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
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
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
An improved RRT∗algorithm,referred to as the AGP-RRT∗algorithm,is proposed to address the problems of poor directionality,long generated paths,and slow convergence speed in multi-axis robotic arm path planning.First,a...An improved RRT∗algorithm,referred to as the AGP-RRT∗algorithm,is proposed to address the problems of poor directionality,long generated paths,and slow convergence speed in multi-axis robotic arm path planning.First,an adaptive biased probabilistic sampling strategy is adopted to dynamically adjust the target deviation threshold and optimize the selection of random sampling points and the direction of generating new nodes in order to reduce the search space and improve the search efficiency.Second,a gravitationally adjustable step size strategy is used to guide the search process and dynamically adjust the step-size to accelerate the search speed of the algorithm.Finally,the planning path is processed by pruning,removing redundant points and path smoothing fitting using cubic B-spline curves to improve the flexibility of the robotic arm.Through the six-axis robotic arm path planning simulation experiments on the MATLAB platform,the results show that the AGP-RRT∗algorithm reduces 87.34%in terms of the average running time and 40.39%in terms of the average path cost;Meanwhile,under two sets of complex environments A and B,the average running time of the AGP-RRT∗algorithm is shortened by 94.56%vs.95.37%,and the average path cost is reduced by 55.28%vs.47.82%,which proves the effectiveness of the AGP-RRT∗algorithm in improving the efficiency of multi-axis robotic arm path planning.展开更多
With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated...With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery power.For this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this paper.Specifically,we use UAVs to assist the WSN in collecting data.In the current UAV-assisted WSN,the clustering and routing schemes are determined sequentially.However,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and routing.To efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing together.In the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing scheme.Therefore,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution faster.Unnecessary point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor nodes.To avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are indispensable.An emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of UAVs.Compared with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.展开更多
Seven tourist cities in eastern and western Guangdong were selected as the research objects to establish an evaluation index system of urban comprehensive carrying capacity,and its changing laws were analyzed.It was f...Seven tourist cities in eastern and western Guangdong were selected as the research objects to establish an evaluation index system of urban comprehensive carrying capacity,and its changing laws were analyzed.It was found that the comprehensive carrying capacities of cities in eastern and western Guangdong showed a trend of“first increasing and then decreasing”from 2015 to 2021,and reached the highest point in 2019,but there were significant differences among regions.From the perspective of spatial distribution,the comprehensive carrying capacities of cities in eastern and western Guangdong generally presented the law of high on both sides and low in the middle.In terms of the proportion of comprehensive carrying capacity of tourist cities,the larger part was always the carrying capacity of infrastructure and public services.The value of economic carrying capacity showed a trend of“first increasing and then decreasing”,while the value of environmental carrying capacity was always on the increase,and the value of tourism resources carrying capacity was basically stable.Finally,according to the analysis results,this paper put forward the optimization paths for comprehensive carrying capacities of tourist cities in eastern and western Guangdong from following four aspects:coordinating regional development,rationally utilizing natural resources,adjusting economic structure and adhering to the sustainable development concept.展开更多
With the rapid development of information technology,the combination of terminal technology,big data and mobile Internet and textbooks has become an irresistible trend in the modern education field.Under the context o...With the rapid development of information technology,the combination of terminal technology,big data and mobile Internet and textbooks has become an irresistible trend in the modern education field.Under the context of the Internet,carrying out education and teaching activities based on digital textbooks can give full play to the rich media,openness and interaction of digital textbooks,broaden students′horizon,enrich students′knowledge,and promote the improvement of students′ability and all-round development.However,in the specific teaching practice,there are also problems such as old compilation ideas,single compilation mode and low efficiency of personalized learning.Therefore,schools and teachers need to constantly innovate the presentation and arrangement of digital textbooks,strengthen technical support,deepen students′understanding of the teaching content of digital textbooks,promote the comprehensive development of students and improve the effectiveness of digital textbook teaching.展开更多
During the sintering process of iron ore,a large amount of nitrogen oxides is generated,for which there is currently no efficient and economical treatment process.Therefore,it is necessary to implement process control...During the sintering process of iron ore,a large amount of nitrogen oxides is generated,for which there is currently no efficient and economical treatment process.Therefore,it is necessary to implement process control in sintering production to keep the mass concentration of NO_(x)in sintering flue gas at a low level.Through industrial trials at sintering sites,methods such as correlation analysis,path analysis,and multiple linear regression were applied to analyze the influence of various factors on NO emissions during the sintering process.The results indicate that negative correlations exist between nitrogen monoxide(NO)emissions and negative pressure,permeability index,O_(2) concentration,CO concentration,and flue gas temperature.Conversely,positive correlations exist between NO emissions and dust concentration,water vapor volume fraction,and sintering bed speed.Among these factors,O_(2) concentration and dust concentration are identified as the most significant influencing factors on NO emissions.By analyzing the masses and modes of influence of different factors,the mechanisms of action of each factor were obtained.Specifically,O_(2) concentration,dust concentration,permeability index,CO concentration,and flue gas temperature play a direct dominant role in NO emissions during the sintering process,while water vapor volume fraction,sintering trolley speed,and negative pressure have an indirect effect.A predictive model for NO mass concentration in flue gas was established with an accuracy rate of 91.6%,showing consistent overall trends with actual values.Finally,denitrification strategies for sintering industrial production were proposed,along with prospects for preliminary denitrification of sintering flue gas using fluidized bed conditions in the duct.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.
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.
基金supported by Foundation of key Laboratory of AI and Information Processing of Education Department of Guangxi(No.2022GXZDSY002)(Hechi University),Foundation of Guangxi Key Laboratory of Automobile Components and Vehicle Technology(Nos.2022GKLACVTKF04,2023GKLACVTZZ06)。
文摘An improved RRT∗algorithm,referred to as the AGP-RRT∗algorithm,is proposed to address the problems of poor directionality,long generated paths,and slow convergence speed in multi-axis robotic arm path planning.First,an adaptive biased probabilistic sampling strategy is adopted to dynamically adjust the target deviation threshold and optimize the selection of random sampling points and the direction of generating new nodes in order to reduce the search space and improve the search efficiency.Second,a gravitationally adjustable step size strategy is used to guide the search process and dynamically adjust the step-size to accelerate the search speed of the algorithm.Finally,the planning path is processed by pruning,removing redundant points and path smoothing fitting using cubic B-spline curves to improve the flexibility of the robotic arm.Through the six-axis robotic arm path planning simulation experiments on the MATLAB platform,the results show that the AGP-RRT∗algorithm reduces 87.34%in terms of the average running time and 40.39%in terms of the average path cost;Meanwhile,under two sets of complex environments A and B,the average running time of the AGP-RRT∗algorithm is shortened by 94.56%vs.95.37%,and the average path cost is reduced by 55.28%vs.47.82%,which proves the effectiveness of the AGP-RRT∗algorithm in improving the efficiency of multi-axis robotic arm path planning.
基金supported in part by National Natural Science Foundation of China under Grants 62122069, 62071431, 62072490 and 62301490in part by Science and Technology Development Fund of Macao SAR, China under Grant 0158/2022/A+2 种基金in part by the Guangdong Basic and Applied Basic Research Foundation (2022A1515011287)in part by MYRG202000107-IOTSCin part by FDCT SKL-IOTSC (UM)-2021-2023
文摘With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery power.For this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this paper.Specifically,we use UAVs to assist the WSN in collecting data.In the current UAV-assisted WSN,the clustering and routing schemes are determined sequentially.However,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and routing.To efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing together.In the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing scheme.Therefore,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution faster.Unnecessary point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor nodes.To avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are indispensable.An emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of UAVs.Compared with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.
基金Sponsored by The Special Projects in Key Areas of General Colleges and Universities in Guangdong Province(2022ZDZX4057)Innovation Team Project of Colleges and Universities in Guangdong Province(2023WCXTD021)The Educational Science Planning Project of Guangdong Province(2022GXJK355).
文摘Seven tourist cities in eastern and western Guangdong were selected as the research objects to establish an evaluation index system of urban comprehensive carrying capacity,and its changing laws were analyzed.It was found that the comprehensive carrying capacities of cities in eastern and western Guangdong showed a trend of“first increasing and then decreasing”from 2015 to 2021,and reached the highest point in 2019,but there were significant differences among regions.From the perspective of spatial distribution,the comprehensive carrying capacities of cities in eastern and western Guangdong generally presented the law of high on both sides and low in the middle.In terms of the proportion of comprehensive carrying capacity of tourist cities,the larger part was always the carrying capacity of infrastructure and public services.The value of economic carrying capacity showed a trend of“first increasing and then decreasing”,while the value of environmental carrying capacity was always on the increase,and the value of tourism resources carrying capacity was basically stable.Finally,according to the analysis results,this paper put forward the optimization paths for comprehensive carrying capacities of tourist cities in eastern and western Guangdong from following four aspects:coordinating regional development,rationally utilizing natural resources,adjusting economic structure and adhering to the sustainable development concept.
基金supported by Second Batch of Curriculum Assessment Reform Pilot Project of Sanya University,(SYJGKH2023029)。
文摘With the rapid development of information technology,the combination of terminal technology,big data and mobile Internet and textbooks has become an irresistible trend in the modern education field.Under the context of the Internet,carrying out education and teaching activities based on digital textbooks can give full play to the rich media,openness and interaction of digital textbooks,broaden students′horizon,enrich students′knowledge,and promote the improvement of students′ability and all-round development.However,in the specific teaching practice,there are also problems such as old compilation ideas,single compilation mode and low efficiency of personalized learning.Therefore,schools and teachers need to constantly innovate the presentation and arrangement of digital textbooks,strengthen technical support,deepen students′understanding of the teaching content of digital textbooks,promote the comprehensive development of students and improve the effectiveness of digital textbook teaching.
基金supported by the National Natural Science Foundation of China(No.51974131)Hebei Outstanding Youth Fund Project(No.E2020209082),Tangshan Key R&D Program project(No.22150232J)Sixth Division Wujiaqu City Science and Technology Plan Project(2410).
文摘During the sintering process of iron ore,a large amount of nitrogen oxides is generated,for which there is currently no efficient and economical treatment process.Therefore,it is necessary to implement process control in sintering production to keep the mass concentration of NO_(x)in sintering flue gas at a low level.Through industrial trials at sintering sites,methods such as correlation analysis,path analysis,and multiple linear regression were applied to analyze the influence of various factors on NO emissions during the sintering process.The results indicate that negative correlations exist between nitrogen monoxide(NO)emissions and negative pressure,permeability index,O_(2) concentration,CO concentration,and flue gas temperature.Conversely,positive correlations exist between NO emissions and dust concentration,water vapor volume fraction,and sintering bed speed.Among these factors,O_(2) concentration and dust concentration are identified as the most significant influencing factors on NO emissions.By analyzing the masses and modes of influence of different factors,the mechanisms of action of each factor were obtained.Specifically,O_(2) concentration,dust concentration,permeability index,CO concentration,and flue gas temperature play a direct dominant role in NO emissions during the sintering process,while water vapor volume fraction,sintering trolley speed,and negative pressure have an indirect effect.A predictive model for NO mass concentration in flue gas was established with an accuracy rate of 91.6%,showing consistent overall trends with actual values.Finally,denitrification strategies for sintering industrial production were proposed,along with prospects for preliminary denitrification of sintering flue gas using fluidized bed conditions in the duct.
