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
In the background of the low-carbon transformation of the energy structure,the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy sy...In the background of the low-carbon transformation of the energy structure,the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy systems(IES)is becoming increasingly obvious.In this case,to promote the low-carbon operation of IES and renewable energy consumption,and to improve the IES anti-interference ability,this paper proposes an IES scheduling strategy that considers CCS-P2G and concentrating solar power(CSP)station.Firstly,CSP station,gas hydrogen doping mode and variable hydrogen doping ratio mode are applied to IES,and combined with CCS-P2G coupling model,the IES low-carbon economic dispatch model is established.Secondly,the stepped carbon trading mechanism is applied,and the sensitivity analysis of IES carbon trading is carried out.Finally,an IES optimal scheduling strategy based on fuzzy opportunity constraints and an IES risk assessment strategy based on CVaR theory are established.The simulation shows that the gas-hydrogen doping model proposed in this paper reduces the operating cost and carbon emission of IES by 1.32%and 7.17%,and improves the carbon benefit by 5.73%;variable hydrogen doping ratio model reduces the operating cost and carbon emission of IES by 3.75%and 1.70%,respectively;CSP stations reduce 19.64%and 38.52%of the operating costs of IES and 1.03%and 1.80%of the carbon emissions of IES respectively compared to equal-capacity photovoltaic and wind turbines;the baseline price of carbon trading of IES and its rate of change jointly affect the carbon emissions of IES;evaluating the anti-interference capability of IES through trapezoidal fuzzy number and weighting coefficients,enabling IES to guarantee operation at the lowest cost.展开更多
The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(I...The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.展开更多
Electric Vehicles(EVs)have emerged as a cleaner,low-carbon,and environmentally friendly alternative to traditional internal combustion engine(ICE)vehicles.With the increasing adoption of EVs,they are expected to event...Electric Vehicles(EVs)have emerged as a cleaner,low-carbon,and environmentally friendly alternative to traditional internal combustion engine(ICE)vehicles.With the increasing adoption of EVs,they are expected to eventually replace ICE vehicles entirely.However,the rapid growth of EVs has significantly increased energy demand,posing challenges for power grids and infrastructure.This surge in energy demand has driven advancements in developing efficient charging infrastructure and energy management solutions to mitigate the risks of power outages and disruptions caused by the rising number of EVs on the road.To address these challenges,various deep learning(DL)models,such as Recurrent Neural Networks(RNNs)and Long Short-Term Memory(LSTM)networks,have been employed for predicting energy demand at EV charging stations(EVCS).However,these models face certain limitations.They often lack interpretability,treating all input steps equally without assigning greater importance to critical patterns that are more relevant for prediction.Additionally,these models process data sequentially,which makes them computationally slower and less efficient when dealing with large datasets.In the context of these limitations,this paper introduces a novel Attention-Augmented Long Short-Term Memory(AA-LSTM)model.The proposed model integrates an attention mechanism to focus on the most relevant time steps,thereby enhancing its ability to capture long-term dependencies and improve prediction accuracy.By combining the strengths of LSTM networks in handling sequential data with the interpretability and efficiency of the attention mechanism,the AA-LSTM model delivers superior performance.The attention mechanism selectively prioritizes critical parts of the input sequence,reducing the computational burden and making the model faster and more effective.The AA-LSTM model achieves impressive results,demonstrating a Mean Absolute Percentage Error(MAPE)of 3.90%and a Mean Squared Error(MSE)of 0.40,highlighting its accuracy and reliability.These results suggest that the AA-LSTM model is a highly promising solution for predicting energy demand at EVCS,offering improved performance and efficiency compared to contemporary approaches.展开更多
Through the demand analysis of emergency power supply construction, waterfall noise reduction treatment, and utilization of residual pressure resources, combined with water resources and industrial infrastructure cond...Through the demand analysis of emergency power supply construction, waterfall noise reduction treatment, and utilization of residual pressure resources, combined with water resources and industrial infrastructure conditions, this paper proposes the significance of micro hydropower station construction. However, micro hydropower stations face issues such as insufficient construction standardization, prominent safety hazards, lack of specialized standards, and the need for improved planning and design. Therefore, this paper analyzes and discusses the constraints and improvement summaries in the entire construction process of micro hydropower stations from aspects including guidance of standard formulation, rationality of planning and design, and innovation of new product applications.展开更多
This article focuses on the municipal prefabricated bathroom station.It elaborates on its modular design concept,including key design points such as spatial layout,functional modules,and determination of key parameter...This article focuses on the municipal prefabricated bathroom station.It elaborates on its modular design concept,including key design points such as spatial layout,functional modules,and determination of key parameters;introduces the optimization of intelligent production processes,precision control,and integration of construction technology,and also mentions the verification of full lifecycle applications and quality control;as well as emphasizes the importance of BIM+IoT platform and looks forward to the future.展开更多
Aiming at the problem of mobile data traffic surge in 5G networks,this paper proposes an effective solution combining massive multiple-input multiple-output techniques with Ultra-Dense Network(UDN)and focuses on solvi...Aiming at the problem of mobile data traffic surge in 5G networks,this paper proposes an effective solution combining massive multiple-input multiple-output techniques with Ultra-Dense Network(UDN)and focuses on solving the resulting challenge of increased energy consumption.A base station control algorithm based on Multi-Agent Proximity Policy Optimization(MAPPO)is designed.In the constructed 5G UDN model,each base station is considered as an agent,and the MAPPO algorithm enables inter-base station collaboration and interference management to optimize the network performance.To reduce the extra power consumption due to frequent sleep mode switching of base stations,a sleep mode switching decision algorithm is proposed.The algorithm reduces unnecessary power consumption by evaluating the network state similarity and intelligently adjusting the agent’s action strategy.Simulation results show that the proposed algorithm reduces the power consumption by 24.61% compared to the no-sleep strategy and further reduces the power consumption by 5.36% compared to the traditional MAPPO algorithm under the premise of guaranteeing the quality of service of users.展开更多
As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowc...As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowcarbon goals,offshore wind power has emerged as a key renewable energy source,yet its booster stations face harsh marine environments,including persistent wave impacts,salt spray corrosion,and equipment-induced vibrations.Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations:low efficiency,poor real-time performance,and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.To address these challenges,this study proposes a biomechanics-driven structural safety monitoring system integrated with deep learning.Inspired by biological stress-sensing mechanisms,the system deploys a distributedmulti-dimensional force sensor network to capture real-time stress distributions in key structural components.A hybrid convolutional neural network-radial basis function(CNN-RBF)model is developed:the CNN branch extracts spatiotemporal features from multi-source sensing data,while the RBF branch reconstructs the nonlinear stress field for accurate anomaly diagnosis.The three-tier architectural design—data layer(distributed sensor array),function layer(CNN-RBF modeling),and application layer(edge computing terminal)—enables a closedloop process from high-resolution data collection to real-time early warning,with data processing delay controlled within 200 ms.Experimental validation against traditional SOM-based systems demonstrates significant performance improvements:monitoring accuracy increased by 19.8%,efficiency by 23.4%,recall rate by 20.5%,and F1 score by 21.6%.Under extreme weather(e.g.,typhoons and winter storms),the system’s stability is 40% higher,with user satisfaction improving by 17.2%.The biomechanics-inspired sensor design enhances survival rates in salt fog(85.7%improvement)and dynamic loads,highlighting its robust engineering applicability for intelligent offshore wind farm maintenance.展开更多
To investigate the response of Roadside Monitoring Stations(RSs)to traffic-related air pollution,traffic and pollutant characteristics,influencing factors,and potential source characterization in Tianjin,China were de...To investigate the response of Roadside Monitoring Stations(RSs)to traffic-related air pollution,traffic and pollutant characteristics,influencing factors,and potential source characterization in Tianjin,China were determined based on roadside monitoring of real-world data conducted at RSs in 2022.The diurnal variation trend of pollutants at RSs was consistent with that at the National Monitoring Station(NM),with notably higher pollutant fluctuations during the morning and evening peak traffic times at RSs,where the average diurnal concentration was 41.46%higher than that at the NM.The generalized additive model(GAM)for nitrogen oxides(NO_(x))and carbon monoxide(CO),responding to themultiple influencing factors,performed well at RSs,with deviance explained by 86.6%and 61.4%,respectively.The synergistic effects of wind direction and speed contributed to most of the variations in NO_(x) and CO,which were 14.74%and 12.87%,respectively.Pollutant concentrations were highest under windless conditions,with pollutants originating primarily from local vehicle emissions.The model results indicated that medium-duty truck(MDT)traffic flow predominantly contributed to the variability in NO_(x) emissions,whereas passenger car(PC)traffic flow was the primary source of CO emissions from traffic variables.MDTs should be the focus of urban NO_(x) traffic emissions control.Potential-source analysis validated the results obtained from the GAM,and both analyses showed that RSs can better characterize traffic-related air pollutants.Furthermore,more stringent emission standards have effectively mitigated the release of pollutants from motor vehicles and contributed to the modernization of vehicle fleet composition,effectively decreasing CO concentrations.展开更多
Taking Huanghua Port Railway Station of the Shuozhou-Huanghua Railway as a demonstration case,an overall solution for the 5G-based intelligent shunting system at heavy haul railway stations was developed to address th...Taking Huanghua Port Railway Station of the Shuozhou-Huanghua Railway as a demonstration case,an overall solution for the 5G-based intelligent shunting system at heavy haul railway stations was developed to address the operational complexities,inadequacies of outdated equipment,and low efficiency experienced by shunting operators.The system utilizes a 5G communication platform to facilitate automated and intelligent shunting operations at heavy haul railway stations.Advanced technological equipment for intelligent shunting in heavy haul railways was developed,encompassing a big data center,intelligent dispatching and control systems,automated and remote operation of locomotives,intelligent cloud-based video surveillance,intelligent dual-powered electric locomotive,and a customized 5G private network.Technical measures are implemented to reduce operators'labor intensity,decrease the number of on-site personnel,ensure effective safety protection for operators,improve utilization of arrival and departure tracks at heavy haul railway stations,and promote the development of“smart,intelligent,interconnected,and sensing”heavy haul railway stations.展开更多
In order to monitor large-area mining subsidence accurately, a high-precision global navigation satellite system （GNSS） monitoring network was established based on the nearby international GNSS service （IGS） stati...In order to monitor large-area mining subsidence accurately, a high-precision global navigation satellite system （GNSS） monitoring network was established based on the nearby international GNSS service （IGS） stations taken as reference points. Given the non-linear motions of IGS stations, the robust Kalman filtering （RKF） model was presented to determine the datum of multi-period monitoring network considering the velocity and weekly solution of IGS stations. The theory proposed was applied to monitoring mining subsidence in northern Anhui coal mine in China. According to the case study, the RKF model to establish monitoring datum is better than the prediction method and the weekly solution from IGS analysis centers （ACs）, and the corresponding precision of deformation can reach up to millimeter level with 4 h observation. The research provides an efficient and accurate approach for monitoring large-area mining subsidence.展开更多
To alleviate the resulting increase in energy consumption and emissions and other issues caused by the traffic congestion ahead of the expressway toll station, a novel traffic flowcontrol method is put forward based o...To alleviate the resulting increase in energy consumption and emissions and other issues caused by the traffic congestion ahead of the expressway toll station, a novel traffic flowcontrol method is put forward based on the environment-friendly conception. The technical thinking of inducing the slowly moving traffic into a batch pass is determined based on the conclusion of the research, traffic flowtheory and traffic sensing detection technology. The model of stop times is established and the parameters of the system are optimized in accordance with the principle of minimizing the fuel consumption. The optimal location selection of traffic control lights and Detector 2 for queue of different lengths at toll stations are calculated based on the model. Finally, the effect of the congestion flowcontrol system is verified via the Paramics simulation system. The result shows that the control system is capable of reducing90% of fuel consumption for vehicles going through toll stations.展开更多
Through investigation and analysis on typical system of pumped-storage stations built in China, this paper approaches the investment andfinancing policies, electricity pricing policies and management modes for suchsta...Through investigation and analysis on typical system of pumped-storage stations built in China, this paper approaches the investment andfinancing policies, electricity pricing policies and management modes for suchstations. In order to find out the actual operation situations, eight pumped-storage stations in five provinces (municipality) were investigated, and analysesand calculations were carried out on their investments, benefits, capabilities ofloan-repaying etc. During the investigation and study, the types and the installedcapacities of the stations were paid close attention to, so they were made morerepresentative to reflect the present situation of pumped-storage stations inrespect of construction and operation.展开更多
A service station plays an important role in the petroleum product distribution terminal. With the increase in petroleum consumption in China, the inventory theory should be applied in the stock control of service st...A service station plays an important role in the petroleum product distribution terminal. With the increase in petroleum consumption in China, the inventory theory should be applied in the stock control of service stations. In this paper the inventory theory including its background and characteristics is introduced. At the same time, the application of the theory in some trades today, especially in petroleum trade, is analyzed. Then (s, S) stochastic model is advanced, which is established according to the principle of operational research and, based on this model, a sample is given, which discusses the details of application in the stock control of service stations. The sample is simplified but implies the validity of the model in optimizing the storage of petroleum products in the market.展开更多
CHINA.5G Base Stations See Strong Growth.China witnessed substantial growth in the number of 5G base stations in 2025,according to data from the Ministry of Industry and Information Technology.As of the end of October...CHINA.5G Base Stations See Strong Growth.China witnessed substantial growth in the number of 5G base stations in 2025,according to data from the Ministry of Industry and Information Technology.As of the end of October 2025,the total number of 5G base stations in the country reached around 4.76 million,with a net increase of 507,000 from the end of last year,accounting for 37 percent of all mobile base stations.展开更多
We investigated the seasonal and spatial ozone variations in China by using three-year surface ozone observation data from the six Chinese Global Atmosphere Watch(GAW)stations and tropospheric column ozone data from s...We investigated the seasonal and spatial ozone variations in China by using three-year surface ozone observation data from the six Chinese Global Atmosphere Watch(GAW)stations and tropospheric column ozone data from satellite retrieval over the period2010–2012. It is shown that the seasonal ozone variations at these GAW stations are rather different, particularly between the western and eastern locations. Compared with western China, eastern China has lower background ozone levels. However, the Asian summer monsoon(ASM) can transport photochemical pollutants from the southern to the northern areas in eastern China, leading to a northward gradual enhancement of background ozone levels at the eastern GAW stations. Over China, the tropospheric column ozone densities peak during spring and summer in the areas that are directly and/or indirectly affected by the ASM, and the peak time lags from the south to the north in eastern China. We also investigated the regional representativeness of seasonal variations of ozone at the six Chinese GAW stations using the yearly maximum tropospheric column month as indicator.The results show that the seasonal variation characteristics of ozone revealed by the Chinese GAW stations are typical, with each station having a considerable large surrounding area with the ozone maximum occurring at the same month. Ozone variations at the GAW stations are influenced by many complex factors and their regional representativeness needs to be investigated further in a broader sense.展开更多
This paper presents a single-site positioning method based on the joint estimation of propagation time-of-arrival(TOA) and direction-of-arrival(DOA), with the assist of virtual stations in the typical non-line-of-sigh...This paper presents a single-site positioning method based on the joint estimation of propagation time-of-arrival(TOA) and direction-of-arrival(DOA), with the assist of virtual stations in the typical non-line-of-sight(NLOS) environment. Consider the influence of multipath noise on the positioning performance, the proposed method firstly presents a modified high-resolution estimation technique called Multipath noise Limiting Matrix Pencil(MLMP) algorithm to achieve the TOA/DOA estimations, in which the matrix pencil and matrix enhancement process are implemented to deal with the measurements from the uniform linear array(ULA) receiver. Meanwhile, the subspace dimension estimation is improved via an adaptive threshold, for enhancing the performance of high-resolution techniques in low signal-noise-ration(SNR) situation. Next the proposed method generates virtual stations utilizing the known floor plan of surrounding reflectors, and adopts a weighted Least Square(WLS) position estimator to calculate the required position, combining the TOA/DOA estimations with the location of virtual stations. Simulations are conducted to evaluate the proposed method under NLOSconditions, and the results show that comparing with the multipath fingerprinting scheme, the proposed method has better performance in various simulation scenarios.展开更多
During the great Wenchuan earthquake, about 460 permanent free-field stations in National Strong Motion Observation Network System （NSMONS） of China captured the main shock acceleration records. These records can be...During the great Wenchuan earthquake, about 460 permanent free-field stations in National Strong Motion Observation Network System （NSMONS） of China captured the main shock acceleration records. These records can be applied to site effect analyses, and then the site classification of those permanent stations can be carried out firstly, which will served as the fundamental information for further research. In this paper, the site of near-fault stations is classified by horizontal-to-vertical spectral ratio （HVSR） method according to the site class description of Japan earthquake resistant design code and response spectral shapes （RSS） method following the site class description of the 1997 Uniform Building Code （UBC） provisions. Then based on the detailed borehole data of those free-field stations, the equivalent shear wave velocity and overburden thickness are calculated and the site classifications are given by Chinese code for seismic design of buildings. Furthermore, for the stations having successful microtremor test data, the site dominant periods are computed to verify the results of site classification. Finally, combined with all the above results, the recommended site classes of near-fault permanent free-field stations are given.展开更多
Transfer station(TS)is an integral part of present-day municipal solid waste(MSW)management systems.To provide information for the incorporation of waste facilities within the current integrated waste management syste...Transfer station(TS)is an integral part of present-day municipal solid waste(MSW)management systems.To provide information for the incorporation of waste facilities within the current integrated waste management system,the authors measured the existing environmental quality at five MSW TSs.Discharged wastewater,air,and noise were monitored and assayed at the five TSs in Beijing in 2001-2006 during rainy seasons(RSs)and dry seasons(DSs).Except Ammonia(NH_3)and hydrogen sulfide(H_2S),the analytical results of...展开更多
In 5G systems, massive multiple-input multiple-output (MIMO) has been adopted in base stations (BSs) to improve spectral efficiency and coverage. The traditional conductive performance test techniques are challenging ...In 5G systems, massive multiple-input multiple-output (MIMO) has been adopted in base stations (BSs) to improve spectral efficiency and coverage. The traditional conductive performance test techniques are challenging due to the unaffordable cost and high complexity when testing a large number of antennas. To solve this problem, the over-the-air (OTA) test has been presented, in which probe selection is the key to reduce the number of channel emulators and probes. In this paper, a novel artificial bee colony (ABC) algorithm is introduced to enhance the efficiency and accuracy of probe selection procedure. A sectoring- based multi-probe anechoic chamber (MPAC) is built to evaluate the throughput performance of massive MIMO equipped in 5G BS. In addition, link level simulation is carried out to evaluate the proposal’s performance gain under the commercial network assumptions, where the average throughput of three velocity is given with different SNR region. The results suggest that OTA chamber and multi-probe wall are available not only for 5G BSs, but also for user equipments (UEs) with end-to-end communication.展开更多
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State Grid Gansu Electric Power Company Science and Technology Program(Grant No.W24FZ2730008)National Natural Science Foundation of China(Grant No.51767017).
文摘In the background of the low-carbon transformation of the energy structure,the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy systems(IES)is becoming increasingly obvious.In this case,to promote the low-carbon operation of IES and renewable energy consumption,and to improve the IES anti-interference ability,this paper proposes an IES scheduling strategy that considers CCS-P2G and concentrating solar power(CSP)station.Firstly,CSP station,gas hydrogen doping mode and variable hydrogen doping ratio mode are applied to IES,and combined with CCS-P2G coupling model,the IES low-carbon economic dispatch model is established.Secondly,the stepped carbon trading mechanism is applied,and the sensitivity analysis of IES carbon trading is carried out.Finally,an IES optimal scheduling strategy based on fuzzy opportunity constraints and an IES risk assessment strategy based on CVaR theory are established.The simulation shows that the gas-hydrogen doping model proposed in this paper reduces the operating cost and carbon emission of IES by 1.32%and 7.17%,and improves the carbon benefit by 5.73%;variable hydrogen doping ratio model reduces the operating cost and carbon emission of IES by 3.75%and 1.70%,respectively;CSP stations reduce 19.64%and 38.52%of the operating costs of IES and 1.03%and 1.80%of the carbon emissions of IES respectively compared to equal-capacity photovoltaic and wind turbines;the baseline price of carbon trading of IES and its rate of change jointly affect the carbon emissions of IES;evaluating the anti-interference capability of IES through trapezoidal fuzzy number and weighting coefficients,enabling IES to guarantee operation at the lowest cost.
基金supported by the National Natural Science Foundation of China(Nos.62272418,62102058)Basic Public Welfare Research Program of Zhejiang Province(No.LGG18E050011)the Major Open Project of Key Laboratory for Advanced Design and Intelligent Computing of the Ministry of Education under Grant ADIC2023ZD001,National Undergraduate Training Program on Innovation and Entrepreneurship(No.202410345054).
文摘The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.
基金supported by the SC&SS,Jawaharlal Nehru University,New Delhi,India.
文摘Electric Vehicles(EVs)have emerged as a cleaner,low-carbon,and environmentally friendly alternative to traditional internal combustion engine(ICE)vehicles.With the increasing adoption of EVs,they are expected to eventually replace ICE vehicles entirely.However,the rapid growth of EVs has significantly increased energy demand,posing challenges for power grids and infrastructure.This surge in energy demand has driven advancements in developing efficient charging infrastructure and energy management solutions to mitigate the risks of power outages and disruptions caused by the rising number of EVs on the road.To address these challenges,various deep learning(DL)models,such as Recurrent Neural Networks(RNNs)and Long Short-Term Memory(LSTM)networks,have been employed for predicting energy demand at EV charging stations(EVCS).However,these models face certain limitations.They often lack interpretability,treating all input steps equally without assigning greater importance to critical patterns that are more relevant for prediction.Additionally,these models process data sequentially,which makes them computationally slower and less efficient when dealing with large datasets.In the context of these limitations,this paper introduces a novel Attention-Augmented Long Short-Term Memory(AA-LSTM)model.The proposed model integrates an attention mechanism to focus on the most relevant time steps,thereby enhancing its ability to capture long-term dependencies and improve prediction accuracy.By combining the strengths of LSTM networks in handling sequential data with the interpretability and efficiency of the attention mechanism,the AA-LSTM model delivers superior performance.The attention mechanism selectively prioritizes critical parts of the input sequence,reducing the computational burden and making the model faster and more effective.The AA-LSTM model achieves impressive results,demonstrating a Mean Absolute Percentage Error(MAPE)of 3.90%and a Mean Squared Error(MSE)of 0.40,highlighting its accuracy and reliability.These results suggest that the AA-LSTM model is a highly promising solution for predicting energy demand at EVCS,offering improved performance and efficiency compared to contemporary approaches.
文摘Through the demand analysis of emergency power supply construction, waterfall noise reduction treatment, and utilization of residual pressure resources, combined with water resources and industrial infrastructure conditions, this paper proposes the significance of micro hydropower station construction. However, micro hydropower stations face issues such as insufficient construction standardization, prominent safety hazards, lack of specialized standards, and the need for improved planning and design. Therefore, this paper analyzes and discusses the constraints and improvement summaries in the entire construction process of micro hydropower stations from aspects including guidance of standard formulation, rationality of planning and design, and innovation of new product applications.
文摘This article focuses on the municipal prefabricated bathroom station.It elaborates on its modular design concept,including key design points such as spatial layout,functional modules,and determination of key parameters;introduces the optimization of intelligent production processes,precision control,and integration of construction technology,and also mentions the verification of full lifecycle applications and quality control;as well as emphasizes the importance of BIM+IoT platform and looks forward to the future.
基金supported by National Natural Science Foundation of China(62271096,U20A20157)Natural Science Foundation of Chongqing,China(CSTB2023NSCQ-LZX0134)+3 种基金University Innovation Research Group of Chongqing(CXQT20017)Youth Innovation Group Support Program of ICE Discipline of CQUPT(SCIE-QN-2022-04)the Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202300632)the Chongqing Postdoctoral Special Funding Project(2022CQBSHTB2057).
文摘Aiming at the problem of mobile data traffic surge in 5G networks,this paper proposes an effective solution combining massive multiple-input multiple-output techniques with Ultra-Dense Network(UDN)and focuses on solving the resulting challenge of increased energy consumption.A base station control algorithm based on Multi-Agent Proximity Policy Optimization(MAPPO)is designed.In the constructed 5G UDN model,each base station is considered as an agent,and the MAPPO algorithm enables inter-base station collaboration and interference management to optimize the network performance.To reduce the extra power consumption due to frequent sleep mode switching of base stations,a sleep mode switching decision algorithm is proposed.The algorithm reduces unnecessary power consumption by evaluating the network state similarity and intelligently adjusting the agent’s action strategy.Simulation results show that the proposed algorithm reduces the power consumption by 24.61% compared to the no-sleep strategy and further reduces the power consumption by 5.36% compared to the traditional MAPPO algorithm under the premise of guaranteeing the quality of service of users.
基金supported by the Science and Technology Project of China Huaneng Group Co.,Ltd.Research on Key Technologies for Monitoring and Protection of Offshore Wind Power Underwater Equipment(HNKJ21-H40).
文摘As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowcarbon goals,offshore wind power has emerged as a key renewable energy source,yet its booster stations face harsh marine environments,including persistent wave impacts,salt spray corrosion,and equipment-induced vibrations.Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations:low efficiency,poor real-time performance,and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.To address these challenges,this study proposes a biomechanics-driven structural safety monitoring system integrated with deep learning.Inspired by biological stress-sensing mechanisms,the system deploys a distributedmulti-dimensional force sensor network to capture real-time stress distributions in key structural components.A hybrid convolutional neural network-radial basis function(CNN-RBF)model is developed:the CNN branch extracts spatiotemporal features from multi-source sensing data,while the RBF branch reconstructs the nonlinear stress field for accurate anomaly diagnosis.The three-tier architectural design—data layer(distributed sensor array),function layer(CNN-RBF modeling),and application layer(edge computing terminal)—enables a closedloop process from high-resolution data collection to real-time early warning,with data processing delay controlled within 200 ms.Experimental validation against traditional SOM-based systems demonstrates significant performance improvements:monitoring accuracy increased by 19.8%,efficiency by 23.4%,recall rate by 20.5%,and F1 score by 21.6%.Under extreme weather(e.g.,typhoons and winter storms),the system’s stability is 40% higher,with user satisfaction improving by 17.2%.The biomechanics-inspired sensor design enhances survival rates in salt fog(85.7%improvement)and dynamic loads,highlighting its robust engineering applicability for intelligent offshore wind farm maintenance.
基金supported by the National Key Research and Development Program of China(Nos.2023YFC3707301 and 2023YFC3705400)the Fundamental Research Funds for the Central Universities(Nos.ZB23003425 and 63211075)。
文摘To investigate the response of Roadside Monitoring Stations(RSs)to traffic-related air pollution,traffic and pollutant characteristics,influencing factors,and potential source characterization in Tianjin,China were determined based on roadside monitoring of real-world data conducted at RSs in 2022.The diurnal variation trend of pollutants at RSs was consistent with that at the National Monitoring Station(NM),with notably higher pollutant fluctuations during the morning and evening peak traffic times at RSs,where the average diurnal concentration was 41.46%higher than that at the NM.The generalized additive model(GAM)for nitrogen oxides(NO_(x))and carbon monoxide(CO),responding to themultiple influencing factors,performed well at RSs,with deviance explained by 86.6%and 61.4%,respectively.The synergistic effects of wind direction and speed contributed to most of the variations in NO_(x) and CO,which were 14.74%and 12.87%,respectively.Pollutant concentrations were highest under windless conditions,with pollutants originating primarily from local vehicle emissions.The model results indicated that medium-duty truck(MDT)traffic flow predominantly contributed to the variability in NO_(x) emissions,whereas passenger car(PC)traffic flow was the primary source of CO emissions from traffic variables.MDTs should be the focus of urban NO_(x) traffic emissions control.Potential-source analysis validated the results obtained from the GAM,and both analyses showed that RSs can better characterize traffic-related air pollutants.Furthermore,more stringent emission standards have effectively mitigated the release of pollutants from motor vehicles and contributed to the modernization of vehicle fleet composition,effectively decreasing CO concentrations.
文摘Taking Huanghua Port Railway Station of the Shuozhou-Huanghua Railway as a demonstration case,an overall solution for the 5G-based intelligent shunting system at heavy haul railway stations was developed to address the operational complexities,inadequacies of outdated equipment,and low efficiency experienced by shunting operators.The system utilizes a 5G communication platform to facilitate automated and intelligent shunting operations at heavy haul railway stations.Advanced technological equipment for intelligent shunting in heavy haul railways was developed,encompassing a big data center,intelligent dispatching and control systems,automated and remote operation of locomotives,intelligent cloud-based video surveillance,intelligent dual-powered electric locomotive,and a customized 5G private network.Technical measures are implemented to reduce operators'labor intensity,decrease the number of on-site personnel,ensure effective safety protection for operators,improve utilization of arrival and departure tracks at heavy haul railway stations,and promote the development of“smart,intelligent,interconnected,and sensing”heavy haul railway stations.
基金Projects(51174206,41204011)supported by the National Natural Science Foundation of ChinaProject supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPDSA1102),China
文摘In order to monitor large-area mining subsidence accurately, a high-precision global navigation satellite system （GNSS） monitoring network was established based on the nearby international GNSS service （IGS） stations taken as reference points. Given the non-linear motions of IGS stations, the robust Kalman filtering （RKF） model was presented to determine the datum of multi-period monitoring network considering the velocity and weekly solution of IGS stations. The theory proposed was applied to monitoring mining subsidence in northern Anhui coal mine in China. According to the case study, the RKF model to establish monitoring datum is better than the prediction method and the weekly solution from IGS analysis centers （ACs）, and the corresponding precision of deformation can reach up to millimeter level with 4 h observation. The research provides an efficient and accurate approach for monitoring large-area mining subsidence.
基金The Natural Science Foundation of Hebei Province(No.E2013202228)the Science and Technology Planning Project of the Department of Transportation of Hebei Province(No.R070245)
文摘To alleviate the resulting increase in energy consumption and emissions and other issues caused by the traffic congestion ahead of the expressway toll station, a novel traffic flowcontrol method is put forward based on the environment-friendly conception. The technical thinking of inducing the slowly moving traffic into a batch pass is determined based on the conclusion of the research, traffic flowtheory and traffic sensing detection technology. The model of stop times is established and the parameters of the system are optimized in accordance with the principle of minimizing the fuel consumption. The optimal location selection of traffic control lights and Detector 2 for queue of different lengths at toll stations are calculated based on the model. Finally, the effect of the congestion flowcontrol system is verified via the Paramics simulation system. The result shows that the control system is capable of reducing90% of fuel consumption for vehicles going through toll stations.
文摘Through investigation and analysis on typical system of pumped-storage stations built in China, this paper approaches the investment andfinancing policies, electricity pricing policies and management modes for suchstations. In order to find out the actual operation situations, eight pumped-storage stations in five provinces (municipality) were investigated, and analysesand calculations were carried out on their investments, benefits, capabilities ofloan-repaying etc. During the investigation and study, the types and the installedcapacities of the stations were paid close attention to, so they were made morerepresentative to reflect the present situation of pumped-storage stations inrespect of construction and operation.
文摘A service station plays an important role in the petroleum product distribution terminal. With the increase in petroleum consumption in China, the inventory theory should be applied in the stock control of service stations. In this paper the inventory theory including its background and characteristics is introduced. At the same time, the application of the theory in some trades today, especially in petroleum trade, is analyzed. Then (s, S) stochastic model is advanced, which is established according to the principle of operational research and, based on this model, a sample is given, which discusses the details of application in the stock control of service stations. The sample is simplified but implies the validity of the model in optimizing the storage of petroleum products in the market.
文摘CHINA.5G Base Stations See Strong Growth.China witnessed substantial growth in the number of 5G base stations in 2025,according to data from the Ministry of Industry and Information Technology.As of the end of October 2025,the total number of 5G base stations in the country reached around 4.76 million,with a net increase of 507,000 from the end of last year,accounting for 37 percent of all mobile base stations.
基金supported by the LAC/CMA(No.2017B02)the National Natural Science Foundation of China(No.41330422)the Special Fund for Meteorological Research in the Public Interest(No.GYHY201206015)
文摘We investigated the seasonal and spatial ozone variations in China by using three-year surface ozone observation data from the six Chinese Global Atmosphere Watch(GAW)stations and tropospheric column ozone data from satellite retrieval over the period2010–2012. It is shown that the seasonal ozone variations at these GAW stations are rather different, particularly between the western and eastern locations. Compared with western China, eastern China has lower background ozone levels. However, the Asian summer monsoon(ASM) can transport photochemical pollutants from the southern to the northern areas in eastern China, leading to a northward gradual enhancement of background ozone levels at the eastern GAW stations. Over China, the tropospheric column ozone densities peak during spring and summer in the areas that are directly and/or indirectly affected by the ASM, and the peak time lags from the south to the north in eastern China. We also investigated the regional representativeness of seasonal variations of ozone at the six Chinese GAW stations using the yearly maximum tropospheric column month as indicator.The results show that the seasonal variation characteristics of ozone revealed by the Chinese GAW stations are typical, with each station having a considerable large surrounding area with the ozone maximum occurring at the same month. Ozone variations at the GAW stations are influenced by many complex factors and their regional representativeness needs to be investigated further in a broader sense.
基金supported in part by the National Natural Science Foundation of China under Grants numbers 61471164, 61601122, 61741102 and 61571128
文摘This paper presents a single-site positioning method based on the joint estimation of propagation time-of-arrival(TOA) and direction-of-arrival(DOA), with the assist of virtual stations in the typical non-line-of-sight(NLOS) environment. Consider the influence of multipath noise on the positioning performance, the proposed method firstly presents a modified high-resolution estimation technique called Multipath noise Limiting Matrix Pencil(MLMP) algorithm to achieve the TOA/DOA estimations, in which the matrix pencil and matrix enhancement process are implemented to deal with the measurements from the uniform linear array(ULA) receiver. Meanwhile, the subspace dimension estimation is improved via an adaptive threshold, for enhancing the performance of high-resolution techniques in low signal-noise-ration(SNR) situation. Next the proposed method generates virtual stations utilizing the known floor plan of surrounding reflectors, and adopts a weighted Least Square(WLS) position estimator to calculate the required position, combining the TOA/DOA estimations with the location of virtual stations. Simulations are conducted to evaluate the proposed method under NLOSconditions, and the results show that comparing with the multipath fingerprinting scheme, the proposed method has better performance in various simulation scenarios.
基金supported by the projects from the Ministry of Science and Technology of China (No.2009BK55B00)China Earthquake Administration (CEA) (No. 200808026)Institute of Engineering Mechanics of CEA (No. 0618001)
文摘During the great Wenchuan earthquake, about 460 permanent free-field stations in National Strong Motion Observation Network System （NSMONS） of China captured the main shock acceleration records. These records can be applied to site effect analyses, and then the site classification of those permanent stations can be carried out firstly, which will served as the fundamental information for further research. In this paper, the site of near-fault stations is classified by horizontal-to-vertical spectral ratio （HVSR） method according to the site class description of Japan earthquake resistant design code and response spectral shapes （RSS） method following the site class description of the 1997 Uniform Building Code （UBC） provisions. Then based on the detailed borehole data of those free-field stations, the equivalent shear wave velocity and overburden thickness are calculated and the site classifications are given by Chinese code for seismic design of buildings. Furthermore, for the stations having successful microtremor test data, the site dominant periods are computed to verify the results of site classification. Finally, combined with all the above results, the recommended site classes of near-fault permanent free-field stations are given.
文摘Transfer station(TS)is an integral part of present-day municipal solid waste(MSW)management systems.To provide information for the incorporation of waste facilities within the current integrated waste management system,the authors measured the existing environmental quality at five MSW TSs.Discharged wastewater,air,and noise were monitored and assayed at the five TSs in Beijing in 2001-2006 during rainy seasons(RSs)and dry seasons(DSs).Except Ammonia(NH_3)and hydrogen sulfide(H_2S),the analytical results of...
基金supported by the State Major Science and Technology Special Projects under Grant No. 2018ZX03001028-003
文摘In 5G systems, massive multiple-input multiple-output (MIMO) has been adopted in base stations (BSs) to improve spectral efficiency and coverage. The traditional conductive performance test techniques are challenging due to the unaffordable cost and high complexity when testing a large number of antennas. To solve this problem, the over-the-air (OTA) test has been presented, in which probe selection is the key to reduce the number of channel emulators and probes. In this paper, a novel artificial bee colony (ABC) algorithm is introduced to enhance the efficiency and accuracy of probe selection procedure. A sectoring- based multi-probe anechoic chamber (MPAC) is built to evaluate the throughput performance of massive MIMO equipped in 5G BS. In addition, link level simulation is carried out to evaluate the proposal’s performance gain under the commercial network assumptions, where the average throughput of three velocity is given with different SNR region. The results suggest that OTA chamber and multi-probe wall are available not only for 5G BSs, but also for user equipments (UEs) with end-to-end communication.
