Companies are eager to have a smart supply chain especially when they have adynamic system.Industry 4.0 is a concept which concentrates on mobility andreal-time integration.Thus,it can be considered as a necessary com...Companies are eager to have a smart supply chain especially when they have adynamic system.Industry 4.0 is a concept which concentrates on mobility andreal-time integration.Thus,it can be considered as a necessary component thathas to be implemented for a dynamic vehicle routing problem.The aim of thisresearch is to solve large-scale DVRP(LSDVRP)in which the delivery vehiclesmust serve customer demands from a common depot to minimize transit costswhile not exceeding the capacity constraint of each vehicle.In LSDVRP,it isdifficult to get an exact solution and the computational time complexity growsexponentially.To find near-optimal answers for this problem,a hierarchicalapproach consisting of three stages:“clustering,route-construction,routeimprovement”is proposed.The major contribution of this paper is dealing withLSDVRP to propose the three-stage algorithm with better results.The resultsconfirmed that the proposed methodology is applicable.展开更多
BACKGROUND Patients with gastric cancer often experience slow postoperative recovery and psychological stress,necessitating enhanced nursing care to improve their prognosis.AIM To analyze the impact of a timing-theory...BACKGROUND Patients with gastric cancer often experience slow postoperative recovery and psychological stress,necessitating enhanced nursing care to improve their prognosis.AIM To analyze the impact of a timing-theory-guided three-stage integrated nursing intervention(TSIN)on the postoperative recovery of patients undergoing gastric cancer surgery.METHODS Total 84 patients that underwent gastric cancer surgeries between June 2022 and June 2024 were selected and divided into a control group and an observation group based on perioperative nursing methods.The control group(n=42)received routine nursing care,whereas the observation group(n=42)received a timing-theory-guided TSIN.The psychological adjustment capabilities,psychological stress,cancer-related fatigue levels,postoperative recovery,and quality of life of the two groups were compared.RESULTS Compared to the control group,the observation group took lesser time to get out of bed,achieve gastrointestinal motility,have the first mealtime,along with a shorter hospital stay(P<0.05).Before nursing,there were no significant differences between groups’parameters or scores(P>0.05).After nursing,the scores for psychological stress and cancer-related fatigue decreased.In contrast,the scores for psychological adjustment capabilities and quality of life increased,with more significant improvements observed in the observation group,showing significant differences within and between the groups(P<0.05).CONCLUSION Timing theory-guided TSIN can improve the psychological adjustment capabilities of patients undergoing gastric cancer surgery,reduce psychological stress and cancer-related fatigue,accelerate postoperative recovery,and improve the quality of life.展开更多
The latent heat thermal energy storage system with solid-liquid phase-change material(SLPCM-LHTES)as energy storage medium provides outstanding advantages such as system simplicity,stable temperature control,and high ...The latent heat thermal energy storage system with solid-liquid phase-change material(SLPCM-LHTES)as energy storage medium provides outstanding advantages such as system simplicity,stable temperature control,and high energy storage density,showing great potential toward addressing the energy storage problems associated with decentralized,intermittent,and unstable renewable energy sources.Notably,effective heat transfer within the SLPCM-LHTES is crucial for extending its application potential.Therefore,a comprehensive understanding of the heat transfer processes in SLPCM-LHTES from a theoretical perspective is necessary.In this review,we propose a three-stage heat transfer pathway in SLPCM-LHTES,including external heating,interfacial heat transfer,and intrinsic phase transition processes.From the perspective of this three-stage pathway,the theoretical basis of heat transfer processes and typical efficiency enhancement strategies in SLPCM-LHTES are summarized.Moreover,an overview of the typical applications of SLPCM-LHTES in various fields,such as building energy efficiency,textiles and garments,and battery thermal management,is presented.Finally,the remaining challenges and possible avenues of research in this burgeoning field will also be discussed.展开更多
This paper introduces a practical solving scheme of gradetransition trajectory optimization(GTTO) problems under typical certificate-checking–updating framework. Due to complicated kinetics of polymerization,differen...This paper introduces a practical solving scheme of gradetransition trajectory optimization(GTTO) problems under typical certificate-checking–updating framework. Due to complicated kinetics of polymerization,differential/algebraic equations(DAEs) always cause great computational burden and system non-linearity usually makes GTTO non-convex bearing multiple optima. Therefore, coupled with the three-stage decomposition model, a three-section algorithm of dynamic programming(TSDP) is proposed based on the general iteration mechanism of iterative programming(IDP) and incorporated with adaptivegrid allocation scheme and heuristic modifications. The algorithm iteratively performs dynamic programming with heuristic modifications under constant calculation loads and adaptively allocates the valued computational resources to the regions that can further improve the optimality under the guidance of local error estimates. TSDP is finally compared with IDP and interior point method(IP) to verify its efficiency of computation.展开更多
Current MSM switching fabric has poor performance under unbalanced traffic. This paper presents an alternative, novel Central-stage Buffered Three-stage Clos switching (CB-3Clos) fabric and proves that this fabric can...Current MSM switching fabric has poor performance under unbalanced traffic. This paper presents an alternative, novel Central-stage Buffered Three-stage Clos switching (CB-3Clos) fabric and proves that this fabric can emulate output queuing switch without any speedup. By analyzing the condition to satisfy the central-stage load-balance, this paper also proposes a Central-stage Load-balanced-based Distributed Scheduling algorithm (CLDS) for CB-3Clos. The results show that, compared with Concurrent Round-Robin based Dispatching (CRRD) algorithm based on MSM, CLDS algorithm has high throughput irrespective with the traffic model and better performance in mean packet delay.展开更多
The flexible job shop scheduling problem(FJSP)is commonly encountered in practical manufacturing environments.A product is typically built by assembling multiple jobs during actual manufacturing.AGVs are normally used...The flexible job shop scheduling problem(FJSP)is commonly encountered in practical manufacturing environments.A product is typically built by assembling multiple jobs during actual manufacturing.AGVs are normally used to transport the jobs from the processing shop to the assembly shop,where they are assembled.Therefore,studying the integrated scheduling problem with its processing,transportation,and assembly stages is extremely beneficial and significant.This research studies the three-stage flexible job shop scheduling problem with assembly and AGV transportation(FJSP-T-A),which includes processing jobs,transporting them via AGVs,and assembling them.A mixed integer linear programming(MILP)model is established to obtain optimal solutions.As the MILP model is challenging for solving large-scale problems,a novel co-evolutionary algorithm(NCEA)with two different decoding methods is proposed.In NCEA,a restart operation is developed to improve the diversity of the population,and a multiple crossover strategy is designed to improve the quality of individuals.The validity of the MILP model is proven by analyzing its complexity.The effectiveness of the restart operator,multiple crossovers,and the proposed algorithm is demonstrated by calculating and analyzing the RPI values of each algorithm's results within the time limit and performing a paired t-test on the average values of each algorithm at the 95%confidence level.This paper studies FJSP-T-A by minimizing the makespan for the first time,and presents a MILP model and an NCEA with two different decoding methods.展开更多
Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting...Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.展开更多
This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the compl...This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.展开更多
Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from...Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.展开更多
Based on a typical prototype of a soil slope in engineering practice, a numerical model of a three-stage soil slope supported by the anchor frame structure was established by means of FLAC3D code. The dynamic response...Based on a typical prototype of a soil slope in engineering practice, a numerical model of a three-stage soil slope supported by the anchor frame structure was established by means of FLAC3D code. The dynamic responses of three-stage soil slope and frame structure were studied by performing a series of bidirectional Wenchuan motions in terms of the failure mode of three-stage structure, the acceleration of soil slope, the displacement of frame structure, and the anchor stress of frame structure. The response accelerations in both horizontal and vertical directions are the most largely amplified at the slope top of each stage subjected to different shaking cases. The platforms among the stages reduce the amplification effect of response acceleration. The residual displacement of frame structure increases significantly as the intensity of shaking case increases. The frame structure at each stage presents a combined displacement mode consisting of a translation and a rotation around the vertex. The anchor stress of frame structure is mainly increased by the first intense pulse of Wenchuan seismic wave, and it is sensitive to the intensity of shaking case. The anchor stress of frame structure at the first stage is the most considerably enlarged by earthquake loading.展开更多
Based on three-stage data envelopment analysis(DEA) model estimates of resource utilization efficiency of coal,we selected 29 provinces from China's 2012 input-output data and used the bootstrap DEA model to corre...Based on three-stage data envelopment analysis(DEA) model estimates of resource utilization efficiency of coal,we selected 29 provinces from China's 2012 input-output data and used the bootstrap DEA model to correct the bias.The results show that the mean overall technical efficiency,pure technical efficiency,and scale efficiency was 0.833,0.998,and 0.711 in 2012,respectively.Moreover,the comprehensive technical efficiency score indicates that the scale is invalid.Area utilization efficiencies for the eastern,central,and western regions were 0.917,0.731,and 0.629,respectively.The results prove that there are significant differences in the distribution of coal resources utilization efficiency across regions.展开更多
Two-oriented agriculture was a complex organism coupling production,economics,society and ecology.Its development process was affected by various factors such as producers,nature,society,etc.In order to overcome measu...Two-oriented agriculture was a complex organism coupling production,economics,society and ecology.Its development process was affected by various factors such as producers,nature,society,etc.In order to overcome measurement error of traditional data envelopment analysis caused by ignoring random,three-stage DEA model was studied to remove environmental factors and random effects.On the foundation of this model was two-oriented agriculture comprehensive production efficiency of 14 cities were estimated in Hunan Province in 2008,and brown forth corresponding policy proposals to promote agricultural development.展开更多
From the perspective of agricultural insurance agency,this paper focuses on the study of operational efficiency of agricultural insurance agency,and analyzes the operational efficiency of agricultural insurance agency...From the perspective of agricultural insurance agency,this paper focuses on the study of operational efficiency of agricultural insurance agency,and analyzes the operational efficiency of agricultural insurance agency and its influencing factors,in order to improve the operational efficiency of agricultural insurance agency,better supply agricultural insurance and achieve the policy effect of agricultural insurance.The results of this paper are as follows:( i) Either comprehensive operational efficiency or scale efficiency of Chinese-funded agency is higher than that of foreign-funded agency,but its pure technical efficiency is lower than that of foreign-funded agency,indicating that the managerial decision ability of Chinese-funded agency is weaker than that of foreign-funded agency,and needs to be improved;( ii) The operational efficiency of professional agricultural insurance agency is higher than that of comprehensive agricultural insurance agency,and the agricultural insurance agency is greatly affected by environmental factors;( iii) The operating time of agricultural insurance agency is proportional to its operational efficiency;( iv) The quality of employees is positively correlated with the capital and cost input difference,but negatively correlated with the difference in the number of employees. Therefore,it is necessary to pay attention to the improvement of employees' working efficiency while laying emphasis on employees' quality.展开更多
The use of an electrical network as close as possible to its limits can lead to its instability in the event of a high amplitude disturbance. The damping of system oscillations can be achieved by conventional means of...The use of an electrical network as close as possible to its limits can lead to its instability in the event of a high amplitude disturbance. The damping of system oscillations can be achieved by conventional means of voltage and speed regulation but also by FACTS (Flexible AC Transmission Systems) devices, which are increasingly used in power networks. In this work, optimal control coordination between a hybrid power flow controller and a three-level inverter was used to improve the transient stability of a transmission line. The UPFC is a combination of a serial compensator (SSSC) and a parallel compensator (STATCOM) both connected to a DC-LINK DC bus. The SSSC acts as a voltage source for the network and injects a voltage that can be adjusted in phase and amplitude in addition to the network voltage;the STATCOM acts as a current source. The approach used is tested in the Matlab Simulink environment on a single machine network. Optimal controller tuning gives a better transient stability improvement by reducing the transport angle oscillations from 248.17% to 9.85%.展开更多
In order to improve the dynamic response bandwidth of three-stage electro-hydraulic servo valve,a new method,speed-feedback control is presented in this paper.The construction and principle of three-stage electro-hydr...In order to improve the dynamic response bandwidth of three-stage electro-hydraulic servo valve,a new method,speed-feedback control is presented in this paper.The construction and principle of three-stage electro-hydraulic servo valve are explained,and the mathematical model of three-stage electro-hydraulic servo valve is built in frequency domain.Experimental and simulation results show that the bandwidth compared with proportional control is improved under speed-feedback control.Moreover,the research results play an important role in developing high performance three-stage electro-hydraulic servo valve.展开更多
Numerical simulation of enhanced fluid flow characteristics in a three-stage double-stirring extraction tank was conducted with the coupling of an Eulerian multiphase flow model and a Morsi-Alexander interphase drag f...Numerical simulation of enhanced fluid flow characteristics in a three-stage double-stirring extraction tank was conducted with the coupling of an Eulerian multiphase flow model and a Morsi-Alexander interphase drag force model. Results show that the addition of a stirring device into the settler can efficiently reduce the volume fraction of out-of-phase impurity in the outlet, and accelerate the settling separation of oil-water mixture. Such addition can also effectively break down the oil-water-wrapped liquid droplets coming from the mixer, inhibit reflux from the outlet, and improve the oil-water separation. The addition of a stirring device induces ignorable power consumption compared with that by the mixer, and can thus facilitate the commercialized promotion of this novel equipment.展开更多
Objective Rapakivi granites,characterized by rapakivi texture,Atype granite feature and an anorogenic setting,commonly occur in the Proterozoic of the Northern Hemisphere（Fig.la）.Recently,more and more Phanerozoic r...Objective Rapakivi granites,characterized by rapakivi texture,Atype granite feature and an anorogenic setting,commonly occur in the Proterozoic of the Northern Hemisphere（Fig.la）.Recently,more and more Phanerozoic rapakivi granite suites have been identified and some even occur in orogenic belts.Significantly,three-stage,Proterozoic.展开更多
Software defect prediction is a research hotspot in the field of software engineering.However,due to the limitations of current machine learning algorithms,we can’t achieve good effect for defect prediction by only u...Software defect prediction is a research hotspot in the field of software engineering.However,due to the limitations of current machine learning algorithms,we can’t achieve good effect for defect prediction by only using machine learning algorithms.In previous studies,some researchers used extreme learning machine(ELM)to conduct defect prediction.However,the initial weights and biases of the ELM are determined randomly,which reduces the prediction performance of ELM.Motivated by the idea of search based software engineering,we propose a novel software defect prediction model named KAEA based on kernel principal component analysis(KPCA),adaptive genetic algorithm,extreme learning machine and Adaboost algorithm,which has three main advantages:(1)KPCA can extract optimal representative features by leveraging a nonlinear mapping function;(2)We leverage adaptive genetic algorithm to optimize the initial weights and biases of ELM,so as to improve the generalization ability and prediction capacity of ELM;(3)We use the Adaboost algorithm to integrate multiple ELM basic predictors optimized by adaptive genetic algorithm into a strong predictor,which can further improve the effect of defect prediction.To effectively evaluate the performance of KAEA,we use eleven datasets from large open source projects,and compare the KAEA with four machine learning basic classifiers,ELM and its three variants.The experimental results show that KAEA is superior to these baseline models in most cases.展开更多
This paper uses a three-stage DEA model to measure the land use efficiency of the three major urban agglomerations in the Yangtze River Delta,Beijing-Tianjin-Hebei,and the Pearl River Delta from 2007 to 2018.The follo...This paper uses a three-stage DEA model to measure the land use efficiency of the three major urban agglomerations in the Yangtze River Delta,Beijing-Tianjin-Hebei,and the Pearl River Delta from 2007 to 2018.The following conclusions are drawn through research:first,the urban land use efficiency of the three major urban agglomerations in the Yangtze River Delta,Beijing-Tianjin-Hebei,and the Pearl River Delta all showed a downward trend,with the rates of decline being 6.06%,2.86%,and 24.34%respectively.In particular,the Pearl River Delta urban agglomeration had the largest decline.Second,the overall urban land use efficiency of the Beijing-Tianjin-Hebei urban agglomeration is relatively high,and the amount of redundancy is relatively small.The rate of decline is significantly lower than the urban land use efficiency of the two major urban agglomerations in the Yangtze River Delta and the Pearl River Delta.The land use efficiency of the Yangtze River Delta and Pearl River Delta urban agglomerations is in a state of continuous decline.Third,the proportion of cities with the effectiveness of returns to scale of urban land use efficiency in the three major urban agglomerations has decreased by 10.53%,10%,and 33.34%,respectively.The Pearl River Delta has the largest decline.Fourth,the land use efficiency of the Yangtze River Delta urban agglomeration is quite different.The central-peripheral phenomenon is evident for the Beijing-Tianjin-Hebei urban agglomerations and the Pearl River Delta urban agglomerations.展开更多
Objective: To investigate the effects of standardized three-stage rehabilitation combined with edaravone therapy on the neurotrophic state and oxidative stress injury in patients with cerebral infarction. Methods: A t...Objective: To investigate the effects of standardized three-stage rehabilitation combined with edaravone therapy on the neurotrophic state and oxidative stress injury in patients with cerebral infarction. Methods: A total of 90 patients with acute cerebral infarction who were treated in the hospital between May 2015 and April 2017 were divided into control group (n=45) and observation group (n=45) by random number table. Control group received edaravone therapy, and observation group received standardized three-stage rehabilitation combined with edaravone therapy. The differences in neurotrophic state and oxidative stress injury were compared between the two groups before and after treatment. Results: There was no statistically significant difference in serum levels of neurotrophic indexes and oxidative stress indexes between the two groups before treatment. After treatment, serum neurotrophic indexes BDNF and NGF levels of observation group were higher than those of control group;serum oxidation indexes AOPPs, LHP and MDA levels were lower than those of control group whereas SOD, CAT and T-AOC levels were higher than those of control group. Conclusion:Standardized three-stage rehabilitation combined with edaravone therapy can effectively optimize the neurotrophic state and inhibit the oxidative stress in patients with cerebral infarction.展开更多
文摘Companies are eager to have a smart supply chain especially when they have adynamic system.Industry 4.0 is a concept which concentrates on mobility andreal-time integration.Thus,it can be considered as a necessary component thathas to be implemented for a dynamic vehicle routing problem.The aim of thisresearch is to solve large-scale DVRP(LSDVRP)in which the delivery vehiclesmust serve customer demands from a common depot to minimize transit costswhile not exceeding the capacity constraint of each vehicle.In LSDVRP,it isdifficult to get an exact solution and the computational time complexity growsexponentially.To find near-optimal answers for this problem,a hierarchicalapproach consisting of three stages:“clustering,route-construction,routeimprovement”is proposed.The major contribution of this paper is dealing withLSDVRP to propose the three-stage algorithm with better results.The resultsconfirmed that the proposed methodology is applicable.
文摘BACKGROUND Patients with gastric cancer often experience slow postoperative recovery and psychological stress,necessitating enhanced nursing care to improve their prognosis.AIM To analyze the impact of a timing-theory-guided three-stage integrated nursing intervention(TSIN)on the postoperative recovery of patients undergoing gastric cancer surgery.METHODS Total 84 patients that underwent gastric cancer surgeries between June 2022 and June 2024 were selected and divided into a control group and an observation group based on perioperative nursing methods.The control group(n=42)received routine nursing care,whereas the observation group(n=42)received a timing-theory-guided TSIN.The psychological adjustment capabilities,psychological stress,cancer-related fatigue levels,postoperative recovery,and quality of life of the two groups were compared.RESULTS Compared to the control group,the observation group took lesser time to get out of bed,achieve gastrointestinal motility,have the first mealtime,along with a shorter hospital stay(P<0.05).Before nursing,there were no significant differences between groups’parameters or scores(P>0.05).After nursing,the scores for psychological stress and cancer-related fatigue decreased.In contrast,the scores for psychological adjustment capabilities and quality of life increased,with more significant improvements observed in the observation group,showing significant differences within and between the groups(P<0.05).CONCLUSION Timing theory-guided TSIN can improve the psychological adjustment capabilities of patients undergoing gastric cancer surgery,reduce psychological stress and cancer-related fatigue,accelerate postoperative recovery,and improve the quality of life.
基金financial support was provided by the National Natural Science Foundation of China(Nos.52476146,52006008,and 52471219)the Guangdong Basic and Applied Basic Research Foundation(2023A1515140059 and 2025A1515011255)+2 种基金the Peking University Third Hospital Haidian transformation project(HDCXZHKC2023210)the National Foreign Expert Individual Human Project(Category H,No.H20240116)the State Key Laboratory of New Ceramic Materials Tsinghua University(No.KFZD202402).
文摘The latent heat thermal energy storage system with solid-liquid phase-change material(SLPCM-LHTES)as energy storage medium provides outstanding advantages such as system simplicity,stable temperature control,and high energy storage density,showing great potential toward addressing the energy storage problems associated with decentralized,intermittent,and unstable renewable energy sources.Notably,effective heat transfer within the SLPCM-LHTES is crucial for extending its application potential.Therefore,a comprehensive understanding of the heat transfer processes in SLPCM-LHTES from a theoretical perspective is necessary.In this review,we propose a three-stage heat transfer pathway in SLPCM-LHTES,including external heating,interfacial heat transfer,and intrinsic phase transition processes.From the perspective of this three-stage pathway,the theoretical basis of heat transfer processes and typical efficiency enhancement strategies in SLPCM-LHTES are summarized.Moreover,an overview of the typical applications of SLPCM-LHTES in various fields,such as building energy efficiency,textiles and garments,and battery thermal management,is presented.Finally,the remaining challenges and possible avenues of research in this burgeoning field will also be discussed.
基金Supported by the National Basic Research Program of China(2012CB720500)the National High Technology Research and Development Program of China(2013AA040702)
文摘This paper introduces a practical solving scheme of gradetransition trajectory optimization(GTTO) problems under typical certificate-checking–updating framework. Due to complicated kinetics of polymerization,differential/algebraic equations(DAEs) always cause great computational burden and system non-linearity usually makes GTTO non-convex bearing multiple optima. Therefore, coupled with the three-stage decomposition model, a three-section algorithm of dynamic programming(TSDP) is proposed based on the general iteration mechanism of iterative programming(IDP) and incorporated with adaptivegrid allocation scheme and heuristic modifications. The algorithm iteratively performs dynamic programming with heuristic modifications under constant calculation loads and adaptively allocates the valued computational resources to the regions that can further improve the optimality under the guidance of local error estimates. TSDP is finally compared with IDP and interior point method(IP) to verify its efficiency of computation.
基金Funded by the National Basic Research Program of China (No.2007CB307102)National High Tech Research and Development Program of China (No.2005AA121210)National Natural Science Foundation of China (No. 60572042)
文摘Current MSM switching fabric has poor performance under unbalanced traffic. This paper presents an alternative, novel Central-stage Buffered Three-stage Clos switching (CB-3Clos) fabric and proves that this fabric can emulate output queuing switch without any speedup. By analyzing the condition to satisfy the central-stage load-balance, this paper also proposes a Central-stage Load-balanced-based Distributed Scheduling algorithm (CLDS) for CB-3Clos. The results show that, compared with Concurrent Round-Robin based Dispatching (CRRD) algorithm based on MSM, CLDS algorithm has high throughput irrespective with the traffic model and better performance in mean packet delay.
基金Supported by National Natural Science Foundation of China(Grant Nos.52205529 and 62303204)the Youth Innovation Team Program of Shandong Higher Education Institution(Grant No.2023KJ206)the Guangyue Youth Scholar Innovation Talent Program support received from Liaocheng University(Grant No.LCUGYTD2022-03)。
文摘The flexible job shop scheduling problem(FJSP)is commonly encountered in practical manufacturing environments.A product is typically built by assembling multiple jobs during actual manufacturing.AGVs are normally used to transport the jobs from the processing shop to the assembly shop,where they are assembled.Therefore,studying the integrated scheduling problem with its processing,transportation,and assembly stages is extremely beneficial and significant.This research studies the three-stage flexible job shop scheduling problem with assembly and AGV transportation(FJSP-T-A),which includes processing jobs,transporting them via AGVs,and assembling them.A mixed integer linear programming(MILP)model is established to obtain optimal solutions.As the MILP model is challenging for solving large-scale problems,a novel co-evolutionary algorithm(NCEA)with two different decoding methods is proposed.In NCEA,a restart operation is developed to improve the diversity of the population,and a multiple crossover strategy is designed to improve the quality of individuals.The validity of the MILP model is proven by analyzing its complexity.The effectiveness of the restart operator,multiple crossovers,and the proposed algorithm is demonstrated by calculating and analyzing the RPI values of each algorithm's results within the time limit and performing a paired t-test on the average values of each algorithm at the 95%confidence level.This paper studies FJSP-T-A by minimizing the makespan for the first time,and presents a MILP model and an NCEA with two different decoding methods.
基金National Key Research and Development Program of China,No.2023YFC3006704National Natural Science Foundation of China,No.42171047CAS-CSIRO Partnership Joint Project of 2024,No.177GJHZ2023097MI。
文摘Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.
基金supported by the Research Project of China Southern Power Grid(No.056200KK52222031).
文摘This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.
基金supported by the Major Science and Technology Programs in Henan Province(No.241100210100)Henan Provincial Science and Technology Research Project(No.252102211085,No.252102211105)+3 种基金Endogenous Security Cloud Network Convergence R&D Center(No.602431011PQ1)The Special Project for Research and Development in Key Areas of Guangdong Province(No.2021ZDZX1098)The Stabilization Support Program of Science,Technology and Innovation Commission of Shenzhen Municipality(No.20231128083944001)The Key scientific research projects of Henan higher education institutions(No.24A520042).
文摘Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.
基金Projects(51878667,51678571)supported by the National Natural Science Foundation of ChinaProject(2018zzts657)supported by the Central South University Postgraduates’Innovation,ChinaProject(2018JJ2517)supported by the Hunan Provincial Natural Science Foundation of China。
文摘Based on a typical prototype of a soil slope in engineering practice, a numerical model of a three-stage soil slope supported by the anchor frame structure was established by means of FLAC3D code. The dynamic responses of three-stage soil slope and frame structure were studied by performing a series of bidirectional Wenchuan motions in terms of the failure mode of three-stage structure, the acceleration of soil slope, the displacement of frame structure, and the anchor stress of frame structure. The response accelerations in both horizontal and vertical directions are the most largely amplified at the slope top of each stage subjected to different shaking cases. The platforms among the stages reduce the amplification effect of response acceleration. The residual displacement of frame structure increases significantly as the intensity of shaking case increases. The frame structure at each stage presents a combined displacement mode consisting of a translation and a rotation around the vertex. The anchor stress of frame structure is mainly increased by the first intense pulse of Wenchuan seismic wave, and it is sensitive to the intensity of shaking case. The anchor stress of frame structure at the first stage is the most considerably enlarged by earthquake loading.
基金the National Social Science Foundation of China(No.11BGL028)Higher Education Research Fund for the Doctoral Program of China(No.20110095110003)
文摘Based on three-stage data envelopment analysis(DEA) model estimates of resource utilization efficiency of coal,we selected 29 provinces from China's 2012 input-output data and used the bootstrap DEA model to correct the bias.The results show that the mean overall technical efficiency,pure technical efficiency,and scale efficiency was 0.833,0.998,and 0.711 in 2012,respectively.Moreover,the comprehensive technical efficiency score indicates that the scale is invalid.Area utilization efficiencies for the eastern,central,and western regions were 0.917,0.731,and 0.629,respectively.The results prove that there are significant differences in the distribution of coal resources utilization efficiency across regions.
文摘Two-oriented agriculture was a complex organism coupling production,economics,society and ecology.Its development process was affected by various factors such as producers,nature,society,etc.In order to overcome measurement error of traditional data envelopment analysis caused by ignoring random,three-stage DEA model was studied to remove environmental factors and random effects.On the foundation of this model was two-oriented agriculture comprehensive production efficiency of 14 cities were estimated in Hunan Province in 2008,and brown forth corresponding policy proposals to promote agricultural development.
文摘From the perspective of agricultural insurance agency,this paper focuses on the study of operational efficiency of agricultural insurance agency,and analyzes the operational efficiency of agricultural insurance agency and its influencing factors,in order to improve the operational efficiency of agricultural insurance agency,better supply agricultural insurance and achieve the policy effect of agricultural insurance.The results of this paper are as follows:( i) Either comprehensive operational efficiency or scale efficiency of Chinese-funded agency is higher than that of foreign-funded agency,but its pure technical efficiency is lower than that of foreign-funded agency,indicating that the managerial decision ability of Chinese-funded agency is weaker than that of foreign-funded agency,and needs to be improved;( ii) The operational efficiency of professional agricultural insurance agency is higher than that of comprehensive agricultural insurance agency,and the agricultural insurance agency is greatly affected by environmental factors;( iii) The operating time of agricultural insurance agency is proportional to its operational efficiency;( iv) The quality of employees is positively correlated with the capital and cost input difference,but negatively correlated with the difference in the number of employees. Therefore,it is necessary to pay attention to the improvement of employees' working efficiency while laying emphasis on employees' quality.
文摘The use of an electrical network as close as possible to its limits can lead to its instability in the event of a high amplitude disturbance. The damping of system oscillations can be achieved by conventional means of voltage and speed regulation but also by FACTS (Flexible AC Transmission Systems) devices, which are increasingly used in power networks. In this work, optimal control coordination between a hybrid power flow controller and a three-level inverter was used to improve the transient stability of a transmission line. The UPFC is a combination of a serial compensator (SSSC) and a parallel compensator (STATCOM) both connected to a DC-LINK DC bus. The SSSC acts as a voltage source for the network and injects a voltage that can be adjusted in phase and amplitude in addition to the network voltage;the STATCOM acts as a current source. The approach used is tested in the Matlab Simulink environment on a single machine network. Optimal controller tuning gives a better transient stability improvement by reducing the transport angle oscillations from 248.17% to 9.85%.
基金Ministry of Science and Technology of China(No.2006BAF01B12-03)
文摘In order to improve the dynamic response bandwidth of three-stage electro-hydraulic servo valve,a new method,speed-feedback control is presented in this paper.The construction and principle of three-stage electro-hydraulic servo valve are explained,and the mathematical model of three-stage electro-hydraulic servo valve is built in frequency domain.Experimental and simulation results show that the bandwidth compared with proportional control is improved under speed-feedback control.Moreover,the research results play an important role in developing high performance three-stage electro-hydraulic servo valve.
基金financially supported by the National 863 Plan(2010AA03A405and 2012AA062303)+4 种基金the National 973 Plan(2012CBA01205)the National Natural Science Foundation of China(U120227451204040)the National Science and Technology Support Program(2012BAE01B02)the Fundamental Research Funds for the Central Universities(N130702001 and N130607001)
文摘Numerical simulation of enhanced fluid flow characteristics in a three-stage double-stirring extraction tank was conducted with the coupling of an Eulerian multiphase flow model and a Morsi-Alexander interphase drag force model. Results show that the addition of a stirring device into the settler can efficiently reduce the volume fraction of out-of-phase impurity in the outlet, and accelerate the settling separation of oil-water mixture. Such addition can also effectively break down the oil-water-wrapped liquid droplets coming from the mixer, inhibit reflux from the outlet, and improve the oil-water separation. The addition of a stirring device induces ignorable power consumption compared with that by the mixer, and can thus facilitate the commercialized promotion of this novel equipment.
基金supported by the National Natural Science Foundation of China(grants No.41172062, 40872054 and 40372043)the China Geological Survey(grant No.1212010811033)
文摘Objective Rapakivi granites,characterized by rapakivi texture,Atype granite feature and an anorogenic setting,commonly occur in the Proterozoic of the Northern Hemisphere（Fig.la）.Recently,more and more Phanerozoic rapakivi granite suites have been identified and some even occur in orogenic belts.Significantly,three-stage,Proterozoic.
基金This work is supported in part by the National Science Foundation of China(61672392,61373038)in part by the National Key Research and Development Program of China(No.2016YFC1202204).
文摘Software defect prediction is a research hotspot in the field of software engineering.However,due to the limitations of current machine learning algorithms,we can’t achieve good effect for defect prediction by only using machine learning algorithms.In previous studies,some researchers used extreme learning machine(ELM)to conduct defect prediction.However,the initial weights and biases of the ELM are determined randomly,which reduces the prediction performance of ELM.Motivated by the idea of search based software engineering,we propose a novel software defect prediction model named KAEA based on kernel principal component analysis(KPCA),adaptive genetic algorithm,extreme learning machine and Adaboost algorithm,which has three main advantages:(1)KPCA can extract optimal representative features by leveraging a nonlinear mapping function;(2)We leverage adaptive genetic algorithm to optimize the initial weights and biases of ELM,so as to improve the generalization ability and prediction capacity of ELM;(3)We use the Adaboost algorithm to integrate multiple ELM basic predictors optimized by adaptive genetic algorithm into a strong predictor,which can further improve the effect of defect prediction.To effectively evaluate the performance of KAEA,we use eleven datasets from large open source projects,and compare the KAEA with four machine learning basic classifiers,ELM and its three variants.The experimental results show that KAEA is superior to these baseline models in most cases.
文摘This paper uses a three-stage DEA model to measure the land use efficiency of the three major urban agglomerations in the Yangtze River Delta,Beijing-Tianjin-Hebei,and the Pearl River Delta from 2007 to 2018.The following conclusions are drawn through research:first,the urban land use efficiency of the three major urban agglomerations in the Yangtze River Delta,Beijing-Tianjin-Hebei,and the Pearl River Delta all showed a downward trend,with the rates of decline being 6.06%,2.86%,and 24.34%respectively.In particular,the Pearl River Delta urban agglomeration had the largest decline.Second,the overall urban land use efficiency of the Beijing-Tianjin-Hebei urban agglomeration is relatively high,and the amount of redundancy is relatively small.The rate of decline is significantly lower than the urban land use efficiency of the two major urban agglomerations in the Yangtze River Delta and the Pearl River Delta.The land use efficiency of the Yangtze River Delta and Pearl River Delta urban agglomerations is in a state of continuous decline.Third,the proportion of cities with the effectiveness of returns to scale of urban land use efficiency in the three major urban agglomerations has decreased by 10.53%,10%,and 33.34%,respectively.The Pearl River Delta has the largest decline.Fourth,the land use efficiency of the Yangtze River Delta urban agglomeration is quite different.The central-peripheral phenomenon is evident for the Beijing-Tianjin-Hebei urban agglomerations and the Pearl River Delta urban agglomerations.
文摘Objective: To investigate the effects of standardized three-stage rehabilitation combined with edaravone therapy on the neurotrophic state and oxidative stress injury in patients with cerebral infarction. Methods: A total of 90 patients with acute cerebral infarction who were treated in the hospital between May 2015 and April 2017 were divided into control group (n=45) and observation group (n=45) by random number table. Control group received edaravone therapy, and observation group received standardized three-stage rehabilitation combined with edaravone therapy. The differences in neurotrophic state and oxidative stress injury were compared between the two groups before and after treatment. Results: There was no statistically significant difference in serum levels of neurotrophic indexes and oxidative stress indexes between the two groups before treatment. After treatment, serum neurotrophic indexes BDNF and NGF levels of observation group were higher than those of control group;serum oxidation indexes AOPPs, LHP and MDA levels were lower than those of control group whereas SOD, CAT and T-AOC levels were higher than those of control group. Conclusion:Standardized three-stage rehabilitation combined with edaravone therapy can effectively optimize the neurotrophic state and inhibit the oxidative stress in patients with cerebral infarction.
