This paper presents an efficient algorithm for reducing RLC power/ground network complexities by exploitation of the regularities in the power/ground networks. The new method first builds the equivalent models for man...This paper presents an efficient algorithm for reducing RLC power/ground network complexities by exploitation of the regularities in the power/ground networks. The new method first builds the equivalent models for many series RLC-current chains based on their Norton＇s form companion models in the original networks,and then the precondition conjugate gradient based iterative method is used to solve the reduced networks,which are symmetric positive definite. The solutions of the original networks are then back solved from those of the reduced networks.Experimental results show that the complexities of reduced networks are typically significantly smaller than those of the original circuits, which makes the new algorithm extremely fast. For instance, power/ground networks with more than one million branches can be solved in a few minutes on modern Sun workstations.展开更多
A CAD tool based on a group of efficient algorithms to verify,design,and optimize power/ground networks for standard cell model is presented.Nonlinear programming techniques,branch and bound algorithms and incomplete ...A CAD tool based on a group of efficient algorithms to verify,design,and optimize power/ground networks for standard cell model is presented.Nonlinear programming techniques,branch and bound algorithms and incomplete Cholesky decomposition conjugate gradient method (ICCG) are the three main parts of our work.Users can choose nonlinear programming method or branch and bound algorithm to satisfy their different requirements of precision and speed.The experimental results prove that the algorithms can run very fast with lower wiring resources consumption.As a result,the CAD tool based on these algorithms is able to cope with large-scale circuits.展开更多
To realize practical wide-area quantum communication,a satellite-to-ground network with partially entangled states is developed in this paper.For efficiency and security reasons,the existing method of quantum communic...To realize practical wide-area quantum communication,a satellite-to-ground network with partially entangled states is developed in this paper.For efficiency and security reasons,the existing method of quantum communication in distributed wireless quantum networks with partially entangled states cannot be applied directly to the proposed quantum network.Based on this point,an efficient and secure quantum communication scheme with partially entangled states is presented.In our scheme,the source node performs teleportation only after an end-to-end entangled state has been established by entanglement swapping with partially entangled states.Thus,the security of quantum communication is guaranteed.The destination node recovers the transmitted quantum bit with the help of an auxiliary quantum bit and specially defined unitary matrices.Detailed calculations and simulation analyses show that the probability of successfully transferring a quantum bit in the presented scheme is high.In addition,the auxiliary quantum bit provides a heralded mechanism for successful communication.Based on the critical components that are presented in this article an efficient,secure,and practical wide-area quantum communication can be achieved.展开更多
The rapid expansion of satellite Internet deployments,driven by the rise of Space-Ground Integration Network (SGIN) construction,has led to a significant increase in satellite numbers.To address the challenge of effic...The rapid expansion of satellite Internet deployments,driven by the rise of Space-Ground Integration Network (SGIN) construction,has led to a significant increase in satellite numbers.To address the challenge of efficient networking between large-scale satellites and limited ground station resources,this paper presents a hybrid learning-assisted multi-parallel algorithm (HLMP).The HLMP features a multi-parallel solving and deconflicting framework,a learning-assisted metaheuristic (LM) algorithm combining reinforcement learning (RL) and Tabu simulated annealing (TSA),and a linear programming (LP) exact-solving algorithm.The framework first divides the problem into parallel sub-problems based on the time domain,then applies LM and LP to solve each sub-problem in parallel.LM uses LP-generated scheduling results to improve its own accuracy.The deconflicting strategy integrates and refines the planning results from all sub-problems,ensuring an optimized outcome.HLMP advances beyond traditional task-driven satellite scheduling methods by offering a novel approach for optimizing large-scale satellite-ground networks under the new macro paradigm of "maximizing linkage to the greatest extent feasible." Experimental cases involving up to 1,000 satellites and 100 ground stations highlight HLMP’s efficiency.Comparative experiments with other metaheuristic algorithms and the CPLEX solver further demonstrate HLMP’s ability to generate high-quality solutions more quickly.展开更多
Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation...Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.展开更多
In recent years,intensified environmental pollution and climate change have increasingly exposed the world to natural disasters such as earthquakes and floods,resulting in substantial economic losses[1].These disaster...In recent years,intensified environmental pollution and climate change have increasingly exposed the world to natural disasters such as earthquakes and floods,resulting in substantial economic losses[1].These disasters frequently damage terrestrial communication infrastructures,making the rapid deployment of emergency communication networks in affected areas critical in increasing rescue efficiency[2].展开更多
This paper proposes a novel algorithm, which can be used to model and analyzemesh tree hybrid power/ground distribution networks with multiple voltage supply in time domain.Not only this algorithm enhances common meth...This paper proposes a novel algorithm, which can be used to model and analyzemesh tree hybrid power/ground distribution networks with multiple voltage supply in time domain.Not only this algorithm enhances common method''s ability on analysis of power/ground network withirregular topology, but also very high accuracy it keeps. The accuracy and stability of thisalgorithm is proved using strict math method in this paper. Also, the usage of both preconditiontechnique based on Incomplete Choleskey Decomposition and fast variable elimination technique hasimproved the algorithm''s efficiency a lot. Experimental results show that it can finish the analysisof power/ground network with enormous, size within very short time. Also, this algorithm can beapplied to analyze the clock network, bus network, and signal network without buffer under highworking frequency because of the independence of the topology.展开更多
In this paper,a layer-constrained triangulated irregular network（ LC-TIN） algorithm is proposed for three-dimensional（ 3 D） modelling,and applied to construct a 3 D model for geological disease information based o...In this paper,a layer-constrained triangulated irregular network（ LC-TIN） algorithm is proposed for three-dimensional（ 3 D） modelling,and applied to construct a 3 D model for geological disease information based on ground penetrating radar（ GPR） data. Compared with the traditional TIN algorithm,the LCTIN algorithm introduced a layer constraint to the discrete data points during the 3 D modelling process,and it can dynamically construct networks from layer to layer and implement 3 D modelling for arbitrary shapes with high precision. The experimental results validated this method,the proposed algorithm not only can maintain the rationality of triangulation network,but also can obtain a good generation speed. In addition,the algorithm is also introduced to our self-developed 3 D visualization platform,which utilized GPR data to model geological diseases. Therefore the feasibility of the algorithm is verified in the practical application.展开更多
The spaceborne precipitation radar onboard the Tropical Rainfall Measuring Mission satellite （TRMM PR） can provide good measurement of the vertical structure of reflectivity, while ground radar （GR） has a relative...The spaceborne precipitation radar onboard the Tropical Rainfall Measuring Mission satellite （TRMM PR） can provide good measurement of the vertical structure of reflectivity, while ground radar （GR） has a relatively high horizontal resolution and greater sensitivity. Fusion of TRMM PR and GR reflectivity data may maximize the advantages from both instruments. In this paper, TRMM PR and GR reflectivity data are fused using a neural network （NN）-based approach. The main steps included are： quality control of TRMM PR and GR reflectivity data; spatiotemporal matchup; GR calibration bias correction; conversion of TRMM PR data from Ku to S band; fusion of TRMM PR and GR reflectivity data with an NN method： interpolation of reflectivity data that are below PR＇s sensitivity; blind areas compensation with a distance weighting-based merging approach; combination of three types of data： data with the NN method, data below PR＇s sensitivity and data within compensated blind areas. During the NN fusion step, the TRMM PR data are taken as targets of the training NNs, and gridded GR data after horizontal downsampling at different heights are used as the input. The trained NNs are then used to obtain 3D high-resolution reflectivity from the original GR gridded data. After 3D fusion of the TRMM PR and GR reflectivity data, a more complete and finer-scale 3D radar reflectivity dataset incorporating characteristics from both the TRMM PR and GR observations can be obtained. The fused reflectivity data are evaluated based on a convective precipitation event through comparison with the high resolution TRMM PR and GR data with an interpolation algorithm.展开更多
The neutral grounding mode of medium-voltage distribution network decides the reliability, overvoltage, relay protection and electrical safety. Therefore, a comprehensive consideration of the reliability, safety and e...The neutral grounding mode of medium-voltage distribution network decides the reliability, overvoltage, relay protection and electrical safety. Therefore, a comprehensive consideration of the reliability, safety and economy is particularly important for the decision of neutral grounding mode. This paper proposes a new decision method of neutral point grounding mode for mediumvoltage distribution network. The objective function is constructed for the decision according the life cycle cost. The reliability of the neutral point grounding mode is taken into account through treating the outage cost as an operating cost. The safety condition of the neutral point grounding mode is preserved as the constraint condition of decision models, so the decision method can generate the most economical and reliable scheme of neutral point grounding mode within a safe limit. The example is used to verify the feasibility and effectiveness of the decision method.展开更多
In the distribution network system with its neutral point grounding via arc suppression coil, when single-phase grounding fault occurred near zero-crossing point of the phase voltage, the inaccuracy of the line select...In the distribution network system with its neutral point grounding via arc suppression coil, when single-phase grounding fault occurred near zero-crossing point of the phase voltage, the inaccuracy of the line selection always existed in existing methods. According to the characteristics that transient current was different between the fault feeder and other faultless feeders, wavelet transformation was performed on data of the transient current within a power frequency cycle after the fault occurred. Based on different fault angles, wavelet energy in corresponding frequency band was chosen to compare. The result was that wavelet energy in fault feeder was the largest of all, and it was larger than sum of those in other faultless feeders, when the bus broke down, the disparity between each wavelet energy was not significant. Fault line could be selected out by the criterion above. The results of MATLAB/simulink simulation experiment indicated that this method had anti-interference capacity and was feasible.展开更多
Omnidirectional antennas are often used for radio frequency (RF) communication in wireless sensor networks (WSNs). Outside noise, electromagnetic interference (EMI), overloaded network traffic, large obstacles (vegeta...Omnidirectional antennas are often used for radio frequency (RF) communication in wireless sensor networks (WSNs). Outside noise, electromagnetic interference (EMI), overloaded network traffic, large obstacles (vegetation and buildings), terrain and atmospheric composition, along with climate patterns can degrade signal quality in the form of data packet loss or reduced RF communication range. This paper explores the RF range reduction properties of a particular WSN designed to operate in agricultural crop fields to collect aggregate data composed of subsurface soil moisture and soil temperature. Our study, using simulation, anechoic and field measurements shows that the effect of antenna placement close to the ground (within 10 cm) signi?cantly changes the omnidirectional transmission pattern. We then develop and propose a prediction method that is more precise than current practices of using the Friis and Fresnel equations. Our prediction method takes into account environmental properties for RF communication range based on the height of nodes and gateways.展开更多
With the rapid development of network language,more and more phenomena of Chinese/English Codeswitching appear in our daily communications.Codeswitching research of the network language is a new aspect in the linguist...With the rapid development of network language,more and more phenomena of Chinese/English Codeswitching appear in our daily communications.Codeswitching research of the network language is a new aspect in the linguistic field.The paper starts from cognitive perspective to discuss the process of Chinese/English Codeswitching by Figure/ground theory.展开更多
Application of the artificial neural network （ANN） to predict pseudospectral acceleration or peak ground acceleration is explored in the study. The training of ANN model is carried out using feed-forward backpropaga...Application of the artificial neural network （ANN） to predict pseudospectral acceleration or peak ground acceleration is explored in the study. The training of ANN model is carried out using feed-forward backpropagation method and about 600 records from 39 California earthquakes. The statistics of the residuals or modeling error for the trained ANN-based models are almost the same as those for the parametric ground motion prediction equations, derived through regression analysis; the residual or modeling error can be modeled as a normal variate. The similarity and differences between the predictions by these two approaches are shown. The trained ANN-based models, however, are not robust because the models with almost identical mean square errors do not always lead to the same predictions. This undesirable behaviour for predicting the ground motion measures has not been shown or discussed in the literature; the presented results, at least, serve to raise questions and caution on this problem. A practical approach to ameliorate this problem, perhaps, is to consider several trained ANN models, and to take the average of the predicted values from the trained ANN models as the predicted ground motion measure.展开更多
Wheeled mobile robots(WMRs) encounter unavoidable slippage especially on the low adhesion terrain such that the robots stability and accuracy are reduced greatly.To overcome this drawback,this article presents a neura...Wheeled mobile robots(WMRs) encounter unavoidable slippage especially on the low adhesion terrain such that the robots stability and accuracy are reduced greatly.To overcome this drawback,this article presents a neural network(NN) based terminal sliding mode control(TSMC) for WMRs where an augmented ground friction model is reported by which the uncertain friction can be estimated and compensated according to the required performance.In contrast to the existing friction models,the developed augmented ground friction model corresponds to actual fact because not only the effects associated with the mobile platform velocity but also the slippage related to the wheel slip rate are concerned simultaneously.Besides,the presented control approach can combine the merits of both TSMC and radial basis function(RBF) neural networks techniques,thereby providing numerous excellent performances for the closed-loop system,such as finite time convergence and faster friction estimation property.Simulation results validate the proposed friction model and robustness of controller;these research results will improve the autonomy and intelligence of WMRs,particularly when the mobile platform suffers from the sophisticated unstructured environment.展开更多
A gait control method for a biped robot based on the deep Q-network (DQN) algorithm is proposed to enhance the stability of walking on uneven ground. This control strategy is an intelligent learning method of posture ...A gait control method for a biped robot based on the deep Q-network (DQN) algorithm is proposed to enhance the stability of walking on uneven ground. This control strategy is an intelligent learning method of posture adjustment. A robot is taken as an agent and trained to walk steadily on an uneven surface with obstacles, using a simple reward function based on forward progress. The reward-punishment (RP) mechanism of the DQN algorithm is established after obtaining the offline gait which was generated in advance foot trajectory planning. Instead of implementing a complex dynamic model, the proposed method enables the biped robot to learn to adjust its posture on the uneven ground and ensures walking stability. The performance and effectiveness of the proposed algorithm was validated in the V-REP simulation environment. The results demonstrate that the biped robot's lateral tile angle is less than 3° after implementing the proposed method and the walking stability is obviously improved.展开更多
随着第六代移动通信系统(6th generation mobile communication system, 6G)通信技术的发展,空天地一体化网络(Spaceair-ground integrated network, SAGIN)作为6G的重要组成部分,旨在实现卫星、空中平台与地面系统的无缝互联,在应急通...随着第六代移动通信系统(6th generation mobile communication system, 6G)通信技术的发展,空天地一体化网络(Spaceair-ground integrated network, SAGIN)作为6G的重要组成部分,旨在实现卫星、空中平台与地面系统的无缝互联,在应急通信、环境监测、智能交通等领域展现出巨大的潜力.然而,SAGIN具有异构结构、链路动态性高、资源分布广泛等特征,给网络的高效管理与优化带来巨大的挑战.近年来,人工智能(Artificial intelligence, AI)技术凭借强大的感知、学习与自主决策能力应用于通信网络,为SAGIN的智能演进提供了新契机.本文首先系统介绍SAGIN网络架构的基本组成与关键特征,并梳理当前主流AI技术在网络优化中的主要技术体系与适配优势,包括机器学习、图神经网络以及强化学习.其次,本文深入探讨了AI技术在SAGIN中智能资源管理、移动性管理与路由优化、空中平台路径规划、任务卸载与计算协同等典型场景中的应用与最新进展.最后,本文总结了AI技术应用在SAGIN网络中面临的挑战并展望了AI与SAGIN融合发展的未来方向.本文概述了AI技术在SAGIN网络中应用的优势与进展,旨在为AI赋能的SAGIN研究与应用发展提供技术参考.展开更多
A new form of producing and sharing knowledge has emerged as an international(United States of America,Asia,and Europe) research collaboration,known as the Long-Term Ecological Research(LTER) Network.Although Africa b...A new form of producing and sharing knowledge has emerged as an international(United States of America,Asia,and Europe) research collaboration,known as the Long-Term Ecological Research(LTER) Network.Although Africa boasts rich biodiversity,including endemic species,it lacks the long-term initiatives to underpin sustainable biodiversity managements.At present,climate change may exacerbate hunger and poverty concerns in addition to resulting in ecosystem degradation,land use change,and other threats in Africa.Therefore,ecosystem monitoring was suggested to understanding the effects of climate change and setting strategies to mitigate these changes.This paper aimed to investigate ecosystem monitoring ground sites and address their coverage gaps in Africa to provide a foundation for optimizing the African Ecosystem Research Network(AERN) ground sites.The geographic coordinates and characteristics of ground sites-based ecosystem monitoring were collected from various networks aligned with the LTER implementation in Africa.Additionally,climatic data and biodiversity distribution maps were retrieved from various sources.These data were used to assess the size of existing ground sites and the gaps in description,ecosystems and biomes.The results reveal that there were 1089 sites established by various networks.Among these sites,30.5%,27.5%,and 28.8% had no information of area,year of establishment,current status,respectively.However,68.0% of them had an area equal to or greater than 1 km2.Sites were created progressively over the course of the years,with 68.9% being created from 2000 to 2005.To date,only 41.5% of the sites were operational.The sites were scattered across Africa,but they were concentrated in Eastern and Southern Africa.The unbalanced distribution pattern of the sites left Central and Northern Africa hardly covered,and many unique ecosystems in Central Africa were not included.To sustain these sites,the AERN should be based on operational sites,seeking secure funding by establishing multiple partnerships.展开更多
Rolling dynamic compaction(RDC),which involves the towing of a noncircular module,is now widespread and accepted among many other soil compaction methods.However,to date,there is no accurate method for reliable predic...Rolling dynamic compaction(RDC),which involves the towing of a noncircular module,is now widespread and accepted among many other soil compaction methods.However,to date,there is no accurate method for reliable prediction of the densification of soil and the extent of ground improvement by means of RDC.This study presents the application of artificial neural networks(ANNs) for a priori prediction of the effectiveness of RDC.The models are trained with in situ dynamic cone penetration(DCP) test data obtained from previous civil projects associated with the 4-sided impact roller.The predictions from the ANN models are in good agreement with the measured field data,as indicated by the model correlation coefficient of approximately 0.8.It is concluded that the ANN models developed in this study can be successfully employed to provide more accurate prediction of the performance of the RDC on a range of soil types.展开更多
文摘This paper presents an efficient algorithm for reducing RLC power/ground network complexities by exploitation of the regularities in the power/ground networks. The new method first builds the equivalent models for many series RLC-current chains based on their Norton＇s form companion models in the original networks,and then the precondition conjugate gradient based iterative method is used to solve the reduced networks,which are symmetric positive definite. The solutions of the original networks are then back solved from those of the reduced networks.Experimental results show that the complexities of reduced networks are typically significantly smaller than those of the original circuits, which makes the new algorithm extremely fast. For instance, power/ground networks with more than one million branches can be solved in a few minutes on modern Sun workstations.
文摘A CAD tool based on a group of efficient algorithms to verify,design,and optimize power/ground networks for standard cell model is presented.Nonlinear programming techniques,branch and bound algorithms and incomplete Cholesky decomposition conjugate gradient method (ICCG) are the three main parts of our work.Users can choose nonlinear programming method or branch and bound algorithm to satisfy their different requirements of precision and speed.The experimental results prove that the algorithms can run very fast with lower wiring resources consumption.As a result,the CAD tool based on these algorithms is able to cope with large-scale circuits.
基金supported by the National Natural Science Foundation of China(Grant Nos.61072067 and 61372076)the 111 Project(Grant No.B08038)+1 种基金the Fund from the State Key Laboratory of Integrated Services Networks(Grant No.ISN 1001004)the Fundamental Research Funds for the Central Universities(Grant Nos.K5051301059 and K5051201021)
文摘To realize practical wide-area quantum communication,a satellite-to-ground network with partially entangled states is developed in this paper.For efficiency and security reasons,the existing method of quantum communication in distributed wireless quantum networks with partially entangled states cannot be applied directly to the proposed quantum network.Based on this point,an efficient and secure quantum communication scheme with partially entangled states is presented.In our scheme,the source node performs teleportation only after an end-to-end entangled state has been established by entanglement swapping with partially entangled states.Thus,the security of quantum communication is guaranteed.The destination node recovers the transmitted quantum bit with the help of an auxiliary quantum bit and specially defined unitary matrices.Detailed calculations and simulation analyses show that the probability of successfully transferring a quantum bit in the presented scheme is high.In addition,the auxiliary quantum bit provides a heralded mechanism for successful communication.Based on the critical components that are presented in this article an efficient,secure,and practical wide-area quantum communication can be achieved.
基金supported by the National Natural Science Foundation of China(Grant Nos.72201272 and U23B2039)the National Fundamental Research Project,China(Grant No.2023-JCJQ-QT-042)the Science Foundation of National University of Defense Technology,China(Grant No.ZK22-48).
文摘The rapid expansion of satellite Internet deployments,driven by the rise of Space-Ground Integration Network (SGIN) construction,has led to a significant increase in satellite numbers.To address the challenge of efficient networking between large-scale satellites and limited ground station resources,this paper presents a hybrid learning-assisted multi-parallel algorithm (HLMP).The HLMP features a multi-parallel solving and deconflicting framework,a learning-assisted metaheuristic (LM) algorithm combining reinforcement learning (RL) and Tabu simulated annealing (TSA),and a linear programming (LP) exact-solving algorithm.The framework first divides the problem into parallel sub-problems based on the time domain,then applies LM and LP to solve each sub-problem in parallel.LM uses LP-generated scheduling results to improve its own accuracy.The deconflicting strategy integrates and refines the planning results from all sub-problems,ensuring an optimized outcome.HLMP advances beyond traditional task-driven satellite scheduling methods by offering a novel approach for optimizing large-scale satellite-ground networks under the new macro paradigm of "maximizing linkage to the greatest extent feasible." Experimental cases involving up to 1,000 satellites and 100 ground stations highlight HLMP’s efficiency.Comparative experiments with other metaheuristic algorithms and the CPLEX solver further demonstrate HLMP’s ability to generate high-quality solutions more quickly.
基金supported by the National Natural Science Foundation of China[grant number 42175132]the National Key R&D Program[grant number 2020YFA0607802]the CAS Information Technology Program[grant number CAS-WX2021SF-0107-02]。
文摘Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.
基金supported in part by the National Natural Science Foundation of China(U2441226).
文摘In recent years,intensified environmental pollution and climate change have increasingly exposed the world to natural disasters such as earthquakes and floods,resulting in substantial economic losses[1].These disasters frequently damage terrestrial communication infrastructures,making the rapid deployment of emergency communication networks in affected areas critical in increasing rescue efficiency[2].
文摘This paper proposes a novel algorithm, which can be used to model and analyzemesh tree hybrid power/ground distribution networks with multiple voltage supply in time domain.Not only this algorithm enhances common method''s ability on analysis of power/ground network withirregular topology, but also very high accuracy it keeps. The accuracy and stability of thisalgorithm is proved using strict math method in this paper. Also, the usage of both preconditiontechnique based on Incomplete Choleskey Decomposition and fast variable elimination technique hasimproved the algorithm''s efficiency a lot. Experimental results show that it can finish the analysisof power/ground network with enormous, size within very short time. Also, this algorithm can beapplied to analyze the clock network, bus network, and signal network without buffer under highworking frequency because of the independence of the topology.
基金Supported by the National Science Foundation of China(61302157)the National High Technology Research and Development Program of China(863 Program)(2012AA12A308)the Yue Qi Young Scholars Project of China University of Mining&Technology(Beijing)(800015Z1117)
文摘In this paper,a layer-constrained triangulated irregular network（ LC-TIN） algorithm is proposed for three-dimensional（ 3 D） modelling,and applied to construct a 3 D model for geological disease information based on ground penetrating radar（ GPR） data. Compared with the traditional TIN algorithm,the LCTIN algorithm introduced a layer constraint to the discrete data points during the 3 D modelling process,and it can dynamically construct networks from layer to layer and implement 3 D modelling for arbitrary shapes with high precision. The experimental results validated this method,the proposed algorithm not only can maintain the rationality of triangulation network,but also can obtain a good generation speed. In addition,the algorithm is also introduced to our self-developed 3 D visualization platform,which utilized GPR data to model geological diseases. Therefore the feasibility of the algorithm is verified in the practical application.
基金supported by funding from the Natural Science Foundation of Jiangsu Province (Grant No. BK20171457)the 2013 Special Fund for Meteorological Scientific Research in the Public Interest (Grant No. GYHY201306078)+1 种基金the National Natural Science Foundation of China (Grant No. 41301399)Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
文摘The spaceborne precipitation radar onboard the Tropical Rainfall Measuring Mission satellite （TRMM PR） can provide good measurement of the vertical structure of reflectivity, while ground radar （GR） has a relatively high horizontal resolution and greater sensitivity. Fusion of TRMM PR and GR reflectivity data may maximize the advantages from both instruments. In this paper, TRMM PR and GR reflectivity data are fused using a neural network （NN）-based approach. The main steps included are： quality control of TRMM PR and GR reflectivity data; spatiotemporal matchup; GR calibration bias correction; conversion of TRMM PR data from Ku to S band; fusion of TRMM PR and GR reflectivity data with an NN method： interpolation of reflectivity data that are below PR＇s sensitivity; blind areas compensation with a distance weighting-based merging approach; combination of three types of data： data with the NN method, data below PR＇s sensitivity and data within compensated blind areas. During the NN fusion step, the TRMM PR data are taken as targets of the training NNs, and gridded GR data after horizontal downsampling at different heights are used as the input. The trained NNs are then used to obtain 3D high-resolution reflectivity from the original GR gridded data. After 3D fusion of the TRMM PR and GR reflectivity data, a more complete and finer-scale 3D radar reflectivity dataset incorporating characteristics from both the TRMM PR and GR observations can be obtained. The fused reflectivity data are evaluated based on a convective precipitation event through comparison with the high resolution TRMM PR and GR data with an interpolation algorithm.
文摘The neutral grounding mode of medium-voltage distribution network decides the reliability, overvoltage, relay protection and electrical safety. Therefore, a comprehensive consideration of the reliability, safety and economy is particularly important for the decision of neutral grounding mode. This paper proposes a new decision method of neutral point grounding mode for mediumvoltage distribution network. The objective function is constructed for the decision according the life cycle cost. The reliability of the neutral point grounding mode is taken into account through treating the outage cost as an operating cost. The safety condition of the neutral point grounding mode is preserved as the constraint condition of decision models, so the decision method can generate the most economical and reliable scheme of neutral point grounding mode within a safe limit. The example is used to verify the feasibility and effectiveness of the decision method.
文摘In the distribution network system with its neutral point grounding via arc suppression coil, when single-phase grounding fault occurred near zero-crossing point of the phase voltage, the inaccuracy of the line selection always existed in existing methods. According to the characteristics that transient current was different between the fault feeder and other faultless feeders, wavelet transformation was performed on data of the transient current within a power frequency cycle after the fault occurred. Based on different fault angles, wavelet energy in corresponding frequency band was chosen to compare. The result was that wavelet energy in fault feeder was the largest of all, and it was larger than sum of those in other faultless feeders, when the bus broke down, the disparity between each wavelet energy was not significant. Fault line could be selected out by the criterion above. The results of MATLAB/simulink simulation experiment indicated that this method had anti-interference capacity and was feasible.
文摘Omnidirectional antennas are often used for radio frequency (RF) communication in wireless sensor networks (WSNs). Outside noise, electromagnetic interference (EMI), overloaded network traffic, large obstacles (vegetation and buildings), terrain and atmospheric composition, along with climate patterns can degrade signal quality in the form of data packet loss or reduced RF communication range. This paper explores the RF range reduction properties of a particular WSN designed to operate in agricultural crop fields to collect aggregate data composed of subsurface soil moisture and soil temperature. Our study, using simulation, anechoic and field measurements shows that the effect of antenna placement close to the ground (within 10 cm) signi?cantly changes the omnidirectional transmission pattern. We then develop and propose a prediction method that is more precise than current practices of using the Friis and Fresnel equations. Our prediction method takes into account environmental properties for RF communication range based on the height of nodes and gateways.
文摘With the rapid development of network language,more and more phenomena of Chinese/English Codeswitching appear in our daily communications.Codeswitching research of the network language is a new aspect in the linguistic field.The paper starts from cognitive perspective to discuss the process of Chinese/English Codeswitching by Figure/ground theory.
基金The financial support received from the Natural Science and Engineering Research Council of Canadathe University of Western Ontario
文摘Application of the artificial neural network （ANN） to predict pseudospectral acceleration or peak ground acceleration is explored in the study. The training of ANN model is carried out using feed-forward backpropagation method and about 600 records from 39 California earthquakes. The statistics of the residuals or modeling error for the trained ANN-based models are almost the same as those for the parametric ground motion prediction equations, derived through regression analysis; the residual or modeling error can be modeled as a normal variate. The similarity and differences between the predictions by these two approaches are shown. The trained ANN-based models, however, are not robust because the models with almost identical mean square errors do not always lead to the same predictions. This undesirable behaviour for predicting the ground motion measures has not been shown or discussed in the literature; the presented results, at least, serve to raise questions and caution on this problem. A practical approach to ameliorate this problem, perhaps, is to consider several trained ANN models, and to take the average of the predicted values from the trained ANN models as the predicted ground motion measure.
基金supported by the National Natural Science Foundation of China(61573078,61573147)the International S&T Cooperation Program of China(2014DFB70120)the State Key Laboratory of Robotics and System(SKLRS2015ZD06)
文摘Wheeled mobile robots(WMRs) encounter unavoidable slippage especially on the low adhesion terrain such that the robots stability and accuracy are reduced greatly.To overcome this drawback,this article presents a neural network(NN) based terminal sliding mode control(TSMC) for WMRs where an augmented ground friction model is reported by which the uncertain friction can be estimated and compensated according to the required performance.In contrast to the existing friction models,the developed augmented ground friction model corresponds to actual fact because not only the effects associated with the mobile platform velocity but also the slippage related to the wheel slip rate are concerned simultaneously.Besides,the presented control approach can combine the merits of both TSMC and radial basis function(RBF) neural networks techniques,thereby providing numerous excellent performances for the closed-loop system,such as finite time convergence and faster friction estimation property.Simulation results validate the proposed friction model and robustness of controller;these research results will improve the autonomy and intelligence of WMRs,particularly when the mobile platform suffers from the sophisticated unstructured environment.
基金Supported by the National Ministries and Research Funds(3020020221111)
文摘A gait control method for a biped robot based on the deep Q-network (DQN) algorithm is proposed to enhance the stability of walking on uneven ground. This control strategy is an intelligent learning method of posture adjustment. A robot is taken as an agent and trained to walk steadily on an uneven surface with obstacles, using a simple reward function based on forward progress. The reward-punishment (RP) mechanism of the DQN algorithm is established after obtaining the offline gait which was generated in advance foot trajectory planning. Instead of implementing a complex dynamic model, the proposed method enables the biped robot to learn to adjust its posture on the uneven ground and ensures walking stability. The performance and effectiveness of the proposed algorithm was validated in the V-REP simulation environment. The results demonstrate that the biped robot's lateral tile angle is less than 3° after implementing the proposed method and the walking stability is obviously improved.
基金Under the auspices of National Natural Science Foundation of China(No.31161140355)
文摘A new form of producing and sharing knowledge has emerged as an international(United States of America,Asia,and Europe) research collaboration,known as the Long-Term Ecological Research(LTER) Network.Although Africa boasts rich biodiversity,including endemic species,it lacks the long-term initiatives to underpin sustainable biodiversity managements.At present,climate change may exacerbate hunger and poverty concerns in addition to resulting in ecosystem degradation,land use change,and other threats in Africa.Therefore,ecosystem monitoring was suggested to understanding the effects of climate change and setting strategies to mitigate these changes.This paper aimed to investigate ecosystem monitoring ground sites and address their coverage gaps in Africa to provide a foundation for optimizing the African Ecosystem Research Network(AERN) ground sites.The geographic coordinates and characteristics of ground sites-based ecosystem monitoring were collected from various networks aligned with the LTER implementation in Africa.Additionally,climatic data and biodiversity distribution maps were retrieved from various sources.These data were used to assess the size of existing ground sites and the gaps in description,ecosystems and biomes.The results reveal that there were 1089 sites established by various networks.Among these sites,30.5%,27.5%,and 28.8% had no information of area,year of establishment,current status,respectively.However,68.0% of them had an area equal to or greater than 1 km2.Sites were created progressively over the course of the years,with 68.9% being created from 2000 to 2005.To date,only 41.5% of the sites were operational.The sites were scattered across Africa,but they were concentrated in Eastern and Southern Africa.The unbalanced distribution pattern of the sites left Central and Northern Africa hardly covered,and many unique ecosystems in Central Africa were not included.To sustain these sites,the AERN should be based on operational sites,seeking secure funding by establishing multiple partnerships.
基金supported under Australian Research Council's Discovery Projects funding scheme(project No.DP120101761)
文摘Rolling dynamic compaction(RDC),which involves the towing of a noncircular module,is now widespread and accepted among many other soil compaction methods.However,to date,there is no accurate method for reliable prediction of the densification of soil and the extent of ground improvement by means of RDC.This study presents the application of artificial neural networks(ANNs) for a priori prediction of the effectiveness of RDC.The models are trained with in situ dynamic cone penetration(DCP) test data obtained from previous civil projects associated with the 4-sided impact roller.The predictions from the ANN models are in good agreement with the measured field data,as indicated by the model correlation coefficient of approximately 0.8.It is concluded that the ANN models developed in this study can be successfully employed to provide more accurate prediction of the performance of the RDC on a range of soil types.
