The effects of micro-ridge-furrow planting(MR)on yield and the efficiency of light,water,and thermal resource use in rapeseed were tested in a three-year field experiment comparing MR to conventional flat planting.MR ...The effects of micro-ridge-furrow planting(MR)on yield and the efficiency of light,water,and thermal resource use in rapeseed were tested in a three-year field experiment comparing MR to conventional flat planting.MR enhanced canopy heterogeneity by altering the leaf angle between plants on ridges and furrows.The heterogeneous canopy environment increased intercepted photosynthetic active radiation,alleviated canopy temperature stress,and optimized canopy humidity,leading to improvements in light-nitrogen matching and net photosynthetic rate.Consequently,dry matter and yield increased by 13.0%and 11.0%,respectively,while radiation,thermal,and precipitation utilization efficiency increased by 12.3%-16.2%.The corresponding improvements in yield and resource use efficiency were attributed to a heterogeneous canopy environment that improved microclimatic conditions.展开更多
With the rapid advancement of satellite communication technologies,space information networks(SINs)have become essential infrastructure for complex service delivery and cross-domain task coordination,facilitating the ...With the rapid advancement of satellite communication technologies,space information networks(SINs)have become essential infrastructure for complex service delivery and cross-domain task coordination,facilitating the transition toward an intent-driven task-oriented coordination paradigm across the space,ground,and user segments.This study presents a novel intent-driven task-oriented network(IDTN)framework to address task scheduling and resource allocation challenges in SINs.The scheduling problem is formulated as a three-sided matching game that incorporates the preference attributes of entities across all network segments.To manage the variability of random task arrivals and dynamic resources,a context-aware linear upper-confidence-bound online learning mechanism is integrated to reduce decision-making uncertainty.Simulation results demonstrate the effectiveness of the proposed IDTN framework.Compared with conventional baseline methods,the framework achieves significant performance improvements,including a 4.4%-28.9%increase in average system reward,a 6.2%-34.5%improvement in resource utilization,and a 5.6%-35.7%enhancement in user satisfaction.The proposed framework is expected to facilitate the integration and orchestration of space-based platforms.展开更多
In strategic decision-making tasks,determining how to assign limited costly resource towards the defender and the attacker is a central problem.However,it is hard for pre-allocated resource assignment to adapt to dyna...In strategic decision-making tasks,determining how to assign limited costly resource towards the defender and the attacker is a central problem.However,it is hard for pre-allocated resource assignment to adapt to dynamic fighting scenarios,and exists situations where the scenario and rule of the Colonel Blotto(CB)game are too restrictive in real world.To address these issues,a support stage is added as supplementary for pre-allocated results,in which a novel two-stage competitive resource assignment problem is formulated based on CB game and stochastic Lanchester equation(SLE).Further,the force attrition in these two stages is formulated as a stochastic progress to consider the complex fighting progress,including the case that the player with fewer resources defeats the player with more resources and wins the battlefield.For solving this two-stage resource assignment problem,nested solving and no-regret learning are proposed to search the optimal resource assignment strategies.Numerical experiments are taken to analyze the effectiveness of the proposed model and study the assignment strategies in various cases.展开更多
With the development of satellite communication technology,the traditional resource allocation strategies are difficult to meet the requirements of resource utilization efficiency.In order to solve the optimization pr...With the development of satellite communication technology,the traditional resource allocation strategies are difficult to meet the requirements of resource utilization efficiency.In order to solve the optimization problem of resource allocation for multi-layer satellite networks in multi-user scenarios,we propose a new resource allocation scheme based on the many-to-many matching game.This scheme is different from the traditional resource allocation strategies that just consider a trade-off between the new call blocking probability and the handover call failure probability.Based on different preference lists among different layers of medium earth orbit(MEO) satellites,low earth orbit(LEO) satellites,base stations and users,we propose the corresponding algorithms from the perspective of quality of experience(QoE).The simulation results show that the many-to-many matching game scheme can effectively improve both the resource utilization efficiency and QoE,compared with the one-to-one and many-to-one matching algorithms.展开更多
With the rapid deployment of high speed railway(HSR) worldwide,both safety operation and comfort experience can be desired to evolve into a future era of intelligent transportation system.To eliminate boredom and prov...With the rapid deployment of high speed railway(HSR) worldwide,both safety operation and comfort experience can be desired to evolve into a future era of intelligent transportation system.To eliminate boredom and provide entertainment for passengers,an intranet for internal communications among passengers named as onboard social network system(SNS) is needed.In this paper,the latest progress in HSR network architectures and technology building blocks are discussed to enable the implementation of the SNS.Meanwhile,based on the device-to-device(D2 D) communication technology for proximal information interaction,SNS can be efficiently facilitated.A dynamic resource allocation algorithm is proposed to maximize the total utility of the onboard SNS,which is solved with the matching theory method.Simulation results verify the convergence and efficiency of the proposed algorithm.展开更多
National e-commerce demonstration city(NEDC)pilots play a crucial role in transforming urban e-commerce and significantly affect urban land resource carrying capacity(LRCC).Using panel data from prefecture-level citie...National e-commerce demonstration city(NEDC)pilots play a crucial role in transforming urban e-commerce and significantly affect urban land resource carrying capacity(LRCC).Using panel data from prefecture-level cities in China spanning 2006 to 2020,this study treats the NEDC pilot program as a quasi-natural experiment.A theoretical mechanism analysis was conducted to explore the implications of the NEDC pilot program on urban LRCC,and the propensity score matching double-difference method was used to estimate its effects.The findings show that the NEDC pilot program significantly inhibits the enhancement of urban LRCC,a conclusion that remains robust after multiple validity tests.Moreover,as the level of green development in urban land increases,the impact of the NEDC pilot program on urban LRCC shifts from positive to negative.This negative effect is especially pronounced in regions with lower levels of urban informatization,as well as in central and western areas and large cities.Furthermore,the mechanism analysis indicates that the NEDC pilot program exerts a significant negative influence on urban LRCC through three main channels:technological innovation,industrial structure,and economic correlation.展开更多
To satisfy different service requirements of multiple users in the orthogo nal frequency division multiple access wireless local area network OFDMA-WLAN system downlink transmission a resource allocation algorithm bas...To satisfy different service requirements of multiple users in the orthogo nal frequency division multiple access wireless local area network OFDMA-WLAN system downlink transmission a resource allocation algorithm based on fairness and quality of service QoS provisioning is proposed. Different QoS requirements are converted into different rate requirements to calculate the QoSs atisfaction level.The optimization object is revised as a fairness-driven resource optimization function to provide fairness. The complex resource allocation problem is divided into channel allocation and power assignment sub-problems. The sub-problems are solved by the bipartite graph matching and water-filling based method.Compared with other algorithms the proposed algorithm sacrifices less data rate for higher fairnes and QoS satisfaction.The sim ulation results show that the proposed algorithm is capableo fp rovi ding QoS and fairness and performs better in a tradeoff among QoS fairness and data rate.展开更多
Benefit from the enhanced onboard processing capacities and high-speed satellite-terrestrial links,satellite edge computing has been regarded as a promising technique to facilitate the execution of the computation-int...Benefit from the enhanced onboard processing capacities and high-speed satellite-terrestrial links,satellite edge computing has been regarded as a promising technique to facilitate the execution of the computation-intensive applications for satellite communication networks(SCNs).By deploying edge computing servers in satellite and gateway stations,SCNs can achieve significant performance gains of the computing capacities at the expense of extending the dimensions and complexity of resource management.Therefore,in this paper,we investigate the joint computing and communication resource management problem for SCNs to minimize the execution latency of the computation-intensive applications,while two different satellite edge computing scenarios and local execution are considered.Furthermore,the joint computing and communication resource allocation problem for the computation-intensive services is formulated as a mixed-integer programming problem.A game-theoretic and many-to-one matching theorybased scheme(JCCRA-GM)is proposed to achieve an approximate optimal solution.Numerical results show that the proposed method with low complexity can achieve almost the same weight-sum latency as the Brute-force method.展开更多
A joint resource allocation algorithm based on parallel auction(JRAPA)is proposed for mobile edge computing(MEC).In JRAPA,the joint allocation of wireless and cloud resources is modeled as an auction process,aiming at...A joint resource allocation algorithm based on parallel auction(JRAPA)is proposed for mobile edge computing(MEC).In JRAPA,the joint allocation of wireless and cloud resources is modeled as an auction process,aiming at maximizing the utilities of service providers(SPs)and satisfying the delay requirements of mobile terminals(MTs).The auction process consists of the bidding submission,winner determination and pricing stages.At the bidding submission stage,the MTs take available resources from SPs and distance factors into account to decide the bidding priority,thereby reducing the processing delay and improving the successful trades rate.A resource constrained utility ranking(RCUR)algorithm is put forward at the winner determination stage to determine the winners and losers so as to maximize the utilities of SPs.At the pricing stage,the sealed second-price rule is adopted to ensure the independence between the price paid by the buyer and its own bid.The simulation results show that the proposed JRAPA algorithm outperforms other existing algorithms in terms of the convergence rate and the number of successful trades rate.Moreover,it can not only achieve a larger average utility of SPs but also significantly reduce the average delay of MTs.展开更多
In order to lower the power consumption and improve the coefficient of resource utilization of current cloud computing systems, this paper proposes two resource pre-allocation algorithms based on the ＂shut down the r...In order to lower the power consumption and improve the coefficient of resource utilization of current cloud computing systems, this paper proposes two resource pre-allocation algorithms based on the ＂shut down the redundant, turn on the demanded＂ strategy here. Firstly, a green cloud computing model is presented, abstracting the task scheduling problem to the virtual machine deployment issue with the virtualization technology. Secondly, the future workloads of system need to be predicted： a cubic exponential smoothing algorithm based on the conservative control（CESCC） strategy is proposed, combining with the current state and resource distribution of system, in order to calculate the demand of resources for the next period of task requests. Then, a multi-objective constrained optimization model of power consumption and a low-energy resource allocation algorithm based on probabilistic matching（RA-PM） are proposed. In order to reduce the power consumption further, the resource allocation algorithm based on the improved simulated annealing（RA-ISA） is designed with the improved simulated annealing algorithm. Experimental results show that the prediction and conservative control strategy make resource pre-allocation catch up with demands, and improve the efficiency of real-time response and the stability of the system. Both RA-PM and RA-ISA can activate fewer hosts, achieve better load balance among the set of high applicable hosts, maximize the utilization of resources, and greatly reduce the power consumption of cloud computing systems.展开更多
深入解析资源型城市生态系统服务供需关系、识别生态管理分区对优化资源型城市生态修复策略、完善国土空间规划体系以及促进资源高效配置具有重要意义。采用生态系统服务和权衡综合评估(Integrated Valuation of Ecosystem Services and...深入解析资源型城市生态系统服务供需关系、识别生态管理分区对优化资源型城市生态修复策略、完善国土空间规划体系以及促进资源高效配置具有重要意义。采用生态系统服务和权衡综合评估(Integrated Valuation of Ecosystem Services and Tradeoffs,InVEST)仿真模型、皮尔逊系数及四象限模型,揭示安徽省资源型城市水源涵养(WC)、固碳(CS)及粮食(FP)生态系统服务供需的时空变化、权衡协同关系及空间匹配模式,并据此构建生态管理分区框架。结果显示:(1)在2011—2023年,安徽省资源型城市生态系统服务中WC的供给和供需指数均呈上升趋势,需求呈下降趋势;CS的供给和供需指数均呈下降趋势,需求呈上升趋势;FP的供给、需求和供需指数均呈上升趋势;在空间分异上,WC供需指数呈现南高北低梯度格局,CS供需指数空间分布较为均衡,FP供需指数呈现南低北高格局。(2)就供需指数而言,WC生态系统服务与CS为协同关系,FP与WC、CS均为权衡关系。WC、CS及FP均以低-低空间匹配模式为主。(3)粮食生产区为主要功能区,养护为主要管理策略,重点保护为主要管控等级,粮食重点养护区为生态管理分区主要结果。研究可为缓解资源型城市“生态-生产”矛盾、优化国土空间保护格局及促进生态资产价值转化提供决策参考依据。展开更多
Cloud manufacturing(CMfg),combining the idea and technologies of cloud computing and Internet of Things,is an emerging service-oriented manufacturing model.The supply–demand matching of manufacturing resources is on...Cloud manufacturing(CMfg),combining the idea and technologies of cloud computing and Internet of Things,is an emerging service-oriented manufacturing model.The supply–demand matching of manufacturing resources is one of the key technologies for implemention.However,resources in CMfg system are geographically distributed,functional of similar and dynamically changeable,and these features make it difficult to obtain higher accuracy for existing matching methods.In order to select the most satisfied resources in CMfg,a semantics-based supply–demand classification matching method(SDCM)is proposed.Firstly,the implementing framework of SDCM is constructed.Then,combined with the theories of ontology and dynamic description logic,a semantics-based SDCM algorithm is designed,which includes four implementation stages,respectively,basic information matching,IOPE parameters(Input,Outputs,Preconditions,Effects)matching,QoS(Quality of Service)matching and comprehensive matching.Finally,a case verifies the feasibility and effectiveness of the proposed method.展开更多
The optimal planning and operation of multi-type flexible resources(FRs)are critical prerequisites for maintaining power and energy balance in regional power grids with a high proportion of clean energy.However,insuff...The optimal planning and operation of multi-type flexible resources(FRs)are critical prerequisites for maintaining power and energy balance in regional power grids with a high proportion of clean energy.However,insufficient consideration of the multi-dimensional and heterogeneous features of FRs,such as the regulation characteristics of diversified battery energy storage systems(BESSs),poses a challenge in economically relieving imbalance power and adequately sharing feature information between power supply and demand.In view of this disadvantage,an optimal planning and operation method based on differentiated feature matching through response capability characterization and difference quantification of FRs is proposed in this paper.In the planning stage,a model for the optimal planning of diversified energy storages(ESs)including Lithium-ion battery(Li-B),supercapacitor energy storage(SCES),compressed air energy storage(CAES),and pumped hydroelectric storage(PHS)is established.Subsequently,in the operating stage,the potential,direction,and cost of FR response behaviors are refined to match with the power and energy balance demand(PEBD)of power grid operation.An optimal operating algorithm is then employed to quantify the feature differences and output response sequences of multi-type FRs.The performance and effectiveness of the proposed method are demonstrated through comparative studies conducted on an actual regional power grid in northwest China.Analysis and simulation results illustrate that the proposed method can effectively highlight the advantages of BESSs compared with other ESs,and economically reduce imbalance power of the regional power grid under practical operating conditions.展开更多
基金supported by the National Key Research and Development Program of China (2021YFD1901200)the Key Research and Development Program of Hubei Province of China (2023BBB028)+1 种基金the Earmarked Fund of Hubei province of Chinathe Fundamental Research Funds for the Central Universities (2662024ZKQD005)
文摘The effects of micro-ridge-furrow planting(MR)on yield and the efficiency of light,water,and thermal resource use in rapeseed were tested in a three-year field experiment comparing MR to conventional flat planting.MR enhanced canopy heterogeneity by altering the leaf angle between plants on ridges and furrows.The heterogeneous canopy environment increased intercepted photosynthetic active radiation,alleviated canopy temperature stress,and optimized canopy humidity,leading to improvements in light-nitrogen matching and net photosynthetic rate.Consequently,dry matter and yield increased by 13.0%and 11.0%,respectively,while radiation,thermal,and precipitation utilization efficiency increased by 12.3%-16.2%.The corresponding improvements in yield and resource use efficiency were attributed to a heterogeneous canopy environment that improved microclimatic conditions.
基金supported by the National Key Research and Development Program of China(2020YFB1807700)Innovation Capability Support Program of Shaanxi(2024RS-CXTD-01).
文摘With the rapid advancement of satellite communication technologies,space information networks(SINs)have become essential infrastructure for complex service delivery and cross-domain task coordination,facilitating the transition toward an intent-driven task-oriented coordination paradigm across the space,ground,and user segments.This study presents a novel intent-driven task-oriented network(IDTN)framework to address task scheduling and resource allocation challenges in SINs.The scheduling problem is formulated as a three-sided matching game that incorporates the preference attributes of entities across all network segments.To manage the variability of random task arrivals and dynamic resources,a context-aware linear upper-confidence-bound online learning mechanism is integrated to reduce decision-making uncertainty.Simulation results demonstrate the effectiveness of the proposed IDTN framework.Compared with conventional baseline methods,the framework achieves significant performance improvements,including a 4.4%-28.9%increase in average system reward,a 6.2%-34.5%improvement in resource utilization,and a 5.6%-35.7%enhancement in user satisfaction.The proposed framework is expected to facilitate the integration and orchestration of space-based platforms.
基金supported by the National Natural Science Foundation of China(61702528,61806212,62173336)。
文摘In strategic decision-making tasks,determining how to assign limited costly resource towards the defender and the attacker is a central problem.However,it is hard for pre-allocated resource assignment to adapt to dynamic fighting scenarios,and exists situations where the scenario and rule of the Colonel Blotto(CB)game are too restrictive in real world.To address these issues,a support stage is added as supplementary for pre-allocated results,in which a novel two-stage competitive resource assignment problem is formulated based on CB game and stochastic Lanchester equation(SLE).Further,the force attrition in these two stages is formulated as a stochastic progress to consider the complex fighting progress,including the case that the player with fewer resources defeats the player with more resources and wins the battlefield.For solving this two-stage resource assignment problem,nested solving and no-regret learning are proposed to search the optimal resource assignment strategies.Numerical experiments are taken to analyze the effectiveness of the proposed model and study the assignment strategies in various cases.
基金National Natural Science Foundation of China under Grant No.61871422.
文摘With the development of satellite communication technology,the traditional resource allocation strategies are difficult to meet the requirements of resource utilization efficiency.In order to solve the optimization problem of resource allocation for multi-layer satellite networks in multi-user scenarios,we propose a new resource allocation scheme based on the many-to-many matching game.This scheme is different from the traditional resource allocation strategies that just consider a trade-off between the new call blocking probability and the handover call failure probability.Based on different preference lists among different layers of medium earth orbit(MEO) satellites,low earth orbit(LEO) satellites,base stations and users,we propose the corresponding algorithms from the perspective of quality of experience(QoE).The simulation results show that the many-to-many matching game scheme can effectively improve both the resource utilization efficiency and QoE,compared with the one-to-one and many-to-one matching algorithms.
基金supported by the National Key Research and Development Program Under Grant 2016YFB 1200102-04Natural Science Foundation of China under Grant U1334202+3 种基金supported in part by the National S&T Major Project 2016ZX03001021-003the Fundamental Research Funds for the Central Universities under Grant 2016RC056in part by the State Key Laboratory of Rail Traffic Control and Safety,Beijing Jiaotong University,under Contract RCS2017ZT009in part by the China Postdoctoral Science Foundation under Grant 2017M610040
文摘With the rapid deployment of high speed railway(HSR) worldwide,both safety operation and comfort experience can be desired to evolve into a future era of intelligent transportation system.To eliminate boredom and provide entertainment for passengers,an intranet for internal communications among passengers named as onboard social network system(SNS) is needed.In this paper,the latest progress in HSR network architectures and technology building blocks are discussed to enable the implementation of the SNS.Meanwhile,based on the device-to-device(D2 D) communication technology for proximal information interaction,SNS can be efficiently facilitated.A dynamic resource allocation algorithm is proposed to maximize the total utility of the onboard SNS,which is solved with the matching theory method.Simulation results verify the convergence and efficiency of the proposed algorithm.
基金funded by the National Social Science Foundation of China(later funded)[Grant No.23FJYA005].
文摘National e-commerce demonstration city(NEDC)pilots play a crucial role in transforming urban e-commerce and significantly affect urban land resource carrying capacity(LRCC).Using panel data from prefecture-level cities in China spanning 2006 to 2020,this study treats the NEDC pilot program as a quasi-natural experiment.A theoretical mechanism analysis was conducted to explore the implications of the NEDC pilot program on urban LRCC,and the propensity score matching double-difference method was used to estimate its effects.The findings show that the NEDC pilot program significantly inhibits the enhancement of urban LRCC,a conclusion that remains robust after multiple validity tests.Moreover,as the level of green development in urban land increases,the impact of the NEDC pilot program on urban LRCC shifts from positive to negative.This negative effect is especially pronounced in regions with lower levels of urban informatization,as well as in central and western areas and large cities.Furthermore,the mechanism analysis indicates that the NEDC pilot program exerts a significant negative influence on urban LRCC through three main channels:technological innovation,industrial structure,and economic correlation.
基金The National Science and Technology Major Project(No.2012ZX03004005-003)the National Natural Science Foundationof China(No.61171081,61201175)the Science and Technology Support Program of Jiangsu Province(No.BE2011187)
文摘To satisfy different service requirements of multiple users in the orthogo nal frequency division multiple access wireless local area network OFDMA-WLAN system downlink transmission a resource allocation algorithm based on fairness and quality of service QoS provisioning is proposed. Different QoS requirements are converted into different rate requirements to calculate the QoSs atisfaction level.The optimization object is revised as a fairness-driven resource optimization function to provide fairness. The complex resource allocation problem is divided into channel allocation and power assignment sub-problems. The sub-problems are solved by the bipartite graph matching and water-filling based method.Compared with other algorithms the proposed algorithm sacrifices less data rate for higher fairnes and QoS satisfaction.The sim ulation results show that the proposed algorithm is capableo fp rovi ding QoS and fairness and performs better in a tradeoff among QoS fairness and data rate.
基金This work was supported by the National Natural Science Foundation of China(Grants 61971054 and 61601045)Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory Foundation(HHX21641X002 and HHX20641X003).
文摘Benefit from the enhanced onboard processing capacities and high-speed satellite-terrestrial links,satellite edge computing has been regarded as a promising technique to facilitate the execution of the computation-intensive applications for satellite communication networks(SCNs).By deploying edge computing servers in satellite and gateway stations,SCNs can achieve significant performance gains of the computing capacities at the expense of extending the dimensions and complexity of resource management.Therefore,in this paper,we investigate the joint computing and communication resource management problem for SCNs to minimize the execution latency of the computation-intensive applications,while two different satellite edge computing scenarios and local execution are considered.Furthermore,the joint computing and communication resource allocation problem for the computation-intensive services is formulated as a mixed-integer programming problem.A game-theoretic and many-to-one matching theorybased scheme(JCCRA-GM)is proposed to achieve an approximate optimal solution.Numerical results show that the proposed method with low complexity can achieve almost the same weight-sum latency as the Brute-force method.
基金The National Natural Science Foundation of China(No.61741102,61471164,61601122)
文摘A joint resource allocation algorithm based on parallel auction(JRAPA)is proposed for mobile edge computing(MEC).In JRAPA,the joint allocation of wireless and cloud resources is modeled as an auction process,aiming at maximizing the utilities of service providers(SPs)and satisfying the delay requirements of mobile terminals(MTs).The auction process consists of the bidding submission,winner determination and pricing stages.At the bidding submission stage,the MTs take available resources from SPs and distance factors into account to decide the bidding priority,thereby reducing the processing delay and improving the successful trades rate.A resource constrained utility ranking(RCUR)algorithm is put forward at the winner determination stage to determine the winners and losers so as to maximize the utilities of SPs.At the pricing stage,the sealed second-price rule is adopted to ensure the independence between the price paid by the buyer and its own bid.The simulation results show that the proposed JRAPA algorithm outperforms other existing algorithms in terms of the convergence rate and the number of successful trades rate.Moreover,it can not only achieve a larger average utility of SPs but also significantly reduce the average delay of MTs.
基金supported by the National Natural Science Foundation of China(6147219261202004)+1 种基金the Special Fund for Fast Sharing of Science Paper in Net Era by CSTD(2013116)the Natural Science Fund of Higher Education of Jiangsu Province(14KJB520014)
文摘In order to lower the power consumption and improve the coefficient of resource utilization of current cloud computing systems, this paper proposes two resource pre-allocation algorithms based on the ＂shut down the redundant, turn on the demanded＂ strategy here. Firstly, a green cloud computing model is presented, abstracting the task scheduling problem to the virtual machine deployment issue with the virtualization technology. Secondly, the future workloads of system need to be predicted： a cubic exponential smoothing algorithm based on the conservative control（CESCC） strategy is proposed, combining with the current state and resource distribution of system, in order to calculate the demand of resources for the next period of task requests. Then, a multi-objective constrained optimization model of power consumption and a low-energy resource allocation algorithm based on probabilistic matching（RA-PM） are proposed. In order to reduce the power consumption further, the resource allocation algorithm based on the improved simulated annealing（RA-ISA） is designed with the improved simulated annealing algorithm. Experimental results show that the prediction and conservative control strategy make resource pre-allocation catch up with demands, and improve the efficiency of real-time response and the stability of the system. Both RA-PM and RA-ISA can activate fewer hosts, achieve better load balance among the set of high applicable hosts, maximize the utilization of resources, and greatly reduce the power consumption of cloud computing systems.
文摘深入解析资源型城市生态系统服务供需关系、识别生态管理分区对优化资源型城市生态修复策略、完善国土空间规划体系以及促进资源高效配置具有重要意义。采用生态系统服务和权衡综合评估(Integrated Valuation of Ecosystem Services and Tradeoffs,InVEST)仿真模型、皮尔逊系数及四象限模型,揭示安徽省资源型城市水源涵养(WC)、固碳(CS)及粮食(FP)生态系统服务供需的时空变化、权衡协同关系及空间匹配模式,并据此构建生态管理分区框架。结果显示:(1)在2011—2023年,安徽省资源型城市生态系统服务中WC的供给和供需指数均呈上升趋势,需求呈下降趋势;CS的供给和供需指数均呈下降趋势,需求呈上升趋势;FP的供给、需求和供需指数均呈上升趋势;在空间分异上,WC供需指数呈现南高北低梯度格局,CS供需指数空间分布较为均衡,FP供需指数呈现南低北高格局。(2)就供需指数而言,WC生态系统服务与CS为协同关系,FP与WC、CS均为权衡关系。WC、CS及FP均以低-低空间匹配模式为主。(3)粮食生产区为主要功能区,养护为主要管理策略,重点保护为主要管控等级,粮食重点养护区为生态管理分区主要结果。研究可为缓解资源型城市“生态-生产”矛盾、优化国土空间保护格局及促进生态资产价值转化提供决策参考依据。
基金the National High-Tech.R&D Program of China(No.2015AA043801)the Science and Technology Program of Guangdong Province(No.2015A010103022)Post-Doctoral Funding Project of Chongqing(No.Xm2016008).
文摘Cloud manufacturing(CMfg),combining the idea and technologies of cloud computing and Internet of Things,is an emerging service-oriented manufacturing model.The supply–demand matching of manufacturing resources is one of the key technologies for implemention.However,resources in CMfg system are geographically distributed,functional of similar and dynamically changeable,and these features make it difficult to obtain higher accuracy for existing matching methods.In order to select the most satisfied resources in CMfg,a semantics-based supply–demand classification matching method(SDCM)is proposed.Firstly,the implementing framework of SDCM is constructed.Then,combined with the theories of ontology and dynamic description logic,a semantics-based SDCM algorithm is designed,which includes four implementation stages,respectively,basic information matching,IOPE parameters(Input,Outputs,Preconditions,Effects)matching,QoS(Quality of Service)matching and comprehensive matching.Finally,a case verifies the feasibility and effectiveness of the proposed method.
基金This work was supported by the Science and Technology Major Project of Tibetan Autonomous Region of China(No.XZ202201ZD0003G).
文摘The optimal planning and operation of multi-type flexible resources(FRs)are critical prerequisites for maintaining power and energy balance in regional power grids with a high proportion of clean energy.However,insufficient consideration of the multi-dimensional and heterogeneous features of FRs,such as the regulation characteristics of diversified battery energy storage systems(BESSs),poses a challenge in economically relieving imbalance power and adequately sharing feature information between power supply and demand.In view of this disadvantage,an optimal planning and operation method based on differentiated feature matching through response capability characterization and difference quantification of FRs is proposed in this paper.In the planning stage,a model for the optimal planning of diversified energy storages(ESs)including Lithium-ion battery(Li-B),supercapacitor energy storage(SCES),compressed air energy storage(CAES),and pumped hydroelectric storage(PHS)is established.Subsequently,in the operating stage,the potential,direction,and cost of FR response behaviors are refined to match with the power and energy balance demand(PEBD)of power grid operation.An optimal operating algorithm is then employed to quantify the feature differences and output response sequences of multi-type FRs.The performance and effectiveness of the proposed method are demonstrated through comparative studies conducted on an actual regional power grid in northwest China.Analysis and simulation results illustrate that the proposed method can effectively highlight the advantages of BESSs compared with other ESs,and economically reduce imbalance power of the regional power grid under practical operating conditions.
