The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversari...The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversarial networks(GANs)emanating in the category of machine learning(ML)frameworks are used to generate and assess the rationality of the data.While their optimization is based on the long short-term memory(LSTM)strategies.In addition to drawing a heat map,the optimal path of two-dimensional(2D)diffusion is simultaneously demonstrated in a stereoscopic space.The results of our simulation are completely consistent with the previous theoretical predictions.展开更多
A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is proposed.Unlike the traditional road network model,in the SLSD conceptual model,being single-directional an...A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is proposed.Unlike the traditional road network model,in the SLSD conceptual model,being single-directional and single-line style,a road is no longer a linkage of road nodes but abstracted as a network node.Similarly,a road node is abstracted as the linkage of two ordered single-directional roads.This model can describe turn restrictions,circular roads,and other real scenarios usually described using a super-graph.Then a computing framework for optimal path finding（OPF）is presented.It is proved that classical Dijkstra and A algorithms can be directly used for OPF computing of any real-world road networks by transferring a super-graph to an SLSD network.Finally,using Singapore road network data,the proposed conceptual model and its corresponding optimal path finding algorithms are validated using a two-step optimal path finding algorithm with a pre-computing strategy based on the SLSD road network.展开更多
A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK ...A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.展开更多
As an important role in the urban land price system, the basic land price appraisal directs and refleets all kinds of land price in the real estate market. Using geographic information systems （GIS） with algo rithms...As an important role in the urban land price system, the basic land price appraisal directs and refleets all kinds of land price in the real estate market. Using geographic information systems （GIS） with algo rithms and powerful analysis functions to valuate land will improve the rationality and convenience of land valu- ation. The objective of the study on basic land price using the optimal path algorithm is to decrease the man made error, enhance automatization, avoid make inconvenience by roadblock object.展开更多
A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as mea...A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.展开更多
In this paper output predictive algorithm is applied to the design of predictive controller for an optimal path terrain following system. In this way, the error of path tracking is decreased to a minimum degree simply...In this paper output predictive algorithm is applied to the design of predictive controller for an optimal path terrain following system. In this way, the error of path tracking is decreased to a minimum degree simply and efficiently and the computation time for the optimal path is shortened greatly. Therefore, the real-time processing of the optimal path terrain following system is made to be very helpful.展开更多
The optimal path algorithm analysis of GPS navigation in taxi management system based on A＊ algorithm was introduced in this paper. Through improving the traditional Dijkstra algorithm and avoiding problems such as ...The optimal path algorithm analysis of GPS navigation in taxi management system based on A＊ algorithm was introduced in this paper. Through improving the traditional Dijkstra algorithm and avoiding problems such as ＂time-consuming and low efficiency＂ in Dijkstra algorithm with traversal search for each node, A＊ algorithm could help the taxi find the optimal path and bring convenience for traffic management.展开更多
Path tracking performed by multiple chassis actuators remains a significant yet challenging issue in intelligent vehicles.This paper presents a robust optimal path tracking control for intelligent vehicles equipped wi...Path tracking performed by multiple chassis actuators remains a significant yet challenging issue in intelligent vehicles.This paper presents a robust optimal path tracking control for intelligent vehicles equipped with a novel wheel module.A wheel module,named corner drive system(CDS),is proposed by integrating drive,brake,steering,and suspension subsystems.In light of the multi-actuator-integrate characteristic of the CDS,a reconfigurable concept is adopted to carry out the vehicle dynamics modeling.To realize an invariance system for both parametric and nonparametric uncertainties,an integral sliding mode control(ISMC)scheme is devised for desired path tracking by combining the advantages of linear quadratic regulator(LQR)in optimization and SMC in robustness.The chattering problem of the ISMC is analyzed and two continuous controllers for chattering elimination are proposed.A control allocation strategy is proposed to dynamically assign the virtual inputs generated by ISMC among four wheels to optimize vehicle stability and minimize energy dissipation.The superiority of the proposed control scheme is demonstrated under different chassis layouts,road friction conditions,and benchmark controllers on a CarSim-based high-fidelity vehicle model with simulation comparison.Subsequently,the Hardware-in-the-Loop(HiL)test is carried out to further evaluate the feasibility and real-time control performance.The quantitative results demonstrate the path tracking performance of the proposed robust optimal controller under both parametric and nonparametric uncertainties.展开更多
In order to alleviate urban traffic congestion and provide fast vehicle paths,a hidden Markov model(HMM)based on multi-feature data of urban regional roads is constructed to solve the problems of low recognition rate ...In order to alleviate urban traffic congestion and provide fast vehicle paths,a hidden Markov model(HMM)based on multi-feature data of urban regional roads is constructed to solve the problems of low recognition rate and poor instability of traditional model algorithms.At first,the HHM is obtained by training.Then according to dynamic planning principle,the traffic states of intersections are obtained by the Viterbi algorithm.Finally,the optimal path is selected based on the obtained traffic states of intersections.The experiment results show that the proposed method is superior to other algorithms in road unobstruction rate and recognition rate under complex road conditions.展开更多
Based on a differentiable merit function proposed by Taji et al. in ＂Math. Prog. Stud., 58, 1993, 369-383＂, the authors propose an affine scaling interior trust region strategy via optimal path to modify Newton meth...Based on a differentiable merit function proposed by Taji et al. in ＂Math. Prog. Stud., 58, 1993, 369-383＂, the authors propose an affine scaling interior trust region strategy via optimal path to modify Newton method for the strictly monotone variational inequality problem subject to linear equality and inequality constraints. By using the eigensystem decomposition and affine scaling mapping, the authors form an affine scaling optimal curvilinear path very easily in order to approximately solve the trust region subproblem. Theoretical analysis is given which shows that the proposed algorithm is globally convergent and has a local quadratic convergence rate under some reasonable conditions.展开更多
United Nations’7th Sustainable Development Goal envisions the availability of modern energy for everyone by 2030.While the progress has been satisfactory in the last few years,further rural electrification is increas...United Nations’7th Sustainable Development Goal envisions the availability of modern energy for everyone by 2030.While the progress has been satisfactory in the last few years,further rural electrification is increasingly challenging.The current mainstream approach of electrifying villages individually is becoming cost-ineffective due to uncertainties in both resource availability and energy demand for small,difficult-to-reach,residences.A networked rural electrification model,i.e.a cost-optimized network connecting villages and generation facilities,could improve resources utilization,reliability and flexibility.However,determining optimal paths with common search algorithms is extremely inefficient due to complex topographic features of rural areas.This work develops and applies an artificial intelligence search method to efficiently route inter-village power connections in the common rural electrification situation where substantial topological variations exist.The method is evolved from the canonical A*algorithm.Results compare favorably with optimal A*results,at significantly reduced computational effort.Furthermore,users can adaptively trade-off between computation speed and optimality and hence quickly evaluate sites and configurations at reasonable accuracy,which is impossible with classical methods.展开更多
Undergraduate student’s satisfaction is fundamental to creating and implementing successful higher education.The present study sought to identify the factors and analyses impact on satisfaction and service quality.Th...Undergraduate student’s satisfaction is fundamental to creating and implementing successful higher education.The present study sought to identify the factors and analyses impact on satisfaction and service quality.The research was carried out in Chinese higher education institution,with a sample of 1660 students.Based on the higher education satisfaction questionnaire,the“optimal path”model of problem improvement was constructed by applying the“structural equation model”,satisfaction and importance matrix diagram,improvement effect size and other tools.Eight major areas of three-dimensional improvement of“satisfaction,importance,and improvement effect”were formed.Identify the issues that students have urgent demands,high importance,and strong improvement effects.Scientifically analyze the main attention focus of each subgroup of students.Concentrate superior resources and strengths,formulate targeted measures and make key breakthroughs based on“light”,“heavy”,“slow”,“urgent”and“classified”.Provide suggestions for improving student’s satisfaction and promoting the development of high-quality connotative and characteristic development in higher education.展开更多
Consideration of the travel time variation for rescue vehicles is significant in the field of emergency management research.Because of uncertain factors,such as the weather or OD(origin-destination)variations caused b...Consideration of the travel time variation for rescue vehicles is significant in the field of emergency management research.Because of uncertain factors,such as the weather or OD(origin-destination)variations caused by traffic accidents,travel time is a random variable.In emergency situations,it is particularly necessary to determine the optimal reliable route of rescue vehicles from the perspective of uncertainty.This paper first proposes an optimal reliable path finding(ORPF)model for rescue vehicles,which considers the uncertainties of travel time,and link correlations.On this basis,it investigates how to optimize rescue vehicle allocation to minimize rescue time,taking into account travel time reliability under uncertain conditions.Because of the non-additive property of the objective function,this paper adopts a heuristic algorithm based on the K-shortest path algorithm,and inequality techniques to tackle the proposed modified integer programming model.Finally,the numerical experiments are presented to verify the accuracy and effectiveness of the proposed model and algorithm.The results show that ignoring travel time reliability may lead to an over-or under-estimation of the effective travel time of rescue vehicles on a particular path,and thereby an incorrect allocation scheme.展开更多
Due to the rigorous fiscal terms and huge potential risk of risk service contracts,optimizing oil production paths is one of the main challenges in designing oilfield development plans.In this paper,an oil production ...Due to the rigorous fiscal terms and huge potential risk of risk service contracts,optimizing oil production paths is one of the main challenges in designing oilfield development plans.In this paper,an oil production path optimization model is developed to maximize economic benefits within constraints of technology factors and oil contracts.This analysis describes the effects of risk service contract terms on parameters of inputs and outputs and quantifies the relationships between production and production time,revenues,investment and costs.An oil service development and production project is illustrated in which the optimal production path under its own geological conditions and contract terms is calculated.The influences of oil price,service fees per barrel and operating costs on the optimal production have been examined by sensitivity analysis.The results show that the oil price has the largest impact on the optimal production,which is negatively related to oil price and positively related to service fees per barrel and operating costs.展开更多
Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical ...Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.展开更多
The Report of the 20th National Congress of the Communist Party of China explicitly emphasized the promotion of educational digitalization.The rapid development of new media in the era of network information has not o...The Report of the 20th National Congress of the Communist Party of China explicitly emphasized the promotion of educational digitalization.The rapid development of new media in the era of network information has not only broadened the horizons of college students but also profoundly transformed the content and methods of ideological and political education.As the frontline of ideological work,colleges and universities in Xinjiang are guided by the Party’s strategy for governing Xinjiang in the new era to advance network ideological and political education.This is of great significance in guiding students to develop correct network literacy and promoting ideological and political education to keep pace with the times.Through methods such as text analysis,questionnaire surveys,and interviews,this paper outlines the concept,characteristics,and value of network ideological and political education in colleges and universities in Xinjiang,analyzes its current development status and existing issues,and proposes optimization paths such as adhering to correct political guidance,highlighting regional characteristics,innovating educational methods,and strengthening subject construction.These efforts aim to fulfill the fundamental task of“cultivating talents with moral integrity”and serve the overall goal of social stability and long-term peace in Xinjiang.展开更多
Sampling-based path planning is a popular methodology for robot path planning.With a uniform sampling strategy to explore the state space,a feasible path can be found without the complex geometric modeling of the conf...Sampling-based path planning is a popular methodology for robot path planning.With a uniform sampling strategy to explore the state space,a feasible path can be found without the complex geometric modeling of the configuration space.However,the quality of the initial solution is not guaranteed,and the convergence speed to the optimal solution is slow.In this paper,we present a novel image-based path planning algorithm to overcome these limitations.Specifically,a generative adversarial network(GAN)is designed to take the environment map(denoted as RGB image)as the input without other preprocessing works.The output is also an RGB image where the promising region(where a feasible path probably exists)is segmented.This promising region is utilized as a heuristic to achieve non-uniform sampling for the path planner.We conduct a number of simulation experiments to validate the effectiveness of the proposed method,and the results demonstrate that our method performs much better in terms of the quality of the initial solution and the convergence speed to the optimal solution.Furthermore,apart from the environments similar to the training set,our method also works well on the environments which are very different from the training set.展开更多
A hardware/software co-synthesis method is presented for SoC designs consisting of both hardware IP cores and software components on a graph-theoretic formulation. Given a SoC integrated with a set of functions and a ...A hardware/software co-synthesis method is presented for SoC designs consisting of both hardware IP cores and software components on a graph-theoretic formulation. Given a SoC integrated with a set of functions and a set of performance factors, a core for each function is selected from a set of alternative IP cores and software components, and optimal partitions is found in a way to evenly balance the performance factors and to ultimately reduce the overall cost, size, power consumption and runtime of the core-based SoC. The algorithm formulates IP cores and components into the corresponding mathematical models, presents a graph-theoretic model for finding the optimal partitions of SoC design and transforms SoC hardware/software co-synthesis problem into finding optimal paths in a weighted, directed graph. Overcoming the three main deficiencies of the traditional methods, this method can work automatically, evaluate more performance factors at the same time and meet the particularity of SoC designs. At last, the approach is illustrated that is practical and effective through partitioning a practical system.展开更多
In milling around sharp corners, residual materials are left at sharp corners when the stepover is extremely long in the contour-parallel tool path. Milling force at the sharp corner rises momentarily due to the incre...In milling around sharp corners, residual materials are left at sharp corners when the stepover is extremely long in the contour-parallel tool path. Milling force at the sharp corner rises momentarily due to the increase of the cutter contact length, thus shortening the tool life and leading to machine chatter, even cutter breakage. Then a tool path improvement method by inserting biarc transition segments in the contour-parallel tool path is proposed for milling the pocket. Using the method, the cutter moves along the biarc transition tool path. And the corner material is removed. The improved tool path is continuous for clearing residual materials at the sharp corner. Finally, the machining experiment validates the proposed method.展开更多
Using sensor and GPS to make a trajectory planning for the stationary obstacle, autonommus mobile robot can asstmae that it is placed at the center of the map, and from the distance information between autonomous mobi...Using sensor and GPS to make a trajectory planning for the stationary obstacle, autonommus mobile robot can asstmae that it is placed at the center of the map, and from the distance information between autonomous mobile robot and obstacles. But in case of active moving obstacle, many components and information need to process since their moving trace should be considered in real time. This paper mobile robot＇s driving algorithm of unknown dynamic envirormaent in order to drive intelligently to destination using ultrasonic and Global Positional Systern （GPS）. Sensors adjusted the placement dependment on driving of robot, and the robot plans the evasion method according to obstacle which are detected by sensors. The robot saves GPS coordinate of complex obstacle. If there are many repeated driving, robot creates new obstacles to the hr, ation by itself. And then it drives to the destination resolving a large range of local minirmnn point If it needs an intelligent circtmtantial decision, a proposed algorithm is suited for effective obstacle avoidance and arrival at the destination by performing simulations.展开更多
基金supported by the Natural Science Foundation of Shandong Province(Grant No.ZR2020MA092)the Innovation Project for Graduate Students of Ludong University(Grant No.IPGS2024-048).
文摘The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversarial networks(GANs)emanating in the category of machine learning(ML)frameworks are used to generate and assess the rationality of the data.While their optimization is based on the long short-term memory(LSTM)strategies.In addition to drawing a heat map,the optimal path of two-dimensional(2D)diffusion is simultaneously demonstrated in a stereoscopic space.The results of our simulation are completely consistent with the previous theoretical predictions.
基金The National Key Technology R&D Program of China during the 11th Five Year Plan Period(No.2008BAJ11B01)
文摘A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is proposed.Unlike the traditional road network model,in the SLSD conceptual model,being single-directional and single-line style,a road is no longer a linkage of road nodes but abstracted as a network node.Similarly,a road node is abstracted as the linkage of two ordered single-directional roads.This model can describe turn restrictions,circular roads,and other real scenarios usually described using a super-graph.Then a computing framework for optimal path finding（OPF）is presented.It is proved that classical Dijkstra and A algorithms can be directly used for OPF computing of any real-world road networks by transferring a super-graph to an SLSD network.Finally,using Singapore road network data,the proposed conceptual model and its corresponding optimal path finding algorithms are validated using a two-step optimal path finding algorithm with a pre-computing strategy based on the SLSD road network.
文摘A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.
文摘As an important role in the urban land price system, the basic land price appraisal directs and refleets all kinds of land price in the real estate market. Using geographic information systems （GIS） with algo rithms and powerful analysis functions to valuate land will improve the rationality and convenience of land valu- ation. The objective of the study on basic land price using the optimal path algorithm is to decrease the man made error, enhance automatization, avoid make inconvenience by roadblock object.
基金Project(71001079)supported by the National Natural Science Foundation of China
文摘A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.
文摘In this paper output predictive algorithm is applied to the design of predictive controller for an optimal path terrain following system. In this way, the error of path tracking is decreased to a minimum degree simply and efficiently and the computation time for the optimal path is shortened greatly. Therefore, the real-time processing of the optimal path terrain following system is made to be very helpful.
文摘The optimal path algorithm analysis of GPS navigation in taxi management system based on A＊ algorithm was introduced in this paper. Through improving the traditional Dijkstra algorithm and avoiding problems such as ＂time-consuming and low efficiency＂ in Dijkstra algorithm with traversal search for each node, A＊ algorithm could help the taxi find the optimal path and bring convenience for traffic management.
基金supported by the“Beijing Natural Science Foundation”under Grant L233039“Pioneer and Leading Goose R&D Program of Zhejiang”under Grant 2023C01133“Key R&D Program of Ningbo”under Grant 2023Z014.
文摘Path tracking performed by multiple chassis actuators remains a significant yet challenging issue in intelligent vehicles.This paper presents a robust optimal path tracking control for intelligent vehicles equipped with a novel wheel module.A wheel module,named corner drive system(CDS),is proposed by integrating drive,brake,steering,and suspension subsystems.In light of the multi-actuator-integrate characteristic of the CDS,a reconfigurable concept is adopted to carry out the vehicle dynamics modeling.To realize an invariance system for both parametric and nonparametric uncertainties,an integral sliding mode control(ISMC)scheme is devised for desired path tracking by combining the advantages of linear quadratic regulator(LQR)in optimization and SMC in robustness.The chattering problem of the ISMC is analyzed and two continuous controllers for chattering elimination are proposed.A control allocation strategy is proposed to dynamically assign the virtual inputs generated by ISMC among four wheels to optimize vehicle stability and minimize energy dissipation.The superiority of the proposed control scheme is demonstrated under different chassis layouts,road friction conditions,and benchmark controllers on a CarSim-based high-fidelity vehicle model with simulation comparison.Subsequently,the Hardware-in-the-Loop(HiL)test is carried out to further evaluate the feasibility and real-time control performance.The quantitative results demonstrate the path tracking performance of the proposed robust optimal controller under both parametric and nonparametric uncertainties.
基金Natural Science Foundation of Gansu Provincial Science&Technology Department(No.1504GKCA018)。
文摘In order to alleviate urban traffic congestion and provide fast vehicle paths,a hidden Markov model(HMM)based on multi-feature data of urban regional roads is constructed to solve the problems of low recognition rate and poor instability of traditional model algorithms.At first,the HHM is obtained by training.Then according to dynamic planning principle,the traffic states of intersections are obtained by the Viterbi algorithm.Finally,the optimal path is selected based on the obtained traffic states of intersections.The experiment results show that the proposed method is superior to other algorithms in road unobstruction rate and recognition rate under complex road conditions.
基金the National Natural Science Foundation of China(No.10471094)the Doctoral Programmer Foundation of the Ministry of Education of China(No.0527003)+1 种基金the Shanghai Leading Academic Discipline Project(No.T0401)and the Science Foundation Grant of Shanghai Municipal Education Committee(Nos.05DZ11,06A110).
文摘Based on a differentiable merit function proposed by Taji et al. in ＂Math. Prog. Stud., 58, 1993, 369-383＂, the authors propose an affine scaling interior trust region strategy via optimal path to modify Newton method for the strictly monotone variational inequality problem subject to linear equality and inequality constraints. By using the eigensystem decomposition and affine scaling mapping, the authors form an affine scaling optimal curvilinear path very easily in order to approximately solve the trust region subproblem. Theoretical analysis is given which shows that the proposed algorithm is globally convergent and has a local quadratic convergence rate under some reasonable conditions.
文摘United Nations’7th Sustainable Development Goal envisions the availability of modern energy for everyone by 2030.While the progress has been satisfactory in the last few years,further rural electrification is increasingly challenging.The current mainstream approach of electrifying villages individually is becoming cost-ineffective due to uncertainties in both resource availability and energy demand for small,difficult-to-reach,residences.A networked rural electrification model,i.e.a cost-optimized network connecting villages and generation facilities,could improve resources utilization,reliability and flexibility.However,determining optimal paths with common search algorithms is extremely inefficient due to complex topographic features of rural areas.This work develops and applies an artificial intelligence search method to efficiently route inter-village power connections in the common rural electrification situation where substantial topological variations exist.The method is evolved from the canonical A*algorithm.Results compare favorably with optimal A*results,at significantly reduced computational effort.Furthermore,users can adaptively trade-off between computation speed and optimality and hence quickly evaluate sites and configurations at reasonable accuracy,which is impossible with classical methods.
基金supported by the Chongqing Education Science Planning funds,and the project is 2021-GX-114.
文摘Undergraduate student’s satisfaction is fundamental to creating and implementing successful higher education.The present study sought to identify the factors and analyses impact on satisfaction and service quality.The research was carried out in Chinese higher education institution,with a sample of 1660 students.Based on the higher education satisfaction questionnaire,the“optimal path”model of problem improvement was constructed by applying the“structural equation model”,satisfaction and importance matrix diagram,improvement effect size and other tools.Eight major areas of three-dimensional improvement of“satisfaction,importance,and improvement effect”were formed.Identify the issues that students have urgent demands,high importance,and strong improvement effects.Scientifically analyze the main attention focus of each subgroup of students.Concentrate superior resources and strengths,formulate targeted measures and make key breakthroughs based on“light”,“heavy”,“slow”,“urgent”and“classified”.Provide suggestions for improving student’s satisfaction and promoting the development of high-quality connotative and characteristic development in higher education.
基金Projects(72071202,71671184)supported by the National Natural Science Foundation of ChinaProject(22YJCZH144)supported by Humanities and Social Sciences Youth Foundation,Ministry of Education of China+3 种基金Project(2022M712680)supported by Postdoctoral Research Foundation of ChinaProject(22KJB110027)supported by Natural Science Foundation of Colleges and Universities in Jiangsu Province,ChinaProject(D2019046)supported by Initiation Foundation of Xuzhou Medical University,ChinaProject(2021SJA1079)supported by General Project of Philosophy and Social Science Research in Jiangsu Universities,China。
文摘Consideration of the travel time variation for rescue vehicles is significant in the field of emergency management research.Because of uncertain factors,such as the weather or OD(origin-destination)variations caused by traffic accidents,travel time is a random variable.In emergency situations,it is particularly necessary to determine the optimal reliable route of rescue vehicles from the perspective of uncertainty.This paper first proposes an optimal reliable path finding(ORPF)model for rescue vehicles,which considers the uncertainties of travel time,and link correlations.On this basis,it investigates how to optimize rescue vehicle allocation to minimize rescue time,taking into account travel time reliability under uncertain conditions.Because of the non-additive property of the objective function,this paper adopts a heuristic algorithm based on the K-shortest path algorithm,and inequality techniques to tackle the proposed modified integer programming model.Finally,the numerical experiments are presented to verify the accuracy and effectiveness of the proposed model and algorithm.The results show that ignoring travel time reliability may lead to an over-or under-estimation of the effective travel time of rescue vehicles on a particular path,and thereby an incorrect allocation scheme.
基金Funding for this work was provided by the Major Project from the National Social Science Foundation of China through research on replacement strategies for overseas oil and gas resources based on the perspective of China’s petroleum security under the project number 11&ZD164
文摘Due to the rigorous fiscal terms and huge potential risk of risk service contracts,optimizing oil production paths is one of the main challenges in designing oilfield development plans.In this paper,an oil production path optimization model is developed to maximize economic benefits within constraints of technology factors and oil contracts.This analysis describes the effects of risk service contract terms on parameters of inputs and outputs and quantifies the relationships between production and production time,revenues,investment and costs.An oil service development and production project is illustrated in which the optimal production path under its own geological conditions and contract terms is calculated.The influences of oil price,service fees per barrel and operating costs on the optimal production have been examined by sensitivity analysis.The results show that the oil price has the largest impact on the optimal production,which is negatively related to oil price and positively related to service fees per barrel and operating costs.
文摘Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.
基金Social Science Fund Project of the Xinjiang Uygur Autonomous Region“Research on the Construction of Network Ideological Discourse Power in Colleges and Universities in Xinjiang”(2023BKS010)。
文摘The Report of the 20th National Congress of the Communist Party of China explicitly emphasized the promotion of educational digitalization.The rapid development of new media in the era of network information has not only broadened the horizons of college students but also profoundly transformed the content and methods of ideological and political education.As the frontline of ideological work,colleges and universities in Xinjiang are guided by the Party’s strategy for governing Xinjiang in the new era to advance network ideological and political education.This is of great significance in guiding students to develop correct network literacy and promoting ideological and political education to keep pace with the times.Through methods such as text analysis,questionnaire surveys,and interviews,this paper outlines the concept,characteristics,and value of network ideological and political education in colleges and universities in Xinjiang,analyzes its current development status and existing issues,and proposes optimization paths such as adhering to correct political guidance,highlighting regional characteristics,innovating educational methods,and strengthening subject construction.These efforts aim to fulfill the fundamental task of“cultivating talents with moral integrity”and serve the overall goal of social stability and long-term peace in Xinjiang.
基金This work was partially supported by National Key R&D Program of China(2019YFB1312400)Shenzhen Key Laboratory of Robotics Perception and Intelligence(ZDSYS20200810171800001)+1 种基金Hong Kong RGC GRF(14200618)Hong Kong RGC CRF(C4063-18G).
文摘Sampling-based path planning is a popular methodology for robot path planning.With a uniform sampling strategy to explore the state space,a feasible path can be found without the complex geometric modeling of the configuration space.However,the quality of the initial solution is not guaranteed,and the convergence speed to the optimal solution is slow.In this paper,we present a novel image-based path planning algorithm to overcome these limitations.Specifically,a generative adversarial network(GAN)is designed to take the environment map(denoted as RGB image)as the input without other preprocessing works.The output is also an RGB image where the promising region(where a feasible path probably exists)is segmented.This promising region is utilized as a heuristic to achieve non-uniform sampling for the path planner.We conduct a number of simulation experiments to validate the effectiveness of the proposed method,and the results demonstrate that our method performs much better in terms of the quality of the initial solution and the convergence speed to the optimal solution.Furthermore,apart from the environments similar to the training set,our method also works well on the environments which are very different from the training set.
基金This project was supported by the Defense Pre-Research Project of the ‘Tenth Five-Year-Plan’ of China(41315040106) and the National"863"High Technology Research and Development Programof China (2003AAIZ2210)
文摘A hardware/software co-synthesis method is presented for SoC designs consisting of both hardware IP cores and software components on a graph-theoretic formulation. Given a SoC integrated with a set of functions and a set of performance factors, a core for each function is selected from a set of alternative IP cores and software components, and optimal partitions is found in a way to evenly balance the performance factors and to ultimately reduce the overall cost, size, power consumption and runtime of the core-based SoC. The algorithm formulates IP cores and components into the corresponding mathematical models, presents a graph-theoretic model for finding the optimal partitions of SoC design and transforms SoC hardware/software co-synthesis problem into finding optimal paths in a weighted, directed graph. Overcoming the three main deficiencies of the traditional methods, this method can work automatically, evaluate more performance factors at the same time and meet the particularity of SoC designs. At last, the approach is illustrated that is practical and effective through partitioning a practical system.
文摘In milling around sharp corners, residual materials are left at sharp corners when the stepover is extremely long in the contour-parallel tool path. Milling force at the sharp corner rises momentarily due to the increase of the cutter contact length, thus shortening the tool life and leading to machine chatter, even cutter breakage. Then a tool path improvement method by inserting biarc transition segments in the contour-parallel tool path is proposed for milling the pocket. Using the method, the cutter moves along the biarc transition tool path. And the corner material is removed. The improved tool path is continuous for clearing residual materials at the sharp corner. Finally, the machining experiment validates the proposed method.
基金supported by the MKE(The Ministry of Knowledge Economy),Koreathe ITRC(Information Technology Research Center)support program(NIPA-2010-C1090-1021-0010)
文摘Using sensor and GPS to make a trajectory planning for the stationary obstacle, autonommus mobile robot can asstmae that it is placed at the center of the map, and from the distance information between autonomous mobile robot and obstacles. But in case of active moving obstacle, many components and information need to process since their moving trace should be considered in real time. This paper mobile robot＇s driving algorithm of unknown dynamic envirormaent in order to drive intelligently to destination using ultrasonic and Global Positional Systern （GPS）. Sensors adjusted the placement dependment on driving of robot, and the robot plans the evasion method according to obstacle which are detected by sensors. The robot saves GPS coordinate of complex obstacle. If there are many repeated driving, robot creates new obstacles to the hr, ation by itself. And then it drives to the destination resolving a large range of local minirmnn point If it needs an intelligent circtmtantial decision, a proposed algorithm is suited for effective obstacle avoidance and arrival at the destination by performing simulations.
