposed. One class of method is the equivalence integral transform method for special differential algebraic ...In this paper two classes of equivalence transform methods for solving ordinary differential equations are proposed. One class of method is the equivalence integral transform method for special differential algebraic problems. The advantage of this class of method is such that the amount of work calculating one integration with parameters becomes that of two interpolations, when the system of nonlinear equations is solved on the right hand side function. The other class of method is the equivalence substitution method for avoiding calculating derivative on the right hand side function. In order to avoid calculation derivatives, two equivalence substitution methods are proposed here. The application instances of some special effect of the equivalence substitution methods are given.展开更多
The history of the development of Chinese telemetry is introduced in the paper. The new telemetry ground station and the new onboard space telemetry system, with the idea of systematic design and the specification, ar...The history of the development of Chinese telemetry is introduced in the paper. The new telemetry ground station and the new onboard space telemetry system, with the idea of systematic design and the specification, are described.展开更多
The formation of the manned aerial vehicle/unmanned aerial vehicle(MAV/UAV) task coalition is considered. To reduce the scale of the problem, the formation progress is divided into three phases. For the task clusterin...The formation of the manned aerial vehicle/unmanned aerial vehicle(MAV/UAV) task coalition is considered. To reduce the scale of the problem, the formation progress is divided into three phases. For the task clustering phase, the geographical position of tasks is taken into consideration and a cluster method is proposed. For the UAV allocation phase, the UAV requirement for both constrained and unconstrained resources is introduced, and a multi-objective optimal algorithm is proposed to solve the allocation problem. For the MAV allocation phase, the optimal model is firstly constructed and it is decomposed according to the ideal of greed to reduce the time complexity of the algorithm. Based on the above phases, the MAV/UAV task coalition formation method is proposed and the effectiveness and practicability are demonstrated by simulation examples.展开更多
The Department of Water Resources and Harbour Engineering was originally a division of hydraulic engineering in the Department of Civil Engineering in Peiyang University the first modern university founded in China in...The Department of Water Resources and Harbour Engineering was originally a division of hydraulic engineering in the Department of Civil Engineering in Peiyang University the first modern university founded in China in 1933. Since then, about 5000 students have graduated from the Department.展开更多
Middle censoring is an important censoring scheme,in which the actual failure data of an observation becomes unobservable if it falls into a random interval. This paper considers the statistical analysis of the depend...Middle censoring is an important censoring scheme,in which the actual failure data of an observation becomes unobservable if it falls into a random interval. This paper considers the statistical analysis of the dependent competing risks model by using the Marshall-Olkin bivariate Weibull(MOBW) distribution.The maximum likelihood estimations(MLEs), midpoint approximation(MPA) estimations and approximate confidence intervals(ACIs) of the unknown parameters are obtained. In addition, the Bayes approach is also considered based on the Gamma-Dirichlet prior of the scale parameters, with the given shape parameter.The acceptance-rejection sampling method is used to obtain the Bayes estimations and construct credible intervals(CIs). Finally,two numerical examples are used to show the performance of the proposed methods.展开更多
Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest develop ments and achievements in both theoretical and pr...Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest develop ments and achievements in both theoretical and practical aspects of systems engineering,electronics and related research areas.The journal welcomes high quality original papers from a wide range of countries.展开更多
Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest develop-ments and achievements in both theoretical and pr...Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest develop-ments and achievements in both theoretical and practical aspects of systems engineering,electronicsand related research areas.展开更多
For the target threat evaluation of warships formation air defense, the sample data are frequently insufficient and even incomplete. The existing evaluation methods rely too much on expertise and are difficult to carr...For the target threat evaluation of warships formation air defense, the sample data are frequently insufficient and even incomplete. The existing evaluation methods rely too much on expertise and are difficult to carry out for the dynamic evaluation on time series. In order to solve these problems, a threat evaluation method based on the AR(p)(auto regressive(AR))-dynamic improved technique for order preference by similarity to ideal solution(DITOPSIS) method is proposed. The AR(p) model is adopted to predict the missing data on the time series. Then, the entropy weight method is applied to solve each index weight at the objective point. Kullback-Leibler divergence(KLD) is used to improve the traditional TOPSIS, and to carry out the target threat evaluation. The Poisson distribution is used to assign the weight value.Simulation results show that the improved AR(p)-DITOPSIS threat evaluation method can synthetically take into account the target threat degree in time series and is more suitable for the threat evaluation under the condition of missing the target data than the traditional TOPSIS method.展开更多
文摘Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest developments and achievements in both theoretical and practical aspects of systems engineering,electronics and related research areas.The journal welcomes high quality original papers from a wide range of countries.The scope of the journal includes systems engineering,military systems,electronic technology,defense electronic technology,control theory and practice,software algorithm and simulation,reliability,computer development and application,and other topics in all related fields.
文摘Titanium-based semiconductors are known for their high chemical stability and suitable band gap widths.However,the conventional experimental screening methods are inefficient due to the wide variety of materials.To speed up the selection process,this work focuses on interpretable feature learning and band gap prediction for titanium-based semiconductors.First,titanium compounds were selected from the Materials Project database by machine learning,and elemental features were extracted using the Magpie descriptors.Then,principal component analysis(PCA)was applied to reduce the data dimensionality,creating a representative dataset.Meantime,heatmaps and SHAP(SHapley Additive exPlanations)methods were used to demonstrate the influence of key features such as electronegativity,covalent radius,period number,and unit cell volume on the bandgap,understanding the relationship between the material’s properties and performance.After comparing different machine learning models,including Random Forest(RF),Support Vector Machines(SVM),Linear Regression(LR),and Gradient Boosting Regression(GBR),the RF was found to be the most accurate for band gap prediction.Finally,the model performance was improved through parameter tuning,showing high accuracy.These findings provide strong data support and design guidance for the development of materials in fields like photocatalysis and solar cells.
基金supported by the National Defense Pre-research Project of China during the 12th Five-year Plan Period(4040570201)Innovation Project of Military Academy(ZYX14060014)
文摘This paper presents the design of an experimental battlefield dynamic scanning and staring imaging system based on a fast steering mirror(FSM), which is capable of real-time monitoring of hot targets and wide-area reconnaissance of hot regions. First,the working principle and working sequence of the FSM are briefly analyzed. The mathematical model of the FSM system is built by modeling its dynamic and electrical properties, and the rationality of the model is validated by means of model identification. Second,the influence of external sources of disturbance such as the carrier and moment on the control precision of the FSM is effectively suppressed by the jointly controlling of proportional integral(PI)and disturbance observer(DOB), thus realizing a high precision and strong robustness control of the FSM system. Then, this paper designs an experimental prototype and introduces a special optical structure to enable the infrared camera to share the FSM with the visible light camera. Finally, the influence of the velocity difference between the mirror of the FSM and the rotating platform on the imaging quality of the system is experimentally analyzed by using the image sharpness evaluation method based on point sharpness. A good dynamic scanning and staring imaging result is achieved when the velocity of these two components correspond.
基金supported by the National Natural Science Foundation of China(61471194 61705104)+1 种基金the Science and Technology on Avionics Integration Laboratory and Aeronautical Science Foundation of China(20155552050)the Natural Science Foundation of Jiangsu Province(BK20170804)
文摘Considering the relatively poor robustness of quality scores for different types of distortion and the lack of mechanism for determining distortion types, a no-reference image quality assessment(NR-IQA) method based on the Ada Boost BP neural network in the wavelet domain(WABNN) is proposed. A 36-dimensional image feature vector is constructed by extracting natural scene statistics(NSS) features and local information entropy features of the distorted image wavelet sub-band coefficients in three scales. The ABNN classifier is obtained by learning the relationship between image features and distortion types. The ABNN scorer is obtained by learning the relationship between image features and image quality scores. A series of contrast experiments are carried out in the laboratory of image and video engineering(LIVE) database and TID2013 database. Experimental results show the high accuracy of the distinguishing distortion type, the high consistency with subjective scores and the high robustness of the method for distorted images. Experiment results also show the independence of the database and the relatively high operation efficiency of this method.
基金supported by the National Natural Science Foundation of China(61571131 11604055)
文摘A new normalized least mean square(NLMS) adaptive filter is first derived from a cost function, which incorporates the conventional one of the NLMS with a minimum-disturbance(MD)constraint. A variable regularization factor(RF) is then employed to control the contribution made by the MD constraint in the cost function. Analysis results show that the RF can be taken as a combination of the step size and regularization parameter in the conventional NLMS. This implies that these parameters can be jointly controlled by simply tuning the RF as the proposed algorithm does. It also demonstrates that the RF can accelerate the convergence rate of the proposed algorithm and its optimal value can be obtained by minimizing the squared noise-free posteriori error. A method for automatically determining the value of the RF is also presented, which is free of any prior knowledge of the noise. While simulation results verify the analytical ones, it is also illustrated that the performance of the proposed algorithm is superior to the state-of-art ones in both the steady-state misalignment and the convergence rate. A novel algorithm is proposed to solve some problems. Simulation results show the effectiveness of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(11501433)the Fundamental Research Funds for the Central Universities(JB180711)
文摘Inference are considered for the dependence competing risks model by using the Marshal-Olkin bivariate exponential distribution. Under generalized progressively hybrid censoring with partially observed failure causes, the maximum likelihood estimators are established, and the approximate confidence intervals are also constructed via the observed Fisher information matrix.Moreover, Bayes estimates and highest probability density credible intervals are presented and the importance sampling technique is used to compute corresponding results. Finally, the numerical analysis is proposed for illustration.
文摘The paper presents the conceptual and operational basis of the creation of IDSS based on our recent research experience. In this paper, an intelligent decision support system, IDSS is defined as: any interactive system that is specially designed to improve the decision making of its user by extending the user's cognitive decision making abilities. As a result, this view of man-machine joint cognitive system stresses the need to use computational technology to aid the user in the decision making process. And the human's role is to achieve total systems's objectives. The paper outlines the designing procedure in successive steps. First, the decision maker's cognitive needs for decision support are identified. Second, the computationally realizable support functions are defined that could be provided by IDSS. Then, the specific techniques that would best fill the decision needs are discussed. And finally, for system implementation the modern computational technology infrastructure is emphasized.
基金supported by the Program of Introducing Talents of Discipline to Universities(111 Plan)of China(B14010)the National Natural Science Foundation of China(31727901)
文摘While moving ahead with the object detection technology, especially deep neural networks, many related tasks, such as medical application and industrial automation, have achieved great success. However, the detection of objects with multiple aspect ratios and scales is still a key problem. This paper proposes a top-down and bottom-up feature pyramid network(TDBU-FPN),which combines multi-scale feature representation and anchor generation at multiple aspect ratios. First, in order to build the multi-scale feature map, this paper puts a number of fully convolutional layers after the backbone. Second, to link neighboring feature maps, top-down and bottom-up flows are adopted to introduce context information via top-down flow and supplement suboriginal information via bottom-up flow. The top-down flow refers to the deconvolution procedure, and the bottom-up flow refers to the pooling procedure. Third, the problem of adapting different object aspect ratios is tackled via many anchor shapes with different aspect ratios on each multi-scale feature map. The proposed method is evaluated on the pattern analysis, statistical modeling and computational learning visual object classes(PASCAL VOC)dataset and reaches an accuracy of 79%, which exhibits a 1.8% improvement with a detection speed of 23 fps.
基金supported by the National Natural Science Foundation of China(6157301761703425)+2 种基金the Aeronautical Science Fund(20175796014)Shaanxi Province Natural Science Foundation(2016JQ60622017JM6062)
文摘To solve the problem of distributed tasks-platforms scheduling in holonic command and control(C2) organization,the basic elements of the organization are analyzed firstly and the formal description of organizational elements and structure is provided. Based on the improvement of task execution quality,a single task resource scheduling model is established and the solving method based on the m-best algorithm is proposed. For the problem of tactical decision-holon cannot handle tasks with low priority effectively, a distributed resource scheduling collaboration mechanism based on platform pricing and a platform exchange mechanism based on resource capacities are designed. Finally,a series of experiments are designed to prove the effectiveness of these methods. The results show that the proposed distributed scheduling methods can realize the effective balance of platform resources.
基金supported by the National Natural Science Foundation of China(U1435220)
文摘How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.
基金supported by the National Natural Science Foundation of China(91216104 61503302)
文摘A smart homing guidance strategy with control saturation against a target-defender team is derived. It is noteworthy that a cooperative strategy of the target-defender team is applied,which has been proved more challenging for the homing guidance.The defender missile is launched by the target and guided by a cooperative augmented proportional navigation(APN). At the same time, the target performs a one-switch maneuver to cooperate and minimize the defender's acceleration requirement. The problem is analyzed for arbitrary-order linear dynamics of the agents in the linearized form but validated by the mathematical simulations by using nonlinear kinematics. The perfect information of three agents' states is assumed. Then, a method to deal with the target-defender team is proposed. It contains a combined performance index penalizing the miss distance relative to the target and energy consumption in the whole duration. Besides, the specific miss distance related to the defender is regarded as an inequality constraint. An analytical solution for the smart guidance strategy against the APN guided defender is derived. Meanwhile, the control saturations are introduced to get more realistic and reasonable insights to this practical target-missile-defender problem. A simple but effective iterative searching technique is proposed to determine the saturation time points. The solution provides an optimal homing strategy to evade the defender with a specific miss distance and intercept the target with the minimum miss distance in the minimum energy manner. Nonlinear two-dimensional simulation results are used to validate the theoretical analysis. By comparison with the optimal differential game guidance(ODGG) and the combined minimum effort guidance(CMEG), the superiority of this smart guidance strategy is concluded.
基金The Project is Supported by Nation Natural Science Foundation of China
文摘This paper presents a brief summary of the three development stages of investigation on the transpiration cooling and its control for aircraft, missiles and electromagnetic gun, then the control problem of the distributed parameters system with a moving boundary is derived. It introduces the mathematical model of the transpiration cooling control, its control characteristics, and the present situation of the experimental and theoretical study on this problem. This paper also describes the main study results and the existing problems. The prospective application is also reported. The major references in every developing stage are listed systematically for further study.
基金The project was supported by the National Natural Science Faundation of China
文摘In this paper two classes of equivalence transform methods for solving ordinary differential equations are proposed. One class of method is the equivalence integral transform method for special differential algebraic problems. The advantage of this class of method is such that the amount of work calculating one integration with parameters becomes that of two interpolations, when the system of nonlinear equations is solved on the right hand side function. The other class of method is the equivalence substitution method for avoiding calculating derivative on the right hand side function. In order to avoid calculation derivatives, two equivalence substitution methods are proposed here. The application instances of some special effect of the equivalence substitution methods are given.
文摘The history of the development of Chinese telemetry is introduced in the paper. The new telemetry ground station and the new onboard space telemetry system, with the idea of systematic design and the specification, are described.
基金supported by the National Natural Science Foundation of China(61573017 61703425)the Aeronautical Science Fund(20175796014)
文摘The formation of the manned aerial vehicle/unmanned aerial vehicle(MAV/UAV) task coalition is considered. To reduce the scale of the problem, the formation progress is divided into three phases. For the task clustering phase, the geographical position of tasks is taken into consideration and a cluster method is proposed. For the UAV allocation phase, the UAV requirement for both constrained and unconstrained resources is introduced, and a multi-objective optimal algorithm is proposed to solve the allocation problem. For the MAV allocation phase, the optimal model is firstly constructed and it is decomposed according to the ideal of greed to reduce the time complexity of the algorithm. Based on the above phases, the MAV/UAV task coalition formation method is proposed and the effectiveness and practicability are demonstrated by simulation examples.
文摘The Department of Water Resources and Harbour Engineering was originally a division of hydraulic engineering in the Department of Civil Engineering in Peiyang University the first modern university founded in China in 1933. Since then, about 5000 students have graduated from the Department.
基金supported by the National Natural Science Foundation of China(71571144 71401134)the Program of International Cooperation and Exchanges in Science and Technology Funded by Shaanxi Province(2016KW-033)
文摘Middle censoring is an important censoring scheme,in which the actual failure data of an observation becomes unobservable if it falls into a random interval. This paper considers the statistical analysis of the dependent competing risks model by using the Marshall-Olkin bivariate Weibull(MOBW) distribution.The maximum likelihood estimations(MLEs), midpoint approximation(MPA) estimations and approximate confidence intervals(ACIs) of the unknown parameters are obtained. In addition, the Bayes approach is also considered based on the Gamma-Dirichlet prior of the scale parameters, with the given shape parameter.The acceptance-rejection sampling method is used to obtain the Bayes estimations and construct credible intervals(CIs). Finally,two numerical examples are used to show the performance of the proposed methods.
文摘Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest develop ments and achievements in both theoretical and practical aspects of systems engineering,electronics and related research areas.The journal welcomes high quality original papers from a wide range of countries.
文摘Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest develop-ments and achievements in both theoretical and practical aspects of systems engineering,electronicsand related research areas.
基金supported by the Postdoctoral Science Foundation of China(2013T60923)
文摘For the target threat evaluation of warships formation air defense, the sample data are frequently insufficient and even incomplete. The existing evaluation methods rely too much on expertise and are difficult to carry out for the dynamic evaluation on time series. In order to solve these problems, a threat evaluation method based on the AR(p)(auto regressive(AR))-dynamic improved technique for order preference by similarity to ideal solution(DITOPSIS) method is proposed. The AR(p) model is adopted to predict the missing data on the time series. Then, the entropy weight method is applied to solve each index weight at the objective point. Kullback-Leibler divergence(KLD) is used to improve the traditional TOPSIS, and to carry out the target threat evaluation. The Poisson distribution is used to assign the weight value.Simulation results show that the improved AR(p)-DITOPSIS threat evaluation method can synthetically take into account the target threat degree in time series and is more suitable for the threat evaluation under the condition of missing the target data than the traditional TOPSIS method.
