With the development of high energy solid propellants,it is critical to evaluate the safety and power performance of solid propellants in the face of threats such as unmanned aerial vehicles(UAVs)when transporting and...With the development of high energy solid propellants,it is critical to evaluate the safety and power performance of solid propellants in the face of threats such as unmanned aerial vehicles(UAVs)when transporting and using them in contemporary warfare.An electric probe-type cylinder test measured the displacement-time behavior of NEPE high-energy solid propellant,and the parameters of the Jones-Wilkins-Lee(JWL)equation of state(EOS)were derived using particle swarm optimization(PSO)with the Gurney energy model.Further,the parameters of JWL-Miller EOS,determined through AUTODYN simulations,were validated by comparing airburst process simulations with experimental overpressure data.The study established a method for determining EOS parameters of high-energy propellants,achieving a high degree of accuracy.The derived parameters ensure precise modeling of propellant behavior,offering a reliable foundation for future applications in solid rocket motor performance optimization and safety assessment.展开更多
When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game ...When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game strategy,the game of kind is generally considered to be angle-optimized,which allows unlimited turns,but these practices do not take into account the effect of acceleration,which does not correspond to the actual situation,thus,based on the angle-optimized,the acceleration optimization and the acceleration upper bound constraint are added into the game for consideration.A two-to-one differential game problem is proposed in the three-dimensional space,and an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to solve the optimal game point of this problem.With the equations that describe the relative motions between the pursuers and the evader in the three-dimensional space,a multi-objective function with constraints is given as the performance index to design an optimal strategy for the differential game.Then the optimal game point is solved by using the IMOGWO algorithm.It is proved based on Markov chains that with the IMOGWO,the Pareto solution set is the solution of the differential game.Finally,it is verified through simulations that the pursuers can capture the escapee,and via comparative experiments,it is shown that the IMOGWO algorithm performs well in terms of running time and memory usage.展开更多
In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t...In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.展开更多
Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for t...Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for timing and deployment.To improve the response speed and jamming effect,a cluster of OADs based on an unmanned surface vehicle(USV)is proposed.The formation of the cluster determines the effectiveness of jamming.First,based on the mechanism of OAD jamming,critical conditions are identified,and a method for assessing the jamming effect is proposed.Then,for the optimization of the cluster formation,a mathematical model is built,and a multi-tribe adaptive particle swarm optimization algorithm based on mutation strategy and Metropolis criterion(3M-APSO)is designed.Finally,the formation optimization problem is solved and analyzed using the 3M-APSO algorithm under specific scenarios.The results show that the improved algorithm has a faster convergence rate and superior performance as compared to the standard Adaptive-PSO algorithm.Compared with a single OAD,the optimal formation of USV-OAD cluster effectively fills the blind area and maximizes the use of jamming resources.展开更多
针对快速扩展随机树(rapid-exploration random tree^(*),RRT^(*))算法在三维避障路径规划中存在盲目性、低效率和路径不光滑的问题,提出一种改进的RRT^(*)算法,以提高焊接机器人路径规划的性能。通过采用双向搜索策略,缩短搜索时间;结...针对快速扩展随机树(rapid-exploration random tree^(*),RRT^(*))算法在三维避障路径规划中存在盲目性、低效率和路径不光滑的问题,提出一种改进的RRT^(*)算法,以提高焊接机器人路径规划的性能。通过采用双向搜索策略,缩短搜索时间;结合人工势场(artificial potential field,APF)算法与RRT^(*)算法以提升路径平滑性并平衡局部优化与全局最优;提出一种基于角度与密度的改进APF算法策略,提高避障与路径引导效率;提出动态目标偏置策略和动态步长策略,以增强算法在障碍物密集和稀疏区域的自适应性及搜索效率;采用路径修剪策略缩短和平滑路径。最后,通过改进的RRT^(*)算法与RRT^(*)、APF-RRT^(*)、Bi-APF-RRT^(*)(bidirectional-APFRRT^(*))3种算法对比仿真实验以及真机实验,验证了改进算法的高效性和实用性。展开更多
[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been propo...[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been proposed for monitoring cow ruminant behavior,including video surveillance,sound recognition,and sensor monitoring methods.How‐ever,the application of edge device gives rise to the issue of inadequate real-time performance.To reduce the volume of data transmission and cloud computing workload while achieving real-time monitoring of dairy cow rumination behavior,a real-time monitoring method was proposed for cow ruminant behavior based on edge computing.[Methods]Autono‐mously designed edge devices were utilized to collect and process six-axis acceleration signals from cows in real-time.Based on these six-axis data,two distinct strategies,federated edge intelligence and split edge intelligence,were investigat‐ed for the real-time recognition of cow ruminant behavior.Focused on the real-time recognition method for cow ruminant behavior leveraging federated edge intelligence,the CA-MobileNet v3 network was proposed by enhancing the MobileNet v3 network with a collaborative attention mechanism.Additionally,a federated edge intelligence model was designed uti‐lizing the CA-MobileNet v3 network and the FedAvg federated aggregation algorithm.In the study on split edge intelli‐gence,a split edge intelligence model named MobileNet-LSTM was designed by integrating the MobileNet v3 network with a fusion collaborative attention mechanism and the Bi-LSTM network.[Results and Discussions]Through compara‐tive experiments with MobileNet v3 and MobileNet-LSTM,the federated edge intelligence model based on CA-Mo‐bileNet v3 achieved an average Precision rate,Recall rate,F1-Score,Specificity,and Accuracy of 97.1%,97.9%,97.5%,98.3%,and 98.2%,respectively,yielding the best recognition performance.[Conclusions]It is provided a real-time and effective method for monitoring cow ruminant behavior,and the proposed federated edge intelligence model can be ap‐plied in practical settings.展开更多
Nitrogen(N)and phosphorus(P)are mineral nutrients essential for plant growth and development,playing a crucial role throughout the plant life cycle.Cotton,a globally significant textile crop,has a particularly high de...Nitrogen(N)and phosphorus(P)are mineral nutrients essential for plant growth and development,playing a crucial role throughout the plant life cycle.Cotton,a globally significant textile crop,has a particularly high demand for N fertilizer across its developmental stages.This review explores the effects of adequate or deficient N and P levels on cotton growth phases,focusing on their influence on physiological processes and molecular mechanisms.Key topics include the regulation of N-and P-related enzymes,hormones,and genes,as well as the complex interplay of N-and P-related signaling pathways from the aspects of N-P signaling integration to regulate root development,N-P signaling integration to regulate nutrient uptake,and regulation of N-P interactions—a frontier in current research.Strategies for improving N and P use efficiency are also discussed,including developing high-efficiency cotton cultivars and identifying functional genes to enhance productivity.Generally speaking,we take model plants as a reference in the hope of coming up with new strategies for the efficient utilization of N and P in cotton.展开更多
基金supported by"the Fundamental Research Funds for the Central Universities",No.30924010503.
文摘With the development of high energy solid propellants,it is critical to evaluate the safety and power performance of solid propellants in the face of threats such as unmanned aerial vehicles(UAVs)when transporting and using them in contemporary warfare.An electric probe-type cylinder test measured the displacement-time behavior of NEPE high-energy solid propellant,and the parameters of the Jones-Wilkins-Lee(JWL)equation of state(EOS)were derived using particle swarm optimization(PSO)with the Gurney energy model.Further,the parameters of JWL-Miller EOS,determined through AUTODYN simulations,were validated by comparing airburst process simulations with experimental overpressure data.The study established a method for determining EOS parameters of high-energy propellants,achieving a high degree of accuracy.The derived parameters ensure precise modeling of propellant behavior,offering a reliable foundation for future applications in solid rocket motor performance optimization and safety assessment.
基金National Natural Science Foundation of China(NSFC61773142,NSFC62303136)。
文摘When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game strategy,the game of kind is generally considered to be angle-optimized,which allows unlimited turns,but these practices do not take into account the effect of acceleration,which does not correspond to the actual situation,thus,based on the angle-optimized,the acceleration optimization and the acceleration upper bound constraint are added into the game for consideration.A two-to-one differential game problem is proposed in the three-dimensional space,and an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to solve the optimal game point of this problem.With the equations that describe the relative motions between the pursuers and the evader in the three-dimensional space,a multi-objective function with constraints is given as the performance index to design an optimal strategy for the differential game.Then the optimal game point is solved by using the IMOGWO algorithm.It is proved based on Markov chains that with the IMOGWO,the Pareto solution set is the solution of the differential game.Finally,it is verified through simulations that the pursuers can capture the escapee,and via comparative experiments,it is shown that the IMOGWO algorithm performs well in terms of running time and memory usage.
基金National Natural Science Foundation of China(62373187)Forward-looking Layout Special Projects(ILA220591A22)。
文摘In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.
基金the National Natural Science Foundation of China(Grant No.62101579).
文摘Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for timing and deployment.To improve the response speed and jamming effect,a cluster of OADs based on an unmanned surface vehicle(USV)is proposed.The formation of the cluster determines the effectiveness of jamming.First,based on the mechanism of OAD jamming,critical conditions are identified,and a method for assessing the jamming effect is proposed.Then,for the optimization of the cluster formation,a mathematical model is built,and a multi-tribe adaptive particle swarm optimization algorithm based on mutation strategy and Metropolis criterion(3M-APSO)is designed.Finally,the formation optimization problem is solved and analyzed using the 3M-APSO algorithm under specific scenarios.The results show that the improved algorithm has a faster convergence rate and superior performance as compared to the standard Adaptive-PSO algorithm.Compared with a single OAD,the optimal formation of USV-OAD cluster effectively fills the blind area and maximizes the use of jamming resources.
文摘针对快速扩展随机树(rapid-exploration random tree^(*),RRT^(*))算法在三维避障路径规划中存在盲目性、低效率和路径不光滑的问题,提出一种改进的RRT^(*)算法,以提高焊接机器人路径规划的性能。通过采用双向搜索策略,缩短搜索时间;结合人工势场(artificial potential field,APF)算法与RRT^(*)算法以提升路径平滑性并平衡局部优化与全局最优;提出一种基于角度与密度的改进APF算法策略,提高避障与路径引导效率;提出动态目标偏置策略和动态步长策略,以增强算法在障碍物密集和稀疏区域的自适应性及搜索效率;采用路径修剪策略缩短和平滑路径。最后,通过改进的RRT^(*)算法与RRT^(*)、APF-RRT^(*)、Bi-APF-RRT^(*)(bidirectional-APFRRT^(*))3种算法对比仿真实验以及真机实验,验证了改进算法的高效性和实用性。
文摘[Objective]Real-time monitoring of cow ruminant behavior is of paramount importance for promptly obtaining relevant information about cow health and predicting cow diseases.Currently,various strategies have been proposed for monitoring cow ruminant behavior,including video surveillance,sound recognition,and sensor monitoring methods.How‐ever,the application of edge device gives rise to the issue of inadequate real-time performance.To reduce the volume of data transmission and cloud computing workload while achieving real-time monitoring of dairy cow rumination behavior,a real-time monitoring method was proposed for cow ruminant behavior based on edge computing.[Methods]Autono‐mously designed edge devices were utilized to collect and process six-axis acceleration signals from cows in real-time.Based on these six-axis data,two distinct strategies,federated edge intelligence and split edge intelligence,were investigat‐ed for the real-time recognition of cow ruminant behavior.Focused on the real-time recognition method for cow ruminant behavior leveraging federated edge intelligence,the CA-MobileNet v3 network was proposed by enhancing the MobileNet v3 network with a collaborative attention mechanism.Additionally,a federated edge intelligence model was designed uti‐lizing the CA-MobileNet v3 network and the FedAvg federated aggregation algorithm.In the study on split edge intelli‐gence,a split edge intelligence model named MobileNet-LSTM was designed by integrating the MobileNet v3 network with a fusion collaborative attention mechanism and the Bi-LSTM network.[Results and Discussions]Through compara‐tive experiments with MobileNet v3 and MobileNet-LSTM,the federated edge intelligence model based on CA-Mo‐bileNet v3 achieved an average Precision rate,Recall rate,F1-Score,Specificity,and Accuracy of 97.1%,97.9%,97.5%,98.3%,and 98.2%,respectively,yielding the best recognition performance.[Conclusions]It is provided a real-time and effective method for monitoring cow ruminant behavior,and the proposed federated edge intelligence model can be ap‐plied in practical settings.
基金supported by Supported by National Key Laboratory of Cotton Bio-breeding and Integrated Utilization(CB2023C07)Xinjiang Autonomous Region"Three Agricultural"Backbone Talent Training Program(2022SNGGNT024)Xinjiang Huyanghe City Science and Technology Program(2023C08).
文摘Nitrogen(N)and phosphorus(P)are mineral nutrients essential for plant growth and development,playing a crucial role throughout the plant life cycle.Cotton,a globally significant textile crop,has a particularly high demand for N fertilizer across its developmental stages.This review explores the effects of adequate or deficient N and P levels on cotton growth phases,focusing on their influence on physiological processes and molecular mechanisms.Key topics include the regulation of N-and P-related enzymes,hormones,and genes,as well as the complex interplay of N-and P-related signaling pathways from the aspects of N-P signaling integration to regulate root development,N-P signaling integration to regulate nutrient uptake,and regulation of N-P interactions—a frontier in current research.Strategies for improving N and P use efficiency are also discussed,including developing high-efficiency cotton cultivars and identifying functional genes to enhance productivity.Generally speaking,we take model plants as a reference in the hope of coming up with new strategies for the efficient utilization of N and P in cotton.
