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Carbon Emission Factors Prediction of Power Grid by Using Graph Attention Network
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作者 Xin Shen Jiahao Li +3 位作者 YujunYin Jianlin Tang Weibin Lin Mi Zhou 《Energy Engineering》 EI 2024年第7期1945-1961,共17页
Advanced carbon emission factors of a power grid can provide users with effective carbon reduction advice,which is of immense importance in mobilizing the entire society to reduce carbon emissions.The method of calcul... Advanced carbon emission factors of a power grid can provide users with effective carbon reduction advice,which is of immense importance in mobilizing the entire society to reduce carbon emissions.The method of calculating node carbon emission factors based on the carbon emissions flow theory requires real-time parameters of a power grid.Therefore,it cannot provide carbon factor information beforehand.To address this issue,a prediction model based on the graph attention network is proposed.The model uses a graph structure that is suitable for the topology of the power grid and designs a supervised network using the loads of the grid nodes and the corresponding carbon factor data.The network extracts features and transmits information more suitable for the power system and can flexibly adjust the equivalent topology,thereby increasing the diversity of the structure.Its input and output data are simple,without the power grid parameters.We demonstrated its effect by testing IEEE-39 bus and IEEE-118 bus systems with average error rates of 2.46%and 2.51%. 展开更多
关键词 Predict carbon factors graph attention network prediction algorithm power grid operating parameters
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The Short-Term Prediction ofWind Power Based on the Convolutional Graph Attention Deep Neural Network
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作者 Fan Xiao Xiong Ping +4 位作者 Yeyang Li Yusen Xu Yiqun Kang Dan Liu Nianming Zhang 《Energy Engineering》 EI 2024年第2期359-376,共18页
The fluctuation of wind power affects the operating safety and power consumption of the electric power grid and restricts the grid connection of wind power on a large scale.Therefore,wind power forecasting plays a key... The fluctuation of wind power affects the operating safety and power consumption of the electric power grid and restricts the grid connection of wind power on a large scale.Therefore,wind power forecasting plays a key role in improving the safety and economic benefits of the power grid.This paper proposes a wind power predicting method based on a convolutional graph attention deep neural network with multi-wind farm data.Based on the graph attention network and attention mechanism,the method extracts spatial-temporal characteristics from the data of multiple wind farms.Then,combined with a deep neural network,a convolutional graph attention deep neural network model is constructed.Finally,the model is trained with the quantile regression loss function to achieve the wind power deterministic and probabilistic prediction based on multi-wind farm spatial-temporal data.A wind power dataset in the U.S.is taken as an example to demonstrate the efficacy of the proposed model.Compared with the selected baseline methods,the proposed model achieves the best prediction performance.The point prediction errors(i.e.,root mean square error(RMSE)and normalized mean absolute percentage error(NMAPE))are 0.304 MW and 1.177%,respectively.And the comprehensive performance of probabilistic prediction(i.e.,con-tinuously ranked probability score(CRPS))is 0.580.Thus,the significance of multi-wind farm data and spatial-temporal feature extraction module is self-evident. 展开更多
关键词 Format wind power prediction deep neural network graph attention network attention mechanism quantile regression
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INDEPENDENT-SET-DELETABLE FACTOR-CRITICAL POWER GRAPHS 被引量:6
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作者 原晋江 《Acta Mathematica Scientia》 SCIE CSCD 2006年第4期577-584,共8页
It is said that a graph G is independent-set-deletable factor-critical (in short, ID-factor-critical), if, for everyindependent-set I which has the same parity as |V(G)|, G - I has a perfect matching. A graph G ... It is said that a graph G is independent-set-deletable factor-critical (in short, ID-factor-critical), if, for everyindependent-set I which has the same parity as |V(G)|, G - I has a perfect matching. A graph G is strongly IM-extendable, if for every spanning supergraph H of G, every induced matching of H is included in a perfect matching of H. The κ-th power of G, denoted by G^κ, is the graph with vertex set V(G) in which two vertices are adjacent if and only if they have distance at most k in G. ID-factor-criticality and IM-extendability of power graphs are discussed in this article. The author shows that, if G is a connected graph, then G^3 and T(G) (the total graph of G) are ID-factor-critical, and G^4 (when |V(G)| is even) is strongly IM-extendable; if G is 2-connected, then D^2 is ID-factor-critical. 展开更多
关键词 Independent set perfect matching induced matching ID-factor-critical IM-extendable power of a graph
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Optimization of a dynamic uncertain causality graph for fault diagnosis in nuclear power plant 被引量:2
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作者 Yue Zhao Francesco Di Maio +3 位作者 Enrico Zio Qin Zhang Chun-Ling Dong Jin-Ying Zhang 《Nuclear Science and Techniques》 SCIE CAS CSCD 2017年第3期59-67,共9页
Fault diagnostics is important for safe operation of nuclear power plants(NPPs). In recent years, data-driven approaches have been proposed and implemented to tackle the problem, e.g., neural networks, fuzzy and neuro... Fault diagnostics is important for safe operation of nuclear power plants(NPPs). In recent years, data-driven approaches have been proposed and implemented to tackle the problem, e.g., neural networks, fuzzy and neurofuzzy approaches, support vector machine, K-nearest neighbor classifiers and inference methodologies. Among these methods, dynamic uncertain causality graph(DUCG)has been proved effective in many practical cases. However, the causal graph construction behind the DUCG is complicate and, in many cases, results redundant on the symptoms needed to correctly classify the fault. In this paper, we propose a method to simplify causal graph construction in an automatic way. The method consists in transforming the expert knowledge-based DCUG into a fuzzy decision tree(FDT) by extracting from the DUCG a fuzzy rule base that resumes the used symptoms at the basis of the FDT. Genetic algorithm(GA) is, then, used for the optimization of the FDT, by performing a wrapper search around the FDT: the set of symptoms selected during the iterative search are taken as the best set of symptoms for the diagnosis of the faults that can occur in the system. The effectiveness of the approach is shown with respect to a DUCG model initially built to diagnose 23 faults originally using 262 symptoms of Unit-1 in the Ningde NPP of the China Guangdong Nuclear Power Corporation. The results show that the FDT, with GA-optimized symptoms and diagnosis strategy, can drive the construction of DUCG and lower the computational burden without loss of accuracy in diagnosis. 展开更多
关键词 DYNAMIC UNCERTAIN CAUSALITY graph Fault diagnosis Classification Fuzzy DECISION tree GENETIC algorithm Nuclear power plant
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Collective Entity Alignment for Knowledge Fusion of Power Grid Dispatching Knowledge Graphs 被引量:6
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作者 Linyao Yang Chen Lv +4 位作者 Xiao Wang Ji Qiao Weiping Ding Jun Zhang Fei-Yue Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2022年第11期1990-2004,共15页
Knowledge graphs(KGs)have been widely accepted as powerful tools for modeling the complex relationships between concepts and developing knowledge-based services.In recent years,researchers in the field of power system... Knowledge graphs(KGs)have been widely accepted as powerful tools for modeling the complex relationships between concepts and developing knowledge-based services.In recent years,researchers in the field of power systems have explored KGs to develop intelligent dispatching systems for increasingly large power grids.With multiple power grid dispatching knowledge graphs(PDKGs)constructed by different agencies,the knowledge fusion of different PDKGs is useful for providing more accurate decision supports.To achieve this,entity alignment that aims at connecting different KGs by identifying equivalent entities is a critical step.Existing entity alignment methods cannot integrate useful structural,attribute,and relational information while calculating entities’similarities and are prone to making many-to-one alignments,thus can hardly achieve the best performance.To address these issues,this paper proposes a collective entity alignment model that integrates three kinds of available information and makes collective counterpart assignments.This model proposes a novel knowledge graph attention network(KGAT)to learn the embeddings of entities and relations explicitly and calculates entities’similarities by adaptively incorporating the structural,attribute,and relational similarities.Then,we formulate the counterpart assignment task as an integer programming(IP)problem to obtain one-to-one alignments.We not only conduct experiments on a pair of PDKGs but also evaluate o ur model on three commonly used cross-lingual KGs.Experimental comparisons indicate that our model outperforms other methods and provides an effective tool for the knowledge fusion of PDKGs. 展开更多
关键词 Entity alignment integer programming(IP) knowledge fusion knowledge graph embedding power dispatch
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Accurate querying of frequent subgraphs in power grid graph data 被引量:2
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作者 Aihua Zhou Lipeng Zhu +1 位作者 Xinxin Wu Hongbin Qiu 《Global Energy Interconnection》 2019年第1期78-84,共7页
With the development of information technology, the amount of power grid topology data has gradually increased. Therefore, accurate querying of this data has become particularly important. Several researchers have cho... With the development of information technology, the amount of power grid topology data has gradually increased. Therefore, accurate querying of this data has become particularly important. Several researchers have chosen different indexing methods in the filtering stage to obtain more optimized query results because currently there is no uniform and efficient indexing mechanism that achieves good query results. In the traditional algorithm, the hash table for index storage is prone to "collision" problems, which decrease the index construction efficiency. Aiming at the problem of quick index entry, based on the construction of frequent subgraph indexes, a method of serialized storage optimization based on multiple hash tables is proposed. This method mainly uses the exploration sequence to make the keywords evenly distributed; it avoids conflicts of the stored procedure and performs a quick search of the index. The proposed algorithm mainly adopts the "filterverify" mechanism; in the filtering stage, the index is first established offline, and then the frequent subgraphs are found using the "contains logic" rule to obtain the candidate set. Experimental results show that this method can reduce the time and scale of candidate set generation and improve query efficiency. 展开更多
关键词 power grid graph database graph computing Multi-Hash TABLE Frequent SUBgraphS
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Power domination in planar graphs with small diameter 被引量:1
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作者 赵敏 康丽英 《Journal of Shanghai University(English Edition)》 CAS 2007年第3期218-222,共5页
The problem of monitoring an electric power system by placing as few measurement devices in the system as possible is closely related to the well-known vertex covering and dominating set problems in graph theory. In t... The problem of monitoring an electric power system by placing as few measurement devices in the system as possible is closely related to the well-known vertex covering and dominating set problems in graph theory. In this paper, it was shown that the power domination number of an outerplanar graph with the diameter two or a 2-connected outerplanar graph with the diameter three is precisely one. Upper bounds on the power domination number for a general planar graph with the diameter two or three were determined as an immediate consequences of results proven by Dorfling, et al. Also, an infinite family of outerplanar graphs with the diameter four having arbitrarily large power domination numbers were given. 展开更多
关键词 graph power domination planar graph outerplanar graph
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Enhanced graph-based fault diagnostic system for nuclear power plants 被引量:1
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作者 Yong-Kuo Liu Xin Ai +4 位作者 Abiodun Ayodeji Mao-Pu Wu Min-Jun Peng Hong Xia Wei-Feng Yu 《Nuclear Science and Techniques》 SCIE CAS CSCD 2019年第12期8-21,共14页
Scheduled maintenance and condition-based online monitoring are among the focal points of recent research to enhance nuclear plant safety.One of the most effective ways to monitor plant conditions is by implementing a... Scheduled maintenance and condition-based online monitoring are among the focal points of recent research to enhance nuclear plant safety.One of the most effective ways to monitor plant conditions is by implementing a full-scope,plant-wide fault diagnostic system.However,most of the proposed diagnostic techniques are perceived as unreliable by operators because they lack an explanation module,their implementation is complex,and their decision/inference path is unclear.Graphical formalism has been considered for fault diagnosis because of its clear decision and inference modules,and its ability to display the complex causal relationships between plant variables and reveal the propagation path used for fault localization in complex systems.However,in a graphbased approach,decision-making is slow because of rule explosion.In this paper,we present an enhanced signed directed graph that utilizes qualitative trend evaluation and a granular computing algorithm to improve the decision speed and increase the resolution of the graphical method.We integrate the attribute reduction capability of granular computing with the causal/fault propagation reasoning capability of the signed directed graph and comprehensive rules in a decision table to diagnose faults in a nuclear power plant.Qualitative trend analysis is used to solve the problems of fault diagnostic threshold selection and signed directed graph node state determination.The similarity reasoning and detection ability of the granular computing algorithm ensure a compact decision table and improve the decision result.The performance of the proposed enhanced system was evaluated on selected faults of the Chinese Fuqing 2 nuclear reactor.The proposed method offers improved diagnostic speed and efficient data processing.In addition,the result shows a considerable reduction in false positives,indicating that the method provides a reliable diagnostic system to support further intervention by operators. 展开更多
关键词 NUCLEAR power plants FAULT diagnosis SIGNED directed graph DECISION TABLE GRANULAR computing
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Massive Power Device Condition Monitoring Data Feature Extraction and Clustering Analysis using MapReduce and Graph Model 被引量:4
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作者 Hongtao Shen Peng Tao +1 位作者 Pei Zhao Hao Ma 《CES Transactions on Electrical Machines and Systems》 CSCD 2019年第2期221-230,共10页
Effective storage,processing and analyzing of power device condition monitoring data faces enormous challenges.A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at ... Effective storage,processing and analyzing of power device condition monitoring data faces enormous challenges.A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at the same time based on Aliyun DTplus platform.First,power device condition monitoring data storage based on MaxCompute table and parallel permutation entropy feature extraction based on MaxCompute MapReduce are designed and implemented on DTplus platform.Then,Graph based k-means algorithm is implemented and used for massive condition monitoring data clustering analysis.Finally,performance tests are performed to compare the execution time between serial program and parallel program.Performance is analyzed from CPU cores consumption,memory utilization and parallel granularity.Experimental results show that the designed framework and parallel algorithms can efficiently process massive power device condition monitoring data. 展开更多
关键词 Clustering analysis graph feature extraction MAPREDUCE maxcompute power device condition monitoring.
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Towards sparse matrix operations:graph database approach for power grid computation
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作者 Daoxing Li Kai Xiao +2 位作者 Xiaohui Wang Pengtian Guo Yong Chen 《Global Energy Interconnection》 EI CAS CSCD 2023年第1期50-63,共14页
The construction of new power systems presents higher requirements for the Power Internet of Things(PIoT)technology.The“source-grid-load-storage”architecture of a new power system requires PIoT to have a stronger mu... The construction of new power systems presents higher requirements for the Power Internet of Things(PIoT)technology.The“source-grid-load-storage”architecture of a new power system requires PIoT to have a stronger multi-source heterogeneous data fusion ability.Native graph databases have great advantages in dealing with multi-source heterogeneous data,which make them suitable for an increasing number of analytical computing tasks.However,only few existing graph database products have native support for matrix operation-related interfaces or functions,resulting in low efficiency when handling matrix calculations that are commonly encountered in power grids.In this paper,the matrix computation process is expressed by a strategy called graph description,which relies on the natural connection between the matrix and structure of the graph.Based on that,we implement matrix operations on graph database,including matrix multiplication,matrix decomposition,etc.Specifically,only the nodes relevant to the computation and their neighbors are concerned in the process,which prunes the influence of zero elements in the matrix and avoids useless iterations compared to the conventional matrix computation.Based on the graph description,a series of power grid computations can be implemented on graph database,which reduces redundant data import and export operations while leveraging the parallel computing capability of graph database.It promotes the efficiency of PIoT when handling multi-source heterogeneous data.An comprehensive experimental study over two different scale power system datasets compares the proposed method with Python and MATLAB baselines.The results reveal the superior performance of our proposed method in both power flow and N-1 contingency computations. 展开更多
关键词 graph database graph description MATRIX Parallel computing power flow
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Minimum Rank of Graphs Powers Family
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作者 Alimohammad M. Nazari Marzieh Karimi Radpoor 《Open Journal of Discrete Mathematics》 2012年第2期65-69,共5页
In this paper we study the relationship between minimum rank of graph G and the minimum rank of graph for some families of special graph G, where is the jth power of graph G.
关键词 Minimum RANK power of graphS ZERO FORCING Set
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Optimal power allocation for complex field network coding scheme with the K-th best relay selection
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作者 Xi CAI Pingzhi FAN Qingchun CHEN 《Journal of Modern Transportation》 2012年第4期255-260,共6页
Wireless relay and network coding are two critical techniques to increase the reliability and throughput of wireless cooperative communication systems. In this paper, a complex field network coding (CFNC) scheme wit... Wireless relay and network coding are two critical techniques to increase the reliability and throughput of wireless cooperative communication systems. In this paper, a complex field network coding (CFNC) scheme with the K-th best relay selection (KBS) is proposed and investigated, wherein the K-th best relay is selected to forward the multiplexed signal to the destination. First, the upper bound of the symbol error probability (SEP), the diversity order, and the coding gain are derived for the CFNC scheme with KBS. Then, the coding gain is utilized as the optimized cri- terion to determine the optimal power allocation. It is validated through analysis and simulation that the CFNC scheme with KBS can achieve full diversity only when K=I, while the diversity order decreases with increasing parameter K, and the optimal power allocation can significantly improve the performance of the CFNC scheme with KBS. 展开更多
关键词 complex field network coding the k-th best relay selection power allocation
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Cordial Labeling of Corona Product of Path Graph and Second Power of Fan Graph
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作者 Ashraf Ibrahim Hefnawy Elrokh Shokry Ibrahim Mohamed Nada Eman Mohamed El-Sayed El-Shafey 《Open Journal of Discrete Mathematics》 2021年第2期31-42,共12页
<div style="text-align:justify;"> <span style="font-family:Verdana;">A graph is said to be cordial if it has 0 - 1 labeling which satisfies particular conditions. In this paper, we cons... <div style="text-align:justify;"> <span style="font-family:Verdana;">A graph is said to be cordial if it has 0 - 1 labeling which satisfies particular conditions. In this paper, we construct the corona between paths and second power of fan graphs and explain the necessary and sufficient conditions for this construction to be cordial.</span> </div> 展开更多
关键词 CORONA Second power of Fan Cordial graph
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Fault Diagnosis Based on Graph Theory and Linear Discriminant Principle in Electric Power Network
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作者 Yagang ZHANG Qian MA +2 位作者 Jinfang ZHANG Jing MA Zengping WANG 《Wireless Sensor Network》 2010年第1期62-69,共8页
In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory algorithms and lin... In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory algorithms and linear discriminant principle to resolve fast and exact analysis of faulty components and faulty sections, and finally accomplish fault diagnosis. The results of BFS and linear discriminant are identical. The main technical contributions and innovations in this paper include, introducing global information into electric power network, developing a novel topological analysis to fault diagnosis. Graph theory algorithms can be used to model many different physical and abstract systems such as transportation and communication networks, models for business administration, political science, and psychology and so on. And the linear discriminant is a procedure used to classify an object into one of several a priori groupings dependent on the individual characteristics of the object. In the study of fault diagnosis in electric power network, graph theory algorithms and linear discriminant technology must also have a good prospect of application. 展开更多
关键词 FAULT Diagnosis graph Theory BFS LINEAR DISCRIMINANT PRINCIPLE Electric power Network
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The Wiener Index of an Undirected Power Graph
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作者 Volkan Aşkin Şerife Büyükköse 《Advances in Linear Algebra & Matrix Theory》 2021年第1期21-29,共9页
The undirected power graph <i>P</i>(<i>Z<sub>n</sub></i>) of a finite group <i>Z<sub>n</sub></i> is the graph with vertex set G and two distinct vertices u a... The undirected power graph <i>P</i>(<i>Z<sub>n</sub></i>) of a finite group <i>Z<sub>n</sub></i> is the graph with vertex set G and two distinct vertices u and v are adjacent if and only if <i>u</i> ≠ <i>v</i> and <img src="Edit_3b1df203-9ff2-4c13-93d1-4bba568eae54.png" width="40" height="20" alt="" /> or <img src="Edit_094c8f88-deb6-4f41-825a-ba91c0306ae8.png" width="40" height="20" alt="" />. The Wiener index <i>W</i>(<i>P</i>(<i>Z<sub>n</sub></i>)) of an undirected power graph <i>P</i>(<i>Z<sub>n</sub></i>) is defined to be sum <img src="Edit_348337df-b9c2-480d-9713-ec299a6fcd4e.png" width="110" height="25" alt="" /> of distances between all unordered pair of vertices in <i>P</i>(<i>Z<sub>n</sub></i>). Similarly, the edge-Wiener index <i>W<sub>e</sub></i>(<i>P</i>(<i>Z<sub>n</sub></i>)) of <i>P</i>(<i>Z<sub>n</sub></i>) is defined to be the sum <img src="Edit_e9b89765-f71e-4865-a0c5-c688710ff0c6.png" width="60" height="25" alt="" /> of distances between all unordered pairs of edges in <i>P</i>(<i>Z<sub>n</sub></i>). In this paper, we concentrate on the wiener index of a power graph <img src="Edit_dff0cd99-eb11-4123-a437-78cbbd8ebf96.png" width="40" height="20" alt="" />, <i>P</i>(<i>Z<sub>pq</sub></i>) and <i>P</i>(<i>Z<sub>p</sub></i>). Firstly, we obtain new results on the wiener index and edge-wiener index of power graph <i>P</i>(<i>Z<sub>n</sub></i>), using <i>m,n</i> and Euler function. Also, we obtain an equivalence between the edge-wiener index and wiener index of a power graph of <i>Z<sub>n</sub></i>. 展开更多
关键词 Wiener Index Edge-Wiener Index An Undirected power graph Line graph
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Directed Acyclic Graph Blockchain for Secure Spectrum Sharing and Energy Trading in Power IoT
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作者 Zixi Zhang Mingxia Zhang +2 位作者 Yu Li Bo Fan Li Jiang 《China Communications》 SCIE CSCD 2023年第5期182-197,共16页
Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing an... Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing and energy trading confronts security and privacy challenges.In this paper,we exploit consortium blockchain and Directed Acyclic Graph(DAG)to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT,named spectrum-energy chain,where a set of local aggregators(LAGs)cooperatively confirm the identity of the power devices by utilizing consortium blockchain,so as to form a main chain.Then,the local power devices verify spectrum and energy micro-transactions simultaneously but asynchronously to form local spectrum tangle and local energy tangle,respectively.Moreover,an iterative double auction based micro transactions scheme is designed to solve the spectrum and energy pricing and the amount of shared spectrum and energy among power devices.Security analysis and numerical results illustrate that the developed spectrum-energy chain and the designed iterative double auction based microtransactions scheme are secure and efficient for spectrum sharing and energy trading in power IoT. 展开更多
关键词 power Internet of Things(IoT) spectrum sharing energy trading security and privacy consortium blockchain Directed Acyclic graph(DAG) iterative double auction
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Graph neural network-based scheduling for multi-UAV-enabled communications in D2D networks
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作者 Pei Li Lingyi Wang +3 位作者 Wei Wu Fuhui Zhou Baoyun Wang Qihui Wu 《Digital Communications and Networks》 SCIE CSCD 2024年第1期45-52,共8页
In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission... In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission rate of Downlink Users(DUs).Meanwhile,the Quality of Service(QoS)of all D2D users must be satisfied.We comprehensively considered the interference among D2D communications and downlink transmissions.The original problem is strongly non-convex,which requires high computational complexity for traditional optimization methods.And to make matters worse,the results are not necessarily globally optimal.In this paper,we propose a novel Graph Neural Networks(GNN)based approach that can map the considered system into a specific graph structure and achieve the optimal solution in a low complexity manner.Particularly,we first construct a GNN-based model for the proposed network,in which the transmission links and interference links are formulated as vertexes and edges,respectively.Then,by taking the channel state information and the coordinates of ground users as the inputs,as well as the location of UAVs and the transmission power of all transmitters as outputs,we obtain the mapping from inputs to outputs through training the parameters of GNN.Simulation results verified that the way to maximize the total transmission rate of DUs can be extracted effectively via the training on samples.Moreover,it also shows that the performance of proposed GNN-based method is better than that of traditional means. 展开更多
关键词 Unmanned aerial vehicle D2 Dcommunication graph neural network power control Position planning
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面向幂律图的动态图存储结构Power-PCSR
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作者 毛志雄 刘志楠 +3 位作者 高叙宁 王蒙湘 巩树凤 张岩峰 《计算机科学》 CSCD 北大核心 2024年第8期56-62,共7页
图数据在现实生活中广泛存在,且不断发生变化。传统高效的静态图存储方式——压缩行/列(Compressed Sparse Row/Column,CSR/CSR)存储方式在更新图数据时需要大量的数据迁移,不适用于动态图数据。而能够高效更新图数据的邻接表(Adjacency... 图数据在现实生活中广泛存在,且不断发生变化。传统高效的静态图存储方式——压缩行/列(Compressed Sparse Row/Column,CSR/CSR)存储方式在更新图数据时需要大量的数据迁移,不适用于动态图数据。而能够高效更新图数据的邻接表(Adjacency List,AL)存储方式往往带有大量的指针,导致其图数据读取和分析效率低。Packed Compressed Sparse Row(PCSR)是一种基于CSR的动态图存储结构。该结构在存储边数据时并不是采用连续无空隙数组,而是采用留有空槽的压缩存储阵列(Packed Memory Arrays,PMA)结构,便于边数据的插入。因此,PCSR支持高效图更新和图分析。但是,PCSR在存储幂律图时,其性能容易受大度数顶点的影响。为此,基于PCSR提出一种支持可高效更新和分析动态幂律图的图存储结构Power-PCSR。该结构将幂律图中度数较大的顶点单独存储在一个独立的PMA中,其他所有小度数顶点与PCSR一样存储在原PMA中。小度顶点变化导致的数据迁移不会触及大度数顶点,从而大大减少了数据迁移数量;同样,大度数顶点更新导致的数据迁移只限制在每个大度数顶点的PMA内部,不会涉及小度数顶点和其他大度数顶点的数据迁移。实验显示,Power-PCSR在分析图数据时与PCSR具有相似的性能,而在更新图数据时比PCSR快2倍。 展开更多
关键词 动态图存储 动态图更新 数据迁移 power-PCSR 幂律图
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基于Visual Graph的电力图形系统开发 被引量:23
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作者 林济铿 覃岭 罗萍萍 《电力系统自动化》 EI CSCD 北大核心 2005年第15期73-76,共4页
针对传统面对对象的图形系统开发周期长、维护困难的缺点,基于通用图形开发平台——VisualGraph,提出了一种简便、清晰的面向图形对象的建模新方法。用可视化图形类建立电力元件并组成电网结构图,快速开发出图形系统。建模及过程全部实... 针对传统面对对象的图形系统开发周期长、维护困难的缺点,基于通用图形开发平台——VisualGraph,提出了一种简便、清晰的面向图形对象的建模新方法。用可视化图形类建立电力元件并组成电网结构图,快速开发出图形系统。建模及过程全部实现可视化,十分快捷。实际应用表明,该方法是有效的,所开发的图形系统具有良好的实际应用前景。 展开更多
关键词 VISUAL graph 面向图形对象 电网结构图 图形系统
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Dynamic software allocation algorithm for saving power in pervasive computing
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作者 韩松乔 张申生 +1 位作者 张勇 曹健 《Journal of Southeast University(English Edition)》 EI CAS 2007年第2期216-220,共5页
A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communic... A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communication and migration of software components, a power consumption model of component assignments between a mobile device and a server is set up. Also, the mobility of components and the mobility relationships between components are taken into account in software allocation. By using network flow theory, the optimization problem of power conservation is transformed into the optimal bipartition problem of a flow network which can be partitioned by the max-flow rain-cut algorithm. Simulation results show that the proposed algorithm can save si^nificantlv more energy than existing algorithms. 展开更多
关键词 power aware software allocation code mobility graph theory pervasive computing
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