Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the f...Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.展开更多
In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a ...In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.展开更多
Path planning for Unmanned Aerial Vehicles(UAVs)in complex environments presents several challenges.Traditional algorithms often struggle with the complexity of high-dimensional search spaces,leading to inefficiencies...Path planning for Unmanned Aerial Vehicles(UAVs)in complex environments presents several challenges.Traditional algorithms often struggle with the complexity of high-dimensional search spaces,leading to inefficiencies.Additionally,the non-linear nature of cost functions can cause algorithms to become trapped in local optima.Furthermore,there is often a lack of adequate consideration for real-world constraints,for example,due to the necessity for obstacle avoidance or because of the restrictions of flight safety.To address the aforementioned issues,this paper proposes a dynamic weighted spherical particle swarm optimization(DW-SPSO)algorithm.The algorithm adopts a dual Sigmoid-based adaptive weight adjustment mechanism for balancing global exploration and local exploitation,as well as a lens-based opposition learning one to improve search flexibility and solution diversity.Simulation experiments on real digital elevation models demonstrate that DW-SPSO significantly outperforms recent state-of-the-art particle swarm optimization(PSO)variants in terms of path safety,smoothness,and convergence speed.The performance superiority is statistically validated by the Wilcoxon signed-rank test.The results confirm the algorithm’s effectiveness in generating high-quality UAV paths under diverse threat conditions,offering a robust solution for autonomous navigation systems.展开更多
An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale...An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale wind/solar farms with shunt static var generators(SVGs).The model explicitly represents reactive-power regulation characteristics of doubly-fed wind turbines and PV inverters under real-time meteorological conditions,and quantifies SVG high-speed compensation capability,enabling seamless transition from localized VAR management to a globally coordinated strategy.An enhanced adaptive gain-sharing knowledge optimizer(AGSK-SD)integrates simulated annealing and diversity maintenance to autonomously tune voltage-control actions,renewable source reactive-power set-points,and SVG output.The algorithm adaptively modulates knowledge factors and ratios across search phases,performs SA-based fine-grained local exploitation,and periodically re-injects population diversity to prevent premature convergence.Comprehensive tests on IEEE 9-bus and 39-bus systems demonstrate AGSK-SD’s superiority over NSGA-II and MOPSO in hypervolume(HV),inverse generative distance(IGD),and spread metrics while maintaining acceptable computational burden.The method reduces network losses from 2.7191 to 2.15 MW(20.79%reduction)and from 15.1891 to 11.22 MW(26.16%reduction)in the 9-bus and 39-bus systems respectively.Simultaneously,the cumulative voltage-deviation index decreases from 0.0277 to 3.42×10^(−4) p.u.(98.77%reduction)in the 9-bus system,and from 0.0556 to 0.0107 p.u.(80.76%reduction)in the 39-bus system.These improvements demonstrate significant suppression of line losses and voltage fluctuations.Comparative analysis with traditional heuristic optimization algorithms confirms the superior performance of the proposed approach.展开更多
Since the 1990s, the Yellow River stream has been temporarily interrupted for several years, which affects the development of society, the economy and human life, limits the economic potential of the drainage areas, a...Since the 1990s, the Yellow River stream has been temporarily interrupted for several years, which affects the development of society, the economy and human life, limits the economic potential of the drainage areas, and especially causes great harm to regions on the lower reaches. Based on the analysis of the relationship between the development of society and economy and water scarcity, the author thinks it is necessary to optimize and adjust the industrial structure that has extravagantly consumed enormous amounts of water, and to develop ecological agriculture, industry and tourism which are balanced with the ecological environment. Finally, the author puts forward several pieces of advice and countermeasures about how to build the economic systems by which water can be used economically.展开更多
Public art has practical significance by showing a variety of forms to explore the various design factors on the psychological reactions of different people. Public art should fit the characteristics of human physiolo...Public art has practical significance by showing a variety of forms to explore the various design factors on the psychological reactions of different people. Public art should fit the characteristics of human physiology and psychology. The mental aberration phenomenon induced by unhealthy circumstance could be adjusted and compensated by certain style of public art, and from which the optimization of psychological ecology is resulted. A variety of psychological ecology environment, such as gestalt, artistic exaggeration, implicit, pleasure, interesting, relax, mystery, intricacy, metaphor, and so on, could be constructed by different methods in public art. The excellent public art design optimizes the person's mental spiritual ecology, reduces the burden on people's lives and enhances the quality of life by using the meaningful forms and combinations to achieve the living environment and people's coordination.展开更多
With the rapid development of space activities,non-cooperative space targets increase swiftly,such as failed satellites and upper stages,threating normal spacecrafts seriously.As there are some problems in the capture...With the rapid development of space activities,non-cooperative space targets increase swiftly,such as failed satellites and upper stages,threating normal spacecrafts seriously.As there are some problems in the capture process,such as excessive collision and fast tumbling of targets,manipulator with redundant Degrees of Freedom(DOFs)can be used to improve the compliance and therefore solve these problems.The Rope-Driven Snake Manipulator(RDSM)is a combina-tion of hyper-redundant DOFs and better compliance,and therefore it is suitable for capturing mis-sion.In this paper,a snake manipulator mechanism is designed,and the complete kinematic model and system dynamic model considering RDSM,target and contact is established.Then,to obtain the configuration of joint with hyper-redundant DOFs,an improved motion dexterity index is pro-posed as the joint motion optimization target.Besides,the force-position collaborative optimization index is designed to adjust active stiffness,and the impedance control method based on the modified index is used to capture the space target.Finally,the proposed force-position collaborative opti-mization method is verified by virtual prototype co-simulation.The results demonstrate that based on the proposed method,the collision force is reduced by about 25%compared to normal impe-dance control,showing higher safety.展开更多
In this paper, the evolvement and the actual state of industrial structure in Guizhou was expounded. And the character and the existent issue of industrial structure in Guizhou were analyzed. The guideline and idea an...In this paper, the evolvement and the actual state of industrial structure in Guizhou was expounded. And the character and the existent issue of industrial structure in Guizhou were analyzed. The guideline and idea and goal about the adjustment of industrial structure in Guizhou were also put forward.展开更多
In the context of post-stimulation shale gas wells,the terms“shut-in”and“flowback”refer to two critical phases that occur after hydraulic fracturing(fracking)has been completed.These stages play a crucial role in ...In the context of post-stimulation shale gas wells,the terms“shut-in”and“flowback”refer to two critical phases that occur after hydraulic fracturing(fracking)has been completed.These stages play a crucial role in determining both the well’s initial production performance and its long-term hydrocarbon recovery.By establishing a comprehensive big data analysis platform,the flowback dynamics of over 1000 shale gas wells were analyzed in this work,leading to the development of an index system for evaluating flowback production capacity.Additionally,a shut-in chart was created for wells with different types of post-stimulation fracture networks,providing a structured approach to optimizing production strategies.A dynamic analysis method for flowback was also developed,using daily pressure drop and artificial fracture conductivity as key indicators.This method offers a systematic and effective approach to managing the shut-in and flowback processes for gas wells.Field trials demonstrated significant improvements:the probability of sand production was reduced,gas breakthrough time was extended,artificial fracture conductivity was enhanced,and the average estimated ultimate recovery(EUR)per well increased.展开更多
In the design of a shale-gas cluster horizontal well,it is necessary to consider the bypass of the fracturing influence domains of existing wells and the interference between fracturing influence domains when the well...In the design of a shale-gas cluster horizontal well,it is necessary to consider the bypass of the fracturing influence domains of existing wells and the interference between fracturing influence domains when the wellbore trajectories of infill adjustment wells in the fracturing areas are designed.In order to quickly evaluate the rationality of the design scheme of fracturing wellbore trajectory in an infill adjustment well,this paper adopted the vector algebra method to build a geometric model of the obstacles in the shale gas fracturing area.In this geometric model,the influence domains of hydraulic fractures are taken into account.Then,based on this geometric model,the optimization design model of bypass trajectory in the shale gas fracturing area was established by taking the minimization of total trajectory length and trajectory potential energy as the optimization objective and the anti-collision between trajectories as the constraint.Besides,the geometric check method to judge if there is any interference between fracturing influence domains was provided.Finally,the established optimization design model was verified based on the actual drilling data of Fuling Shale Gas Field in the Sichuan Basin.And the following research results were obtained.First,the obstacle sizes in fracturing areas will be seriously underestimated if the fracturing influence domains are neglected.Second,if the fracturing influence domains are neglected,the designed bypass trajectory can bypass the wellbore trajectories of old wells,but may intersect the fracturing influence domains of existing wells,thus inducing drilling accidents.In conclusion,the proposed optimization design model of bypass trajectory in the shale gas fracturing area can satisfy the constraint of anti-collision and bypass and achieve the optimization objective of minimizing total trajectory length and trajectory potential energy,and the corresponding design calculation avoids complex calculation and check.展开更多
Dear Editor,This letter is concerned with the problem of stable high-quality signal transmission of unmanned aerial vehicle(UAV)-assisted multiple-input multiple-output(MIMO)communication system.The particle swarm opt...Dear Editor,This letter is concerned with the problem of stable high-quality signal transmission of unmanned aerial vehicle(UAV)-assisted multiple-input multiple-output(MIMO)communication system.The particle swarm optimization(PSO)algorithm is used to achieve optimal beamforming and power allocation for this system.Additionally,sensitive particle(SP)and parameter adaptive adjustment are introduced into the traditional PSO algorithm,aiming to improve the performance of the PSO algorithm in dynamic environments with real-time changes in the UAV position.A reinforcement learning(RL)-based approach is proposed to obtain optimal UAV trajectory and adaptive adjustment strategy for PSO parameters,which combine with a specific obstacle avoidance scheme to achieve accurate UAV navigation while satisfying high-quality signal transmission.Simulation experiments show that our scheme provides higher and more stable spectral efficiency as well as more efficient UAV navigation than the currently commonly used scheme with a single RL approach.展开更多
基金funded by the“Research and Application Project of Collaborative Optimization Control Technology for Distribution Station Area for High Proportion Distributed PV Consumption(4000-202318079A-1-1-ZN)”of the Headquarters of the State Grid Corporation.
文摘Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.
基金supported by the National Natural Science Foundation of China under Grant 62472264the Natural Science Distinguished Youth Foundation of Shandong Province under Grant ZR2025QA13。
文摘In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.
基金supported by the National Natural Science Foundation of China(Grant No.62106092)the Natural Science Foundation of Fujian Province(Grant Nos.2024J01822,2025J01981)the Natural Science Foundation of Zhangzhou City(Grant No.ZZ2024J28).
文摘Path planning for Unmanned Aerial Vehicles(UAVs)in complex environments presents several challenges.Traditional algorithms often struggle with the complexity of high-dimensional search spaces,leading to inefficiencies.Additionally,the non-linear nature of cost functions can cause algorithms to become trapped in local optima.Furthermore,there is often a lack of adequate consideration for real-world constraints,for example,due to the necessity for obstacle avoidance or because of the restrictions of flight safety.To address the aforementioned issues,this paper proposes a dynamic weighted spherical particle swarm optimization(DW-SPSO)algorithm.The algorithm adopts a dual Sigmoid-based adaptive weight adjustment mechanism for balancing global exploration and local exploitation,as well as a lens-based opposition learning one to improve search flexibility and solution diversity.Simulation experiments on real digital elevation models demonstrate that DW-SPSO significantly outperforms recent state-of-the-art particle swarm optimization(PSO)variants in terms of path safety,smoothness,and convergence speed.The performance superiority is statistically validated by the Wilcoxon signed-rank test.The results confirm the algorithm’s effectiveness in generating high-quality UAV paths under diverse threat conditions,offering a robust solution for autonomous navigation systems.
基金supported by Yunnan Power Grid Co.,Ltd.Science and Technology Project:Research and application of key technologies for graphical-based power grid accident reconstruction and simulation(YNKJXM20240333).
文摘An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale wind/solar farms with shunt static var generators(SVGs).The model explicitly represents reactive-power regulation characteristics of doubly-fed wind turbines and PV inverters under real-time meteorological conditions,and quantifies SVG high-speed compensation capability,enabling seamless transition from localized VAR management to a globally coordinated strategy.An enhanced adaptive gain-sharing knowledge optimizer(AGSK-SD)integrates simulated annealing and diversity maintenance to autonomously tune voltage-control actions,renewable source reactive-power set-points,and SVG output.The algorithm adaptively modulates knowledge factors and ratios across search phases,performs SA-based fine-grained local exploitation,and periodically re-injects population diversity to prevent premature convergence.Comprehensive tests on IEEE 9-bus and 39-bus systems demonstrate AGSK-SD’s superiority over NSGA-II and MOPSO in hypervolume(HV),inverse generative distance(IGD),and spread metrics while maintaining acceptable computational burden.The method reduces network losses from 2.7191 to 2.15 MW(20.79%reduction)and from 15.1891 to 11.22 MW(26.16%reduction)in the 9-bus and 39-bus systems respectively.Simultaneously,the cumulative voltage-deviation index decreases from 0.0277 to 3.42×10^(−4) p.u.(98.77%reduction)in the 9-bus system,and from 0.0556 to 0.0107 p.u.(80.76%reduction)in the 39-bus system.These improvements demonstrate significant suppression of line losses and voltage fluctuations.Comparative analysis with traditional heuristic optimization algorithms confirms the superior performance of the proposed approach.
文摘Since the 1990s, the Yellow River stream has been temporarily interrupted for several years, which affects the development of society, the economy and human life, limits the economic potential of the drainage areas, and especially causes great harm to regions on the lower reaches. Based on the analysis of the relationship between the development of society and economy and water scarcity, the author thinks it is necessary to optimize and adjust the industrial structure that has extravagantly consumed enormous amounts of water, and to develop ecological agriculture, industry and tourism which are balanced with the ecological environment. Finally, the author puts forward several pieces of advice and countermeasures about how to build the economic systems by which water can be used economically.
基金Sponsored by State Scholarship Fund sponsored by China Scholarship Council(201307095001)
文摘Public art has practical significance by showing a variety of forms to explore the various design factors on the psychological reactions of different people. Public art should fit the characteristics of human physiology and psychology. The mental aberration phenomenon induced by unhealthy circumstance could be adjusted and compensated by certain style of public art, and from which the optimization of psychological ecology is resulted. A variety of psychological ecology environment, such as gestalt, artistic exaggeration, implicit, pleasure, interesting, relax, mystery, intricacy, metaphor, and so on, could be constructed by different methods in public art. The excellent public art design optimizes the person's mental spiritual ecology, reduces the burden on people's lives and enhances the quality of life by using the meaningful forms and combinations to achieve the living environment and people's coordination.
文摘With the rapid development of space activities,non-cooperative space targets increase swiftly,such as failed satellites and upper stages,threating normal spacecrafts seriously.As there are some problems in the capture process,such as excessive collision and fast tumbling of targets,manipulator with redundant Degrees of Freedom(DOFs)can be used to improve the compliance and therefore solve these problems.The Rope-Driven Snake Manipulator(RDSM)is a combina-tion of hyper-redundant DOFs and better compliance,and therefore it is suitable for capturing mis-sion.In this paper,a snake manipulator mechanism is designed,and the complete kinematic model and system dynamic model considering RDSM,target and contact is established.Then,to obtain the configuration of joint with hyper-redundant DOFs,an improved motion dexterity index is pro-posed as the joint motion optimization target.Besides,the force-position collaborative optimization index is designed to adjust active stiffness,and the impedance control method based on the modified index is used to capture the space target.Finally,the proposed force-position collaborative opti-mization method is verified by virtual prototype co-simulation.The results demonstrate that based on the proposed method,the collision force is reduced by about 25%compared to normal impe-dance control,showing higher safety.
文摘In this paper, the evolvement and the actual state of industrial structure in Guizhou was expounded. And the character and the existent issue of industrial structure in Guizhou were analyzed. The guideline and idea and goal about the adjustment of industrial structure in Guizhou were also put forward.
基金PetroChina Research Applied Science and Technology Project,“Shale Gas Scale Increase Production and Exploration andDevelopment Technology-Research and Application of Key Technology of Deep Shale Gas Scale Production”(No.2023ZZ21YJ01).
文摘In the context of post-stimulation shale gas wells,the terms“shut-in”and“flowback”refer to two critical phases that occur after hydraulic fracturing(fracking)has been completed.These stages play a crucial role in determining both the well’s initial production performance and its long-term hydrocarbon recovery.By establishing a comprehensive big data analysis platform,the flowback dynamics of over 1000 shale gas wells were analyzed in this work,leading to the development of an index system for evaluating flowback production capacity.Additionally,a shut-in chart was created for wells with different types of post-stimulation fracture networks,providing a structured approach to optimizing production strategies.A dynamic analysis method for flowback was also developed,using daily pressure drop and artificial fracture conductivity as key indicators.This method offers a systematic and effective approach to managing the shut-in and flowback processes for gas wells.Field trials demonstrated significant improvements:the probability of sand production was reduced,gas breakthrough time was extended,artificial fracture conductivity was enhanced,and the average estimated ultimate recovery(EUR)per well increased.
文摘In the design of a shale-gas cluster horizontal well,it is necessary to consider the bypass of the fracturing influence domains of existing wells and the interference between fracturing influence domains when the wellbore trajectories of infill adjustment wells in the fracturing areas are designed.In order to quickly evaluate the rationality of the design scheme of fracturing wellbore trajectory in an infill adjustment well,this paper adopted the vector algebra method to build a geometric model of the obstacles in the shale gas fracturing area.In this geometric model,the influence domains of hydraulic fractures are taken into account.Then,based on this geometric model,the optimization design model of bypass trajectory in the shale gas fracturing area was established by taking the minimization of total trajectory length and trajectory potential energy as the optimization objective and the anti-collision between trajectories as the constraint.Besides,the geometric check method to judge if there is any interference between fracturing influence domains was provided.Finally,the established optimization design model was verified based on the actual drilling data of Fuling Shale Gas Field in the Sichuan Basin.And the following research results were obtained.First,the obstacle sizes in fracturing areas will be seriously underestimated if the fracturing influence domains are neglected.Second,if the fracturing influence domains are neglected,the designed bypass trajectory can bypass the wellbore trajectories of old wells,but may intersect the fracturing influence domains of existing wells,thus inducing drilling accidents.In conclusion,the proposed optimization design model of bypass trajectory in the shale gas fracturing area can satisfy the constraint of anti-collision and bypass and achieve the optimization objective of minimizing total trajectory length and trajectory potential energy,and the corresponding design calculation avoids complex calculation and check.
基金supported by the National Natural Science Foundation of China(62173251,62203113the“Zhishan”Scholars Programs of Southeast University,and the Fundamental Research Funds for the Central Universities(2242023K30034).
文摘Dear Editor,This letter is concerned with the problem of stable high-quality signal transmission of unmanned aerial vehicle(UAV)-assisted multiple-input multiple-output(MIMO)communication system.The particle swarm optimization(PSO)algorithm is used to achieve optimal beamforming and power allocation for this system.Additionally,sensitive particle(SP)and parameter adaptive adjustment are introduced into the traditional PSO algorithm,aiming to improve the performance of the PSO algorithm in dynamic environments with real-time changes in the UAV position.A reinforcement learning(RL)-based approach is proposed to obtain optimal UAV trajectory and adaptive adjustment strategy for PSO parameters,which combine with a specific obstacle avoidance scheme to achieve accurate UAV navigation while satisfying high-quality signal transmission.Simulation experiments show that our scheme provides higher and more stable spectral efficiency as well as more efficient UAV navigation than the currently commonly used scheme with a single RL approach.
