Function allocation is one of the necessary stages in the design course of man-machine systems since appropriate function allocation makes the whole system more effective, reliable and inexpensive. Therefore, our rese...Function allocation is one of the necessary stages in the design course of man-machine systems since appropriate function allocation makes the whole system more effective, reliable and inexpensive. Therefore, our research mainly focuses on the problems of function allocation between man and machine in man-machine systems, analyses each capability advantage of man and machine according to their respective inherent characteristics and makes a comparison between them. In view of highly uncertain characteristics of decision attribute value in the practical process, we introduce the uncertain linguistic multiple attribute decision making （ULMADM） method in the function allocation process. Meanwhile, we also use the uncertain extended weighted arithmetic averaging （UEWAA） method to determine the automation level range of the operator functions. Then, we eventually estab- lish the automation level of man-machine function allocation by using the multi-attribute decision making algorithm, which is combined by UEWAA and uncertain linguistic hybrid aggregation （ULHA） operators. Finally, an example about function allocation is given, that is, fault diagnosis in the cockpit of civil aircraft. The final result of the example demonstrates that the proposed method about function allocation is feasible and effective.展开更多
A mathematical model of man-machine system is considered.Based on the reference [4],the direction and stability of the Hopf bifurcation are determined using the normal form method and the center manifold theory.Furthe...A mathematical model of man-machine system is considered.Based on the reference [4],the direction and stability of the Hopf bifurcation are determined using the normal form method and the center manifold theory.Furthermore,the existence of Hopf-zero bifurcation is discussed.In the end,some numerical simulations are carried out to illustrate the results found.展开更多
A digital man-machine interaction system controlled by communications between two processors of TMS320F240 and AT98C2051 was researched in the paper. The system is easy to set and modify welding process parameters by ...A digital man-machine interaction system controlled by communications between two processors of TMS320F240 and AT98C2051 was researched in the paper. The system is easy to set and modify welding process parameters by keyboards, and display information of welding site by LCD (Liquid Crystal Display). As one part of multi-task system about TIG welding machine, the coordination of man-machine interaction system with other tasks is the main point to the stability and reliability of its operation. Experiments result indicates that the system is stable, operation-flexible, high precision, and anti-interfering.展开更多
Dashboard similar structure design is a kind of interactive design of ergonomics and industrial design, and also the consistency design of functional features and visual organization effect of dashboard. Functional fe...Dashboard similar structure design is a kind of interactive design of ergonomics and industrial design, and also the consistency design of functional features and visual organization effect of dashboard. Functional feature design of dashboard is the analysis of man-machine interface, and visual organization effect design of dashboard is a branch of industrial design, both of them interact and unite.展开更多
with the rapid development of hi-tech at present, the college English curriculum teaching of higher education in our country faces an inevitable deep reform and innovation. In order to effectively improve the English ...with the rapid development of hi-tech at present, the college English curriculum teaching of higher education in our country faces an inevitable deep reform and innovation. In order to effectively improve the English application ability of undergraduates, this paper analyzes the integration of interpersonal teaching and man-machine teaching in college English, illustrates the connotation and the current situation of interpersonal and man-machine teaching and makes deep research of integration of these two teaching modes. The author proposes to fully exert the features and advantages of interpersonal teaching and multi-media teaching and hopes to improve the teaching quality of college English through the analysis and research of this paper.展开更多
In this paper, we conduct research on the man-machine interactive environment VR and the applications on vocational educationand training under the perspective of interactivity. With the increase in the general standa...In this paper, we conduct research on the man-machine interactive environment VR and the applications on vocational educationand training under the perspective of interactivity. With the increase in the general standard of social knowledge level and competition intensifi es,more and more people have a goal to build a lifelong learning system, according to their own hobbies, work and the needs of the marketcompetition. Under this condition, the vocational education is becoming more and more essential. This paper integrates the VR and man-machineinteractive concept to propose the new education paradigm that is innovative.展开更多
In this paper, we conduct research on the man-machine engineering theory and the applications on furniture design and interior decoration design. Furniture is one of the important media, contacts and relationships bet...In this paper, we conduct research on the man-machine engineering theory and the applications on furniture design and interior decoration design. Furniture is one of the important media, contacts and relationships between building it by their own different shape and size provide comfortable environment for people. Ergonomics is the study of human activity and the claim size on the surrounding environment, how to make furniture to better serve people＇ s life and work. Our research proposed novel paradigm of the man-machine engineering theory which is meaningful.展开更多
Product assembly occupies an extremely important position in the whole production process of products. At present, due to the growing demand of consumers for personalized and customized products, the traditional manua...Product assembly occupies an extremely important position in the whole production process of products. At present, due to the growing demand of consumers for personalized and customized products, the traditional manual assembly method is inefficient, and pure automatic assembly is difficult and costly, which is difficult to meet the production needs of enterprises. Therefore, the intelligent assembly system of human-computer integration arises at the historic moment and realizes high-quality and high-efficiency product assembly.展开更多
Within-Visual-Range(WVR)air combat is a highly dynamic and uncertain domain where effective strategies require intelligent and adaptive decision-making.Traditional approaches,including rule-based methods and conventio...Within-Visual-Range(WVR)air combat is a highly dynamic and uncertain domain where effective strategies require intelligent and adaptive decision-making.Traditional approaches,including rule-based methods and conventional Reinforcement Learning(RL)algorithms,often focus on maximizing engagement outcomes through direct combat superiority.However,these methods overlook alternative tactics,such as inducing adversaries to crash,which can achieve decisive victories with lower risk and cost.This study proposes Alpha Crash,a novel distributional-rein forcement-learning-based agent specifically designed to defeat opponents by leveraging crash induction strategies.The approach integrates an improved QR-DQN framework to address uncertainties and adversarial tactics,incorporating advanced pilot experience into its reward functions.Extensive simulations reveal Alpha Crash's robust performance,achieving a 91.2%win rate across diverse scenarios by effectively guiding opponents into critical errors.Visualization and altitude analyses illustrate the agent's three-stage crash induction strategies that exploit adversaries'vulnerabilities.These findings underscore Alpha Crash's potential to enhance autonomous decision-making and strategic innovation in real-world air combat applications.展开更多
Policy training against diverse opponents remains a challenge when using Multi-Agent Reinforcement Learning(MARL)in multiple Unmanned Combat Aerial Vehicle(UCAV)air combat scenarios.In view of this,this paper proposes...Policy training against diverse opponents remains a challenge when using Multi-Agent Reinforcement Learning(MARL)in multiple Unmanned Combat Aerial Vehicle(UCAV)air combat scenarios.In view of this,this paper proposes a novel Dominant and Non-dominant strategy sample selection(DoNot)mechanism and a Local Observation Enhanced Multi-Agent Proximal Policy Optimization(LOE-MAPPO)algorithm to train the multi-UCAV air combat policy and improve its generalization.Specifically,the LOE-MAPPO algorithm adopts a mixed state that concatenates the global state and individual agent's local observation to enable efficient value function learning in multi-UCAV air combat.The DoNot mechanism classifies opponents into dominant or non-dominant strategy opponents,and samples from easier to more challenging opponents to form an adaptive training curriculum.Empirical results demonstrate that the proposed LOE-MAPPO algorithm outperforms baseline MARL algorithms in multi-UCAV air combat scenarios,and the DoNot mechanism leads to stronger policy generalization when facing diverse opponents.The results pave the way for the fast generation of cooperative strategies for air combat agents with MARLalgorithms.展开更多
The rapid development of military technology has prompted different types of equipment to break the limits of operational domains and emerged through complex interactions to form a vast combat system of systems(CSoS),...The rapid development of military technology has prompted different types of equipment to break the limits of operational domains and emerged through complex interactions to form a vast combat system of systems(CSoS),which can be abstracted as a heterogeneous combat network(HCN).It is of great military significance to study the disintegration strategy of combat networks to achieve the breakdown of the enemy’s CSoS.To this end,this paper proposes an integrated framework called HCN disintegration based on double deep Q-learning(HCN-DDQL).Firstly,the enemy’s CSoS is abstracted as an HCN,and an evaluation index based on the capability and attack costs of nodes is proposed.Meanwhile,a mathematical optimization model for HCN disintegration is established.Secondly,the learning environment and double deep Q-network model of HCN-DDQL are established to train the HCN’s disintegration strategy.Then,based on the learned HCN-DDQL model,an algorithm for calculating the HCN’s optimal disintegration strategy under different states is proposed.Finally,a case study is used to demonstrate the reliability and effectiveness of HCNDDQL,and the results demonstrate that HCN-DDQL can disintegrate HCNs more effectively than baseline methods.展开更多
During its interaction with modern sports,traditional Wushu has faced increasing doubts about its combat effectiveness,raising concerns about its cultural identity.How traditional Wushu is understood as a combat art n...During its interaction with modern sports,traditional Wushu has faced increasing doubts about its combat effectiveness,raising concerns about its cultural identity.How traditional Wushu is understood as a combat art not only helps define its cultural essence but also carries important implications for its long-term development.It is an objective fact that combat represents the practical manifestation of traditional Wushu in history.Combat reflects similarities among traditional Wushu forms that emerged throughout history.Combat reflects the historical law governing the evolution of traditional Wushu and represents an abstraction of repetitive phenomena in traditional Wushu.A correct understanding of this objectivity,these similarities,and this repeatability is conducive to promoting and carrying forward traditional Wushu,thereby facilitating an objective analysis of differences among different traditional Wushu forms and the discovery of their evolution paradigm.In the contemporary context,it is essential for traditional Wushu to emphasize its distinctive cultural roots,thereby facilitating creative transformation and innovative development.展开更多
The high maneuverability of modern fighters in close air combat imposes significant cognitive demands on pilots,making rapid,accurate decision-making challenging.While reinforcement learning(RL)has shown promise in th...The high maneuverability of modern fighters in close air combat imposes significant cognitive demands on pilots,making rapid,accurate decision-making challenging.While reinforcement learning(RL)has shown promise in this domain,the existing methods often lack strategic depth and generalization in complex,high-dimensional environments.To address these limitations,this paper proposes an optimized self-play method enhanced by advancements in fighter modeling,neural network design,and algorithmic frameworks.This study employs a six-degree-of-freedom(6-DOF)F-16 fighter model based on open-source aerodynamic data,featuring airborne equipment and a realistic visual simulation platform,unlike traditional 3-DOF models.To capture temporal dynamics,Long Short-Term Memory(LSTM)layers are integrated into the neural network,complemented by delayed input stacking.The RL environment incorporates expert strategies,curiositydriven rewards,and curriculum learning to improve adaptability and strategic decision-making.Experimental results demonstrate that the proposed approach achieves a winning rate exceeding90%against classical single-agent methods.Additionally,through enhanced 3D visual platforms,we conducted human-agent confrontation experiments,where the agent attained an average winning rate of over 75%.The agent's maneuver trajectories closely align with human pilot strategies,showcasing its potential in decision-making and pilot training applications.This study highlights the effectiveness of integrating advanced modeling and self-play techniques in developing robust air combat decision-making systems.展开更多
To extract and display the significant information of combat systems,this paper introduces the methodology of functional cartography into combat networks and proposes an integrated framework named“functional cartogra...To extract and display the significant information of combat systems,this paper introduces the methodology of functional cartography into combat networks and proposes an integrated framework named“functional cartography of heterogeneous combat networks based on the operational chain”(FCBOC).In this framework,a functional module detection algorithm named operational chain-based label propagation algorithm(OCLPA),which considers the cooperation and interactions among combat entities and can thus naturally tackle network heterogeneity,is proposed to identify the functional modules of the network.Then,the nodes and their modules are classified into different roles according to their properties.A case study shows that FCBOC can provide a simplified description of disorderly information of combat networks and enable us to identify their functional and structural network characteristics.The results provide useful information to help commanders make precise and accurate decisions regarding the protection,disintegration or optimization of combat networks.Three algorithms are also compared with OCLPA to show that FCBOC can most effectively find functional modules with practical meaning.展开更多
Beyond-visual-range(BVR)air combat threat assessment has attracted wide attention as the support of situation awareness and autonomous decision-making.However,the traditional threat assessment method is flawed in its ...Beyond-visual-range(BVR)air combat threat assessment has attracted wide attention as the support of situation awareness and autonomous decision-making.However,the traditional threat assessment method is flawed in its failure to consider the intention and event of the target,resulting in inaccurate assessment results.In view of this,an integrated threat assessment method is proposed to address the existing problems,such as overly subjective determination of index weight and imbalance of situation.The process and characteristics of BVR air combat are analyzed to establish a threat assessment model in terms of target intention,event,situation,and capability.On this basis,a distributed weight-solving algorithm is proposed to determine index and attribute weight respectively.Then,variable weight and game theory are introduced to effectively deal with the situation imbalance and achieve the combination of subjective and objective.The performance of the model and algorithm is evaluated through multiple simulation experiments.The assessment results demonstrate the accuracy of the proposed method in BVR air combat,indicating its potential practical significance in real air combat scenarios.展开更多
Unmanned Aerial Vehicle(UAV) trajectory prediction is an important research topic in the field of UAV air combat. In order to address the problem of single-feature extraction scale and scene adaptability in UAV air co...Unmanned Aerial Vehicle(UAV) trajectory prediction is an important research topic in the field of UAV air combat. In order to address the problem of single-feature extraction scale and scene adaptability in UAV air combat trajectory prediction algorithms, this paper proposes an innovative UAV trajectory prediction method QCNet-3D, which can predict the future trajectory of the target UAV and provide the corresponding possibility. Firstly, the UAV trajectory prediction is modeled based on the mixture of Laplace distributions, and the UAV's kinetic equations are employed to construct the UAV trajectory prediction dataset(UAVTP dataset), ensuring high reliability. Secondly, two improvement methods are proposed on the basis of QCNet: multi-scale Fourier mapping and three-dimensional adaptation. The ablation study shows that the improvement methods have reduced the minimum average displacement error, minimum final displacement error, and missing rate by 55.4%, 54.3%, and 68.1% respectively. Finally, QCNet-3D is proposed based on the two improvement methods, and the simulation experiment confirm the proposed algorithm's capability to predict both simple and complex UAV maneuvers, offering the possibility for each predicted trajectory under various prediction future steps and output modes.展开更多
Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm opt...Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm optimization （HPSO） algorithm is proposed to solve the decision-making （DM） problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts （FAs） to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA based algorithms in searching for the best solution to the DM problem.展开更多
文摘Function allocation is one of the necessary stages in the design course of man-machine systems since appropriate function allocation makes the whole system more effective, reliable and inexpensive. Therefore, our research mainly focuses on the problems of function allocation between man and machine in man-machine systems, analyses each capability advantage of man and machine according to their respective inherent characteristics and makes a comparison between them. In view of highly uncertain characteristics of decision attribute value in the practical process, we introduce the uncertain linguistic multiple attribute decision making （ULMADM） method in the function allocation process. Meanwhile, we also use the uncertain extended weighted arithmetic averaging （UEWAA） method to determine the automation level range of the operator functions. Then, we eventually estab- lish the automation level of man-machine function allocation by using the multi-attribute decision making algorithm, which is combined by UEWAA and uncertain linguistic hybrid aggregation （ULHA） operators. Finally, an example about function allocation is given, that is, fault diagnosis in the cockpit of civil aircraft. The final result of the example demonstrates that the proposed method about function allocation is feasible and effective.
基金Foundation item： Supported bY the Natural Science Foundation of Ningxia（NZ09204） Supported by the Youth Foundation of Ningxia Teacher＇s Universlty（QN2010002）
文摘A mathematical model of man-machine system is considered.Based on the reference [4],the direction and stability of the Hopf bifurcation are determined using the normal form method and the center manifold theory.Furthermore,the existence of Hopf-zero bifurcation is discussed.In the end,some numerical simulations are carried out to illustrate the results found.
文摘A digital man-machine interaction system controlled by communications between two processors of TMS320F240 and AT98C2051 was researched in the paper. The system is easy to set and modify welding process parameters by keyboards, and display information of welding site by LCD (Liquid Crystal Display). As one part of multi-task system about TIG welding machine, the coordination of man-machine interaction system with other tasks is the main point to the stability and reliability of its operation. Experiments result indicates that the system is stable, operation-flexible, high precision, and anti-interfering.
文摘Dashboard similar structure design is a kind of interactive design of ergonomics and industrial design, and also the consistency design of functional features and visual organization effect of dashboard. Functional feature design of dashboard is the analysis of man-machine interface, and visual organization effect design of dashboard is a branch of industrial design, both of them interact and unite.
文摘with the rapid development of hi-tech at present, the college English curriculum teaching of higher education in our country faces an inevitable deep reform and innovation. In order to effectively improve the English application ability of undergraduates, this paper analyzes the integration of interpersonal teaching and man-machine teaching in college English, illustrates the connotation and the current situation of interpersonal and man-machine teaching and makes deep research of integration of these two teaching modes. The author proposes to fully exert the features and advantages of interpersonal teaching and multi-media teaching and hopes to improve the teaching quality of college English through the analysis and research of this paper.
文摘In this paper, we conduct research on the man-machine interactive environment VR and the applications on vocational educationand training under the perspective of interactivity. With the increase in the general standard of social knowledge level and competition intensifi es,more and more people have a goal to build a lifelong learning system, according to their own hobbies, work and the needs of the marketcompetition. Under this condition, the vocational education is becoming more and more essential. This paper integrates the VR and man-machineinteractive concept to propose the new education paradigm that is innovative.
文摘In this paper, we conduct research on the man-machine engineering theory and the applications on furniture design and interior decoration design. Furniture is one of the important media, contacts and relationships between building it by their own different shape and size provide comfortable environment for people. Ergonomics is the study of human activity and the claim size on the surrounding environment, how to make furniture to better serve people＇ s life and work. Our research proposed novel paradigm of the man-machine engineering theory which is meaningful.
文摘Product assembly occupies an extremely important position in the whole production process of products. At present, due to the growing demand of consumers for personalized and customized products, the traditional manual assembly method is inefficient, and pure automatic assembly is difficult and costly, which is difficult to meet the production needs of enterprises. Therefore, the intelligent assembly system of human-computer integration arises at the historic moment and realizes high-quality and high-efficiency product assembly.
基金supported by the National Key R&D Program of China(No.2021YFB3300602)。
文摘Within-Visual-Range(WVR)air combat is a highly dynamic and uncertain domain where effective strategies require intelligent and adaptive decision-making.Traditional approaches,including rule-based methods and conventional Reinforcement Learning(RL)algorithms,often focus on maximizing engagement outcomes through direct combat superiority.However,these methods overlook alternative tactics,such as inducing adversaries to crash,which can achieve decisive victories with lower risk and cost.This study proposes Alpha Crash,a novel distributional-rein forcement-learning-based agent specifically designed to defeat opponents by leveraging crash induction strategies.The approach integrates an improved QR-DQN framework to address uncertainties and adversarial tactics,incorporating advanced pilot experience into its reward functions.Extensive simulations reveal Alpha Crash's robust performance,achieving a 91.2%win rate across diverse scenarios by effectively guiding opponents into critical errors.Visualization and altitude analyses illustrate the agent's three-stage crash induction strategies that exploit adversaries'vulnerabilities.These findings underscore Alpha Crash's potential to enhance autonomous decision-making and strategic innovation in real-world air combat applications.
文摘Policy training against diverse opponents remains a challenge when using Multi-Agent Reinforcement Learning(MARL)in multiple Unmanned Combat Aerial Vehicle(UCAV)air combat scenarios.In view of this,this paper proposes a novel Dominant and Non-dominant strategy sample selection(DoNot)mechanism and a Local Observation Enhanced Multi-Agent Proximal Policy Optimization(LOE-MAPPO)algorithm to train the multi-UCAV air combat policy and improve its generalization.Specifically,the LOE-MAPPO algorithm adopts a mixed state that concatenates the global state and individual agent's local observation to enable efficient value function learning in multi-UCAV air combat.The DoNot mechanism classifies opponents into dominant or non-dominant strategy opponents,and samples from easier to more challenging opponents to form an adaptive training curriculum.Empirical results demonstrate that the proposed LOE-MAPPO algorithm outperforms baseline MARL algorithms in multi-UCAV air combat scenarios,and the DoNot mechanism leads to stronger policy generalization when facing diverse opponents.The results pave the way for the fast generation of cooperative strategies for air combat agents with MARLalgorithms.
基金supported by the National Natural Science Foundation of China(7200120972231011+2 种基金72071206)the Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province(2020RC4046)the Science Foundation for Outstanding Youth Scholars of Hunan Province(2022JJ20047).
文摘The rapid development of military technology has prompted different types of equipment to break the limits of operational domains and emerged through complex interactions to form a vast combat system of systems(CSoS),which can be abstracted as a heterogeneous combat network(HCN).It is of great military significance to study the disintegration strategy of combat networks to achieve the breakdown of the enemy’s CSoS.To this end,this paper proposes an integrated framework called HCN disintegration based on double deep Q-learning(HCN-DDQL).Firstly,the enemy’s CSoS is abstracted as an HCN,and an evaluation index based on the capability and attack costs of nodes is proposed.Meanwhile,a mathematical optimization model for HCN disintegration is established.Secondly,the learning environment and double deep Q-network model of HCN-DDQL are established to train the HCN’s disintegration strategy.Then,based on the learned HCN-DDQL model,an algorithm for calculating the HCN’s optimal disintegration strategy under different states is proposed.Finally,a case study is used to demonstrate the reliability and effectiveness of HCNDDQL,and the results demonstrate that HCN-DDQL can disintegrate HCNs more effectively than baseline methods.
文摘During its interaction with modern sports,traditional Wushu has faced increasing doubts about its combat effectiveness,raising concerns about its cultural identity.How traditional Wushu is understood as a combat art not only helps define its cultural essence but also carries important implications for its long-term development.It is an objective fact that combat represents the practical manifestation of traditional Wushu in history.Combat reflects similarities among traditional Wushu forms that emerged throughout history.Combat reflects the historical law governing the evolution of traditional Wushu and represents an abstraction of repetitive phenomena in traditional Wushu.A correct understanding of this objectivity,these similarities,and this repeatability is conducive to promoting and carrying forward traditional Wushu,thereby facilitating an objective analysis of differences among different traditional Wushu forms and the discovery of their evolution paradigm.In the contemporary context,it is essential for traditional Wushu to emphasize its distinctive cultural roots,thereby facilitating creative transformation and innovative development.
基金co-supported by the National Natural Science Foundation of China(No.91852115)。
文摘The high maneuverability of modern fighters in close air combat imposes significant cognitive demands on pilots,making rapid,accurate decision-making challenging.While reinforcement learning(RL)has shown promise in this domain,the existing methods often lack strategic depth and generalization in complex,high-dimensional environments.To address these limitations,this paper proposes an optimized self-play method enhanced by advancements in fighter modeling,neural network design,and algorithmic frameworks.This study employs a six-degree-of-freedom(6-DOF)F-16 fighter model based on open-source aerodynamic data,featuring airborne equipment and a realistic visual simulation platform,unlike traditional 3-DOF models.To capture temporal dynamics,Long Short-Term Memory(LSTM)layers are integrated into the neural network,complemented by delayed input stacking.The RL environment incorporates expert strategies,curiositydriven rewards,and curriculum learning to improve adaptability and strategic decision-making.Experimental results demonstrate that the proposed approach achieves a winning rate exceeding90%against classical single-agent methods.Additionally,through enhanced 3D visual platforms,we conducted human-agent confrontation experiments,where the agent attained an average winning rate of over 75%.The agent's maneuver trajectories closely align with human pilot strategies,showcasing its potential in decision-making and pilot training applications.This study highlights the effectiveness of integrating advanced modeling and self-play techniques in developing robust air combat decision-making systems.
文摘To extract and display the significant information of combat systems,this paper introduces the methodology of functional cartography into combat networks and proposes an integrated framework named“functional cartography of heterogeneous combat networks based on the operational chain”(FCBOC).In this framework,a functional module detection algorithm named operational chain-based label propagation algorithm(OCLPA),which considers the cooperation and interactions among combat entities and can thus naturally tackle network heterogeneity,is proposed to identify the functional modules of the network.Then,the nodes and their modules are classified into different roles according to their properties.A case study shows that FCBOC can provide a simplified description of disorderly information of combat networks and enable us to identify their functional and structural network characteristics.The results provide useful information to help commanders make precise and accurate decisions regarding the protection,disintegration or optimization of combat networks.Three algorithms are also compared with OCLPA to show that FCBOC can most effectively find functional modules with practical meaning.
基金National Natural Science Foundation of China(62006193,62103338)Aeronautical Science Foundation of China(2022Z023053001)+1 种基金Key Research and Development Program of Shaanxi Province(2024GX-YBXM-115)Fundamental Research Funds for the Central Universities(D5000230150)。
文摘Beyond-visual-range(BVR)air combat threat assessment has attracted wide attention as the support of situation awareness and autonomous decision-making.However,the traditional threat assessment method is flawed in its failure to consider the intention and event of the target,resulting in inaccurate assessment results.In view of this,an integrated threat assessment method is proposed to address the existing problems,such as overly subjective determination of index weight and imbalance of situation.The process and characteristics of BVR air combat are analyzed to establish a threat assessment model in terms of target intention,event,situation,and capability.On this basis,a distributed weight-solving algorithm is proposed to determine index and attribute weight respectively.Then,variable weight and game theory are introduced to effectively deal with the situation imbalance and achieve the combination of subjective and objective.The performance of the model and algorithm is evaluated through multiple simulation experiments.The assessment results demonstrate the accuracy of the proposed method in BVR air combat,indicating its potential practical significance in real air combat scenarios.
基金National Natural Science Foundation (NSF) of China (No.61976014)the Aeronautical Science Foundation of China (2022Z071051001)。
文摘Unmanned Aerial Vehicle(UAV) trajectory prediction is an important research topic in the field of UAV air combat. In order to address the problem of single-feature extraction scale and scene adaptability in UAV air combat trajectory prediction algorithms, this paper proposes an innovative UAV trajectory prediction method QCNet-3D, which can predict the future trajectory of the target UAV and provide the corresponding possibility. Firstly, the UAV trajectory prediction is modeled based on the mixture of Laplace distributions, and the UAV's kinetic equations are employed to construct the UAV trajectory prediction dataset(UAVTP dataset), ensuring high reliability. Secondly, two improvement methods are proposed on the basis of QCNet: multi-scale Fourier mapping and three-dimensional adaptation. The ablation study shows that the improvement methods have reduced the minimum average displacement error, minimum final displacement error, and missing rate by 55.4%, 54.3%, and 68.1% respectively. Finally, QCNet-3D is proposed based on the two improvement methods, and the simulation experiment confirm the proposed algorithm's capability to predict both simple and complex UAV maneuvers, offering the possibility for each predicted trajectory under various prediction future steps and output modes.
文摘Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm optimization （HPSO） algorithm is proposed to solve the decision-making （DM） problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts （FAs） to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA based algorithms in searching for the best solution to the DM problem.
