CN103476051B - A kind of communication net node importance evaluation method - Google Patents
A kind of communication net node importance evaluation method Download PDFInfo
- Publication number
- CN103476051B CN103476051B CN201310413387.9A CN201310413387A CN103476051B CN 103476051 B CN103476051 B CN 103476051B CN 201310413387 A CN201310413387 A CN 201310413387A CN 103476051 B CN103476051 B CN 103476051B
- Authority
- CN
- China
- Prior art keywords
- node
- index
- network
- betweenness
- normalization
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Landscapes
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The present invention relates to a kind of communication net node importance evaluation method, the invention belongs to nodes analysis technical field.A kind of communication net node importance evaluation method, the method comprises the following steps: step 1: the communication network according to reality sets up network Model of having the right; Step 2: the node number of degrees k, node betweenness b, the characteristic vector index C that calculate weighted network respectively
ewith tightness index C
c, professional etiquette of going forward side by side is formatted; Step 3: to F
1, F
2, F
3and F
4, carry out the final score F that Result for Combinations obtains overall merit; Step 4: sort to n node according to the final score F value of overall merit is descending, gets the node that sequence is forward, as the important node in the communication network of reality, thus determines the importance of actual communication network interior joint.First the present invention utilizes the communication network of bandwidth to reality to be weighted, and is then realized the sequence of node importance by overall merit.
Description
Technical field
The present invention relates to a kind of communication net node importance evaluation method, the invention belongs to nodes analysis technical field.
Background technology
Along with communication and the fast development of information technology, the coverage rate of communication network progressively expands, and the business of carrying increases gradually, and the effect in modern large-scale network system is more and more important.Meanwhile, the nodes of communication network will constantly increase, and its complexity constantly increases, so to the node importance of communication network research or necessary.The appraisal procedure of complex network node importance mainly contains in recent years:
(1) based on the connection between this node and other nodes: be using the criterion of the degree of node as node importance the most simply, think that this node is more important more at most on the limit be connected with node, obvious this appraisal procedure has one-sidedness, some important core node might not have larger Connected degree, such as only has the bridge node that two limits are connected.
(2) based on the method that node (collection) is deleted: core concept is " importance is equivalent to the deleted rear destructiveness to network of this node (collection) ".To the excavation of important node in network, be reflected by the change of network connectivty, performance before and after node (collection) deletion.The delet method of node all used by a lot of document, namely supposes node failure, assesses pitch point importance by comparing the change of network performance before and after deletion of node.Knot removal method Problems existing is if the deletion of multiple node all makes network not be communicated with, and so the importance degree of these nodes will be consistent, thus makes assessment result inaccuracy.
(3) node contraction method: by shrinking the limit be connected with this node, thinks that higher then this node of network cohesion degree obtained after shrinking is more important.Network cohesion level index then mainly considers the Connected degree of node and the shortest path through node, assesses the contribution of node to network.Shrinking is the effective method of one weighing and assess node importance in network.Its advantage is mainly: do not need to remove node, and application has basis more widely.Meanwhile, also there is certain shortcoming in shrinking, mainly contains: have no idea to evaluate symmetrical nodes, and for general node, also wayward its shrinks scope.
The basic network topological parameter of complex network comprises the degree of node, betweenness, characteristic vector, tightness etc.The number of degrees of node refer to the limit number connecting this node, reflection be the direct influence of a node for other node in network.
Betweenness features the possibility of information flow through given node, and the betweenness of any node all can increase along with the increase of the information flow through this node, utilizes betweenness can the network node of comformed information heavy load.Brandes betweenness centrality algorithm is the algorithm being proposed to solve betweenness by UlrikBrandes, core concept appoints that to get a node be source node, search the shortest path of other node to this node by breadth-first search, then calculate the betweenness value corresponding to these shortest paths.The cumulative betweenness value that is source node with arbitrary node in scheming, just obtains the final betweenness value on all nodes and limit in figure.
Characteristic vector can be used for analyzing that indirect influence obtained by the adjacent node with height value, directly can not only reflect the Central Position of network, is also applicable to the long-term influence power of description node.Consider the meaning of parameters, linear combination is carried out to parameters, the defect that single index describes Centroid can be overcome, more can react node center in a network.
Tightness is the inverse that this node arrives the distance sum of other nodes all, for portraying the complexity of the node in network by other node in network arrival network, what reflect is the ability that node is exerted one's influence to other nodes by network, more can reflect the global structure of network.Internodal distance can be obtained by Floyd algorithm, and its main thought is: from representing any 2 vertex v
ito v
jthe weighted adjacency matrix of distance start, insert a vertex v at every turn
k, then by v
ito v
jbetween known shortest path with insert vertex v
kas issuable v time intermediate vertex (other summits in a paths except initial point and terminal)
ito v
jpath distance compares, and gets smaller value to obtain new distance matrix.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, the basis of network characterization parametric synthesis is weighted by the bandwidth in communication network, make full use of the intrinsic property of communication network, solve the importance ranking problem of communication network interior joint, provide a kind of communication net node importance evaluation method.
A kind of communication net node importance evaluation method, the method comprises the following steps:
Step 1: the communication network according to reality sets up network Model of having the right;
In actual communication network, node number is n, and the number on limit is m, then the network Model figure G that has the right of the communication network of this reality
gand connection matrix H=[h
ij] be described below:
G
G=(N,L)(1)
In formula: N is the set of communication network interior joint, N={n
1, n
2, n
3... n
n;
L is the set on one group of limit of having the right, L={l
1, l
2, l
3... l
m;
Element h in connection matrix H
ijbe defined as follows:
Limit power adjacency matrix W
gas follows:
Wherein, limit power adjacency matrix W
gmatrix element W
gijfor:
In formula, B
ijfor the weights of circuit between node i and node j;
Connection matrix H then after weighting
qcan be expressed as:
H
q=H*W
g(5), in formula, in * representing matrix, corresponding element is multiplied;
Step 2: the node number of degrees k calculating weighted network respectively
i, node betweenness b
i, characteristic vector index C
e(i) and tightness index C
ci (), professional etiquette of going forward side by side is formatted, and obtains normalization degree index F
1, normalization betweenness index F
2, normalization characteristic vector index F
3, normalization tightness index F
4:
1) normalization degree index F
1
The number of degrees k of i-th node
ithe number on the limit connecting this node, namely
To k
istandardize, can degree of normalization index F
1as follows:
F
1=k
i/(n-1)(7)
2) standardize betweenness index F
2
The betweenness b of i-th node
ifeature the influence power of the node in network for information flow; If network has n node, then the betweenness b of node i
ibe defined as:
δ
st(i)=g
st(i)/g
st
(9)
In formula, δ
sti () represents the ratio being accounted for all shortest paths by the shortest path number of this node, g
strepresent the shortest path number between node s and node t; g
sti () represents the shortest path number through node i between node s and node t, betweenness b
ibrandes betweenness centrality algorithm can be utilized to obtain;
To b
istandardize, obtain normalization betweenness index F
2as follows:
F
2=2b
i/(n-1)(n-2)(10)
3) standardize characteristic vector index F
3
If λ is matrix H
qdominant eigenvalue, e=(e
1, e
2..., e
n) be λ characteristic of correspondence vector, the characteristic vector index C of i-th node
ei () is defined as:
Wherein λ and e meets
:
H
Q·e=λ·e(12)
To C
ei () is standardized, characteristic vector of can standardizing index F
3as follows:
F
3=C
e(i)/max(C
e)(13)
4) standardize tightness index F
4
The tightness index C of i-th node
ci () is defined as the inverse that this node arrives the distance sum of other nodes all, that is:
Wherein, d
ijfor connecting the shortest path length of any two node i and j, can be obtained by Floyd algorithm;
To C
ci () is standardized, tightness of can standardizing index F
4as follows:
F
4=C
c(i)·(n-1)(15)
Step 3: to the normalization degree index F of n node of weighted network
1, normalization betweenness index F
2, normalization characteristic vector index F
3with normalization tightness index F
4, carrying out Result for Combinations, to obtain the final score F of each node overall merit as follows:
Wherein, α
kweight coefficient,
Step 4: sort to n node according to the final score F value of n node overall merit is descending, gets the node that sequence is forward, as the important node in the communication network of reality, thus determines the importance of power telecom network interior joint.
Beneficial effect of the present invention: first the present invention utilizes the communication network of bandwidth to reality to be weighted, then carry out comprehensively to the degree of network topology, betweenness, the basic parameter such as characteristic vector and tightness, realize the sequence of node importance.This invention is all considered network various aspects, is particularly suitable for communication network, has certain reference to the conceptual design of relevant issues, simultaneously also significant for the maintenance of network.
Accompanying drawing explanation
Fig. 1 is the FB(flow block) of the inventive method;
Fig. 2 is the network topology structure schematic diagram of example of the present invention;
Fig. 3 is the network topology structure schematic diagram after weighting of the present invention.
Embodiment
Below in conjunction with accompanying drawing, embodiments of the present invention are described further:
As shown in Figure 1, the FB(flow block) of the inventive method, a kind of communication net node importance evaluation method, it is characterized in that, the method comprises the following steps:
Step 1: the communication network according to reality sets up network Model of having the right;
Actual communication network have the right in network, node number is n, and the number on limit is m, then the Mathematical Modeling of the network of having the right of the communication network of this reality schemes G
gand connection matrix H=[h
ij] be described below:
G
G=(N,L)(1)
In formula, N is the set of communication network interior joint, N={n
1, n
2, n
3... n
n;
L is the set on one group of limit of having the right, L={l
1, l
2, l
3... l
m;
Element h in connection matrix H
ijbe defined as follows:
See Fig. 2, the connection matrix with the network topological diagram of connection shows as follows:
Limit power adjacency matrix W
gas follows:
Wherein, limit power adjacency matrix W
gmatrix element W
gijfor:
In formula, B
ijfor the weights of circuit between node i and node j.
Between communication network interior joint 7 as shown in Figure 3 and node 11, the bandwidth on limit is 2.5GHz, and other edge-band width is 1GHz, the limit between node 7 and node 11 is given to the weights of 2.5, and the weights on other limit are 1, and limit power connection matrix is as follows:
Connection matrix H then after weighting
qcan be expressed as:
H
Q=H*W
G(5)
In formula, in * representing matrix, corresponding element is multiplied, limit power adjacency matrix H
qembody the change of the connection matrix after weighting.
Connection matrix then after weighting is:
Step 2: the node number of degrees k, node betweenness b, the characteristic vector index C that calculate weighted network respectively
ewith tightness index C
c, professional etiquette of going forward side by side is formatted:
1) normalization degree index F
1
The number of degrees k of i-th node
ithe number on the limit connecting this node,
To k
istandardize, can degree of normalization index F
1as follows:
F
1=k
i/(n-1)(7)
2) standardize betweenness index F
2
The betweenness b of i-th node
ifeature the influence power of the node in network for information flow.If network has n node, then the betweenness b of node i
ibe defined as:
δ
st(i)=g
st(i)/g
st
(9)
In formula, δ
sti () represents the ratio being accounted for all shortest paths by the shortest path number of this node, g
strepresent the shortest path number between node s and node t; g
sti () represents the shortest path number through node i between node s and node t.Betweenness b
ibrandes betweenness centrality algorithm can be utilized to obtain, and concrete steps are:
Define the betweenness value based on the arbitrary node i of source node s:
Wherein N is figure G
gnode set, then:
And δ
si () then can pass through with s is root node, to figure G
ga breadth first traversal try to achieve.
To b
istandardize, obtain normalization betweenness index F
2as follows:
F
2=2b
i/(n-1)(n-2)(12)
3) standardize characteristic vector index F
3
If λ is matrix H
qdominant eigenvalue, e=(e
1, e
2..., e
n) be λ characteristic of correspondence vector, the characteristic vector index C of i-th node
ei () is defined as:
Wherein λ and e meets:
H
Q·e=λ·e(14)
The solution procedure of λ and e is as follows:
A () first obtains the characteristic value of matrix: | H
q-λ E|=0;
B () obtains (H to each eigenvalue λ
q-λ E) the basic course laboratory e of X=0
1, e
2..., e
n;
(c) H
qthe characteristic vector belonging to eigenvalue λ be exactly e
1, e
2..., e
nnon-zero linear combination.
To C
ei () is standardized, characteristic vector of can standardizing index F
3as follows:
F
3=C
e(i)/max(C
e)(15)
4) standardize tightness index F
4
The tightness index C of i-th node
ci () is defined as the inverse that this node arrives the distance sum of other nodes all, that is:
Wherein, d
ijfor the shortest path length of node i and j, can be obtained by Floyd algorithm.Concrete computational process is as follows:
Floyd algorithm adjacency matrix D used is:
Define the information that a matrix P is used for recording institute insertion point, P [i, j] represents from V
ito V
jneed the point of process, initialization P [i, j]=j.
Each summit is inserted in figure respectively, then compares the size of the distance after inserting summit k and former distance respectively:
D[i,j]=min(D[i,j],D[i,k]+D[k,j])(18)
If the value of D [i, j] diminishes, then P [i, j]=k.Then the final information including shortest path length between 2 in D, then contains the information in shortest path footpath in P.
To C
ci () is standardized, tightness of can standardizing index F
4as follows:
F
4=C
c(i)·(n-1)(19)
Calculate the normalization degree of each node after non-weighted sum weighting, betweenness, characteristic vector and tightness index respectively, as table 1, shown in table 2.
The normalization degree of each node of the non-weighted network of table 1, betweenness, characteristic vector, tightness index
The normalization degree of each node of table 2 weighted network, betweenness, characteristic vector, tightness index
To n node normalization degree index F of weighted network
1, normalization betweenness index F
2, normalization characteristic vector index F
3with normalization tightness index F
4, carrying out Result for Combinations, to obtain the final score F of each node overall merit as follows:
Wherein, α
kweight coefficient,
The weight coefficient of the normalization degree of node, betweenness, characteristic vector and tightness gets 0.2,0.25,0.35,0.2 respectively;
Step 4: sort to n node according to the final score F value of n node overall merit is descending, gets the node that sequence is forward, as the important node in the communication network of reality, thus determines the importance of actual communication network interior joint.
The node importance sequence obtained, as shown in table 3.
Table 3 node importance result of calculation contrasts
In network topological diagram as shown in Figure 2, before non-weighting, utilize synthesis and shrinkage method first to calculate node importance, as shown in Table 3, node 4, node 5, node 9, node 10 are most important side by side; For the network after weighting, as Fig. 3, weighting node 7-11, the importance that can be obtained node 7 and node 11 by synthesis significantly improves, and for shrinkage method be still node 4,5,9,10 important, sufficient proof this method can have certain advantage for the selection of core node in weighted network like this.Especially for power telecom network, power telecom network Centroid is important, but the degree of its Centroid is often not high, be difficult to find Centroid according to the method for not weighting, and due to the intrinsic property of Centroid, add bandwidth weighting, calculated by synthesis, very effectively can find Centroid.
Claims (1)
1. a communication net node importance evaluation method, is characterized in that, the method comprises the following steps:
Step 1: the communication network according to reality sets up network Model of having the right;
In actual communication network, node number is n, and the number on limit is m, then the network Model figure G that has the right of the communication network of this reality
gand connection matrix H=[h
ij] be described below:
G
G=(N,L)(1)
In formula: N is the set of communication network interior joint, N={n
1, n
2, n
3... n
n;
L is the set on one group of limit of having the right, L={l
1, l
2, l
3... l
m;
Element h in connection matrix H
ijbe defined as follows:
Limit power adjacency matrix W
gas follows:
Wherein, limit power adjacency matrix W
gmatrix element W
gijfor:
In formula, B
ijfor the weights of circuit between node i and node j;
Connection matrix H then after weighting
qcan be expressed as:
H
Q=H*W
G(5)
In formula, in * representing matrix, corresponding element is multiplied;
Step 2: the node number of degrees k calculating weighted network respectively
i, node betweenness b
i, characteristic vector index C
e(i) and tightness index C
ci (), professional etiquette of going forward side by side is formatted, and obtains normalization degree index F
1, normalization betweenness index F
2, normalization characteristic vector index F
3, normalization tightness index F
4:
1) normalization degree index F
1
The number of degrees k of i-th node
ithe number on the limit connecting this node, namely
To k
istandardize, can degree of normalization index F
1as follows:
F
1=k
i/(n-1)(7)
2) standardize betweenness index F
2
The betweenness b of i-th node
ifeature the influence power of the node in network for information flow; If network has n node, then the betweenness b of node i
ibe defined as:
δ
st(i)=g
st(i)/g
st
(9)
In formula, δ
sti () represents the ratio being accounted for all shortest paths by the shortest path number of this node, g
strepresent the shortest path number between node s and node t; g
sti () represents the shortest path number through node i between node s and node t, betweenness b
ibrandes betweenness centrality algorithm can be utilized to obtain;
To b
istandardize, obtain normalization betweenness index F
2as follows:
F
2=2b
i/(n-1)(n-2)(10)
3) standardize characteristic vector index F
3
If λ is matrix H
qdominant eigenvalue, e=(e
1, e
2..., e
n) be λ characteristic of correspondence vector, the characteristic vector index C of i-th node
ei () is defined as:
Wherein λ and e meets:
H
Q·e=λ·e(12)
To C
ei () is standardized, characteristic vector of can standardizing index F
3as follows:
F
3=C
e(i)/max(C
e)(13)
4) standardize tightness index F
4
The tightness index C of i-th node
ci () is defined as the inverse that this node arrives the distance sum of other nodes all, that is:
Wherein, d
ijfor connecting the shortest path length of any two node i and j, can be obtained by Floyd algorithm;
To C
ci () is standardized, tightness of can standardizing index F
4as follows:
F
4=C
c(i)·(n-1)(15)
Step 3: to the normalization degree index F of n node of weighted network
1, normalization betweenness index F
2, normalization characteristic vector index F
3with normalization tightness index F
4, carrying out Result for Combinations, to obtain the final score F of each node overall merit as follows:
Wherein, α
kweight coefficient,
Step 4: sort to n node according to the final score F value of n node overall merit is descending, gets the node that sequence is forward, as the important node in the communication network of reality, thus determines the importance of power telecom network interior joint.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201310413387.9A CN103476051B (en) | 2013-09-11 | 2013-09-11 | A kind of communication net node importance evaluation method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201310413387.9A CN103476051B (en) | 2013-09-11 | 2013-09-11 | A kind of communication net node importance evaluation method |
Publications (2)
Publication Number | Publication Date |
---|---|
CN103476051A CN103476051A (en) | 2013-12-25 |
CN103476051B true CN103476051B (en) | 2016-04-13 |
Family
ID=49800718
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201310413387.9A Expired - Fee Related CN103476051B (en) | 2013-09-11 | 2013-09-11 | A kind of communication net node importance evaluation method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN103476051B (en) |
Families Citing this family (20)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103957114A (en) * | 2014-02-24 | 2014-07-30 | 国家电网公司 | Network survivability assessment method based on variation coefficient |
CN103906271B (en) * | 2014-04-21 | 2017-06-13 | 西安电子科技大学 | Key node measuring method in Ad Hoc networks |
CN104363127B (en) * | 2014-11-28 | 2016-06-08 | 广东电网有限责任公司电力调度控制中心 | Based on the power communication network construction process of the electric network influencing factor |
CN104579867B (en) * | 2014-11-28 | 2016-06-08 | 广东电网有限责任公司电力调度控制中心 | Based on the power communication network construction process of node aggregation coefficient |
CN104811397B (en) * | 2015-03-24 | 2016-02-24 | 中国人民解放军国防科学技术大学 | A kind of complex network node importance appraisal procedure developed based on node state |
CN104992266A (en) * | 2015-06-15 | 2015-10-21 | 广东电网有限责任公司电力调度控制中心 | Method of determining power grid node importance degree and system thereof |
CN104915504A (en) * | 2015-06-18 | 2015-09-16 | 莫毓昌 | BFS strategy improvement method used for novel calculation network reliability evaluation |
CN105550191A (en) * | 2015-07-10 | 2016-05-04 | 成都信息工程大学 | Node importance ranking method for multi-layer network |
CN106375104B (en) * | 2015-07-24 | 2019-10-15 | 国家电网公司 | A kind of powerline network key point knowledge method for distinguishing |
CN105306540A (en) * | 2015-09-24 | 2016-02-03 | 华东师范大学 | Method for obtaining top k nodes with maximum influence in social network |
CN105490840A (en) * | 2015-11-26 | 2016-04-13 | 电子科技大学 | Fault diagnosis test point selection method based on network topological structure |
CN105871594A (en) * | 2016-03-22 | 2016-08-17 | 华北电力大学(保定) | Method for calculating important degrees of nodes of power communication network |
CN107846293B (en) * | 2016-09-19 | 2020-12-01 | 中国电信股份有限公司 | IPv6 communication capacity calculation method and device |
CN107070995A (en) * | 2017-03-16 | 2017-08-18 | 中国科学院信息工程研究所 | The caching method and device of a kind of content center network |
CN107395393A (en) * | 2017-06-14 | 2017-11-24 | 华北电力大学 | A kind of power communication backbone network node evaluation method of automatic weight coefficient |
CN108399491B (en) * | 2018-02-02 | 2021-10-29 | 浙江工业大学 | Employee diversity ordering method based on network graph |
CN109104307B (en) * | 2018-07-27 | 2021-06-04 | 电子科技大学 | Key node sensing method of dynamic data link network |
CN109756422B (en) * | 2019-03-27 | 2021-07-20 | 浪潮云信息技术股份公司 | Forwarding routing node selection method |
CN111800201B (en) * | 2020-06-24 | 2021-06-15 | 西北工业大学 | Method for identifying key nodes of Sink node underwater acoustic sensor network |
CN114637236B (en) * | 2022-03-03 | 2024-07-19 | 国网电力科学研究院有限公司 | Time delay calculation method, device and storage medium based on hybrid frequency stability control system |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101145976A (en) * | 2007-10-31 | 2008-03-19 | 北京航空航天大学 | Super-node selection and resource search method for peer network with node priority |
CN102196461A (en) * | 2011-06-22 | 2011-09-21 | 韩山师范学院 | Evaluation method for importance of sensor network node |
CN102880799A (en) * | 2012-09-24 | 2013-01-16 | 西北工业大学 | Method for comprehensively evaluating importance of complicated network node based on multi-attribute decision-making |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR101123850B1 (en) * | 2010-01-05 | 2012-03-20 | 주식회사 오웨이브미디어 | Method for scoring individual network competitiveness and network effect in an online social network |
-
2013
- 2013-09-11 CN CN201310413387.9A patent/CN103476051B/en not_active Expired - Fee Related
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101145976A (en) * | 2007-10-31 | 2008-03-19 | 北京航空航天大学 | Super-node selection and resource search method for peer network with node priority |
CN102196461A (en) * | 2011-06-22 | 2011-09-21 | 韩山师范学院 | Evaluation method for importance of sensor network node |
CN102880799A (en) * | 2012-09-24 | 2013-01-16 | 西北工业大学 | Method for comprehensively evaluating importance of complicated network node based on multi-attribute decision-making |
Non-Patent Citations (2)
Title |
---|
李琳,刘雅奇.通信网节点重要性的多指标评价方法.《海军工程大学学报》.2010,第22卷(第5期),正文第69-73页. * |
谢琼瑶,邓长虹,赵红生,翁毅选.基于有权网络模型的电力网节点重要度评估.《电力***自动化》.2009,第33卷(第4期),正文第21-24页. * |
Also Published As
Publication number | Publication date |
---|---|
CN103476051A (en) | 2013-12-25 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN103476051B (en) | A kind of communication net node importance evaluation method | |
CN106850254B (en) | Method for identifying key nodes in power communication network | |
CN103324980B (en) | A kind of method for forecasting | |
CN110311376A (en) | A kind of Electrical Power System Dynamic security evaluation collective model and space-time method for visualizing | |
CN102571954B (en) | Complex network clustering method based on key influence of nodes | |
CN112149873B (en) | Low-voltage station line loss reasonable interval prediction method based on deep learning | |
AU2013201595A1 (en) | Method and apparatus for harmonic state estimation in power system | |
CN103607320B (en) | Power telecom network survivability evaluation methodology | |
CN104732300B (en) | A kind of neutral net wind power short term prediction method theoretical based on Fuzzy divide | |
CN110111024A (en) | Scientific and technological achievement market value evaluation method based on AHP fuzzy comprehensive evaluation model | |
CN110417011A (en) | A kind of online dynamic secure estimation method based on mutual information Yu iteration random forest | |
CN108054757B (en) | It is a kind of to embed idle and voltage N-1 Close loop security check method | |
CN107483487B (en) | TOPSIS-based multi-dimensional network security measurement method | |
Zhang et al. | Identifying node importance by combining betweenness centrality and katz centrality | |
CN109670611A (en) | A kind of power information system method for diagnosing faults and device | |
CN103020485B (en) | Based on the short-term wind speed forecasting method of beta noise core ridge regression technology | |
CN106843100A (en) | Substation secondary device running status level determination method and device | |
Yang et al. | Resilience assessment and improvement for electric power transmission systems against typhoon disasters: a data-model hybrid driven approach | |
CN106875124A (en) | A kind of electric power meter state evaluating method, apparatus and system | |
CN114154766A (en) | Method and system for early warning vulnerability of power grid under dynamic prediction of thunder and lightning | |
Shahpari et al. | Vulnerability analysis of power grid with the network science approach based on actual grid characteristics: A case study in Iran | |
CN104967114A (en) | Power grid load real-time digital modeling method and system | |
CN107462810A (en) | A kind of fault section location method suitable for active power distribution network | |
Benzerga et al. | Low-voltage network topology and impedance identification using smart meter measurements | |
CN114385403A (en) | Distributed cooperative fault diagnosis method based on double-layer knowledge graph framework |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
C14 | Grant of patent or utility model | ||
GR01 | Patent grant | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20160413 Termination date: 20210911 |
|
CF01 | Termination of patent right due to non-payment of annual fee |