WO2016090961A1 - 一种网络关联分析方法及装置 - Google Patents

一种网络关联分析方法及装置 Download PDF

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WO2016090961A1
WO2016090961A1 PCT/CN2015/088293 CN2015088293W WO2016090961A1 WO 2016090961 A1 WO2016090961 A1 WO 2016090961A1 CN 2015088293 W CN2015088293 W CN 2015088293W WO 2016090961 A1 WO2016090961 A1 WO 2016090961A1
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network
analysis
data
location
module
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PCT/CN2015/088293
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English (en)
French (fr)
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柳海辉
朱世军
钟陈练
安峰
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中兴通讯股份有限公司
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/04—Arrangements for maintaining operational condition

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  • the present invention relates to the field of mobile communications, and in particular, to a network association analysis method and apparatus.
  • OMM Operaation Maintenance Module
  • Core Network Performance data analysis: performance data can reflect the performance of the entire network, but can not focus on the specific user problem.
  • Alarm analysis can only reflect specific equipment failures, but it is difficult to correlate with specific user problems.
  • CDT Call Detail Trace
  • CDT data analysis is generated: CDT data reflects that the real situation of the system is during the call. A snapshot of the wireless environment and system status, CDT data analysis can obtain every network call details of each user, but it can only display the basic cause value of the abnormal event, and cannot locate the specific device caused by the problem.
  • the embodiment of the invention provides a network association analysis method and device, which at least solves the problem that the related technology only analyzes the problem in the network from a certain dimension, and cannot accurately solve the solution in the network.
  • the embodiment of the present invention adopts the following technical solutions:
  • a network association analysis method including:
  • the method further includes: pre-processing screening the multi-dimensional network data;
  • the network data analysis of the at least one dimension of the location grid in which the network abnormal event occurs according to the acquired multi-dimensional network data and the location raster information comprises: according to the pre-processed multi-dimensional network data. And the location raster information performs at least one dimension of network data analysis on a location raster in which the network anomaly event occurs.
  • Performing at least one dimension of network data analysis on the location grid in which the network abnormal event occurs according to the pre-processed multi-dimensional network data and the location raster information specifically includes: pre-processing multi-dimensional network data according to the pre-processing And the location raster information is performed on the location grid where the network abnormal event occurs, including at least one of the following network data analysis: alarm analysis, capacity analysis, coverage analysis, and wireless parameter analysis.
  • Obtaining a network problem in the location grid where the network abnormal event occurs includes: if the analysis result has at least two network problems in the alarm analysis, the capacity analysis, the coverage analysis, and the wireless parameter analysis, according to the preset priority The network problem with the highest priority is selected as the network problem in the location grid where the network anomaly event occurs.
  • the method further includes: performing aggregation processing of the analysis result in the corresponding location grid in each area of the network in at least one dimension; and performing a dimension-division network on the each area according to the result of the aggregation processing Sort the questions.
  • a network association analysis device includes:
  • a data acquisition module configured to acquire detailed call tracking data and multi-dimensional network data in the network
  • a location raster determining module configured to search for a network abnormal event in the call detailed tracking data acquired by the data acquiring module, and determine location raster information of the network abnormal event;
  • a data analysis module configured to perform at least one dimension on the location grid where the network abnormal event occurs according to the multi-dimensional network data acquired by the data acquisition module and the location raster information determined by the location raster determination module Network data analysis to determine the network problem in the location grid where the network anomaly occurred.
  • the device further includes: a data pre-processing module, configured to perform pre-processing on screening the multi-dimensional network data acquired by the data acquisition module; the data analysis module is specifically configured to: after pre-processing according to the pre-processing module The multi-dimensional network data and the location raster information determined by the location raster determination module perform at least one dimension of network data analysis on the location raster in which the network anomaly event occurs to determine the location of the network anomaly event. Network problems with rasters.
  • the data analysis module specifically includes: an alarm analysis sub-module, a capacity analysis sub-module, a coverage analysis sub-module, and a wireless parameter analysis sub-module, where the data analysis module is specifically configured according to the pre-processed multi-dimensional network data and the
  • the grid information includes at least one of the following network data analysis for the location grid in which the network anomaly event occurs: alarm analysis, capacity analysis, coverage analysis, and wireless parameter analysis.
  • the network analysis module analyzes and obtains the network problem that the location grid of the network abnormal event occurs, and specifically includes: if at least two network problems in the alarm analysis, capacity analysis, coverage analysis, and wireless parameter analysis exist in the analysis result, Then, the network problem with the highest priority is selected according to the preset priority as the network problem existing in the location grid where the network abnormal event occurs.
  • the device further includes an area sorting module, and the area sorting module specifically includes: a collection processing sub-module, configured to perform at least a result in a corresponding position grid in each area of the network analyzed by the data analysis module A collection process of dimensions; the region sorting sub-module is configured to sort the network problems of the differentiated dimensions of the regions according to the processed result of the aggregation processing sub-module.
  • the embodiment of the present invention provides a network association analysis method and device. After acquiring CDT data and multi-dimensional network data in a network, searching for network anomaly events according to CDT data, and determining raster information of the network abnormal event occurs, At least one dimension of network data analysis is performed on the grid in which the network abnormal event occurs, and the network problem in which the grid abnormality event occurs is obtained.
  • the solution mainly obtains the raster information of the network anomaly event through the CDT data, and then performs at least one dimension of the data analysis on the grid. Through the correlation analysis, the grid in which the network abnormal event occurs can be obtained more accurately. The most likely network problem is to assist the network optimization engineer to quickly find the problem, which provides a better method for network maintenance and normal operation.
  • the following analysis is performed on the grid in which the network abnormal event occurs: alarm analysis, capacity analysis, coverage analysis, and wireless parameter analysis, and the network problem of the grid is analyzed according to the preset priority from high to low.
  • the obtained analysis results can be more accurate, reasonable, and fast, so that the network optimization engineers can network to the network for the first time.
  • the grid in question has been processed accordingly, which facilitates the work of the network optimization engineer and saves resources waste.
  • FIG. 1 is a flowchart of a network association analysis method according to Embodiment 1 of the present invention
  • FIG. 2 is a schematic structural diagram of a network association analysis apparatus according to Embodiment 2 of the present invention.
  • FIG. 1 is a schematic diagram of a network association analysis method according to Embodiment 1 of the present invention. Referring to FIG. 1, the method includes:
  • the call detailed tracking data includes: bill data, key data for tracking each call of the access system, and key data for the system to process the user access during the access process. That is, the CDT data reflects the real situation of the system is a snapshot of the wireless environment and system status during the call.
  • each network call details of each user can be obtained; the network data of the multiple dimensions specifically includes: industrial parameter data, configuration data, performance data, alarm data, and DT/CQT Data and the like; the step of obtaining network data may be timed acquisition or active operation acquisition, etc., such as setting once every 5 minutes.
  • S102 Find a network abnormal event in the call detailed tracking data, and determine location raster information of the network abnormal event. Specifically, based on the CDRs in the CDT data, the network abnormal events are found through special evaluations such as dropped calls, access, and poor quality (low rate), and the abnormal events are located to somewhere through the CDT bill positioning algorithm. In the position grid. In this way, by analyzing the acquired CDT data, it can be obtained which user has a network abnormal event; and the location raster of the network abnormal event is calculated by the CDT positioning algorithm; the occurrence of the network abnormal event specifically includes : Anomalous problems such as dropped calls, access failures, or weak coverage; the location grid represents the smallest spatial unit in the network area.
  • S103 Perform at least one dimension of network data analysis on the location grid where the network abnormal event occurs according to the acquired multi-dimensional network data and the location raster information, to obtain a location grid where the network abnormal event occurs.
  • the network problem of the location raster where the network abnormal event occurs is specifically: if at least two network problems in the alarm analysis, capacity analysis, coverage analysis, and wireless parameter analysis exist in the analysis result, according to the preset Priority Selects the network problem with the highest priority as the network problem in the location grid where the network anomaly occurs. specifically,
  • the alarm analysis specifically includes: querying an alarm identifier (Identification, ID) by using an RNC (Radio Network Controller) and a cell ID of the cell ID in which the network abnormal event occurs, and if there is an alarm that causes a network abnormal event
  • the output anomaly analysis is mainly a device problem, and the specific device is given in the detailed reason description.
  • the associated alarm problem includes the following: uplink low power, carrier baseband low power, low carrier.
  • RRU Radio Remote Unit
  • GPS Global Positioning System
  • HDLC High -Level Data Link Control, high-speed link control
  • PPP Public-Private -Partnership, public-private partnership mode
  • the capacity analysis specifically includes: querying the base station by using the RNC and the cell identifier CellID in which the network abnormal event occurs, and the capacity information of the core network at the time. If the capacity reaches the upper limit, the output abnormality analysis is mainly a capacity problem, and is given in the detailed reason description.
  • Capacity analysis indicators include: system capacity load assessment, BHCA (Busy Hour Call Attempt), dimension resource overload analysis, ERL (line unit) dimension resource overload ratio analysis, 1X and DO fan Overload ratio analysis, overload analysis of main service boards and control boards on the base station side, overload analysis of control flow between frames, overload analysis of interface boards, and resource utilization analysis of service processing units.
  • the coverage analysis specifically includes: analyzing the latitude and longitude and signal strength of the network anomaly event, analyzing the weak coverage, the interference, the pilot pollution, the coverage coverage output abnormality analysis category, and analyzing the source or target cell of the problem: 1) When the event occurs, the UE accesses the EC/Io (Energy per Chip average chip power/the Total Interference density) value is less than the specified threshold N, which is determined to be weak coverage; 2) when the event is released, RAB (Radio) Access Bearer, wireless access bearer) busy ratio is less than the predetermined threshold (default 10%); RSSI (Received Signal Strength Indication) is higher than a predetermined threshold (default is -95dBm) is determined as interference; 3) when the event occurs, the number of pilots received by the UE is greater than or equal to 3; When the difference between the strongest and weakest pilot strengths is not greater than the specified threshold M, it is determined to be pilot pollution.
  • EC/Io Energy per Chip average chip power/the Total Interference density
  • the wireless parameter analysis specifically includes: combining the occurrence of the network abnormal event RNC and the cell ID, and correlating the wireless configuration parameters, and analyzing whether the value of the configuration parameter of the cell is abnormal.
  • the analysis indicators are shown in the following table:
  • the location grid of the network abnormal event eventually occurs.
  • Existing network problems will be displayed with the highest priority network problem according to the preset priority.
  • the priority of the network problem from high to low is: alarm analysis, capacity analysis, coverage analysis, and wireless parameter analysis; it should be noted that for some special cases Or a special network, there may be other priority rankings, and this solution is not limited to this priority ranking.
  • the method further includes: performing pre-processing on screening the multi-dimensional network data; that is, performing various types on the acquired multi-dimensional network data.
  • the filtering process in the dimension for example, the timing can be used to filter the acquired multi-dimensional network data, and only need to select the network data useful for the analysis of the network data of each dimension, and the network data can be simplified and reduced.
  • the data storage space is saved in a specified FTP (File Transfer Protocol) (storage computer) server.
  • the step S103 performs at least one dimension of the network data analysis on the location grid in which the network abnormal event occurs according to the acquired multi-dimensional network data and the location raster information, and specifically includes:
  • the pre-processed multi-dimensional network data and the location raster information perform at least one dimension of network data analysis on a location grid in which the network anomaly event occurs. That is, before performing at least one dimension of network data analysis on the location grid where the network anomaly occurs, the network data of various dimensions is pre-processed first, so that the analysis of the network data thereof greatly shortens the analysis time. Network optimization engineers quickly save time by making solutions.
  • the method further includes: performing aggregation processing of the analysis result in the corresponding location grid in each area of the network in at least one dimension; and performing network problem of distinguishing dimensions on the each area according to the result of the aggregation processing Sort.
  • the network anomaly event and the network signal quality are aggregated and analyzed by using the location grid as a dimension, and the problem location grid and the problem location grid TOPN cell are sequentially analyzed (for each area in the network) Sorting network problems with dimensions), problem reason raster analysis. specifically:
  • the evaluation of the problem location grid includes: determining that the access success rate does not reach the preset threshold N1 is an access failure grid; determining that the dropped call rate reaches the threshold N2 is a dropped call grid; and the ratio of the weak coverage points to the total number of points is The decision to reach the threshold N3 is a weak coverage deletion; when the ratio of the coverage points to the total number of points reaches the threshold N4, it is determined as a coverage overlay grid.
  • the problem location grid top 10 cell when the problem location grid is determined to be weakly covered, the primary cell of all weak coverage points is counted, and the number of weak coverage points generated by each cell in the grid is sequentially sorted according to the number of statistics.
  • the weak coverage cell of the TOPN is generated; when the problem location grid is determined to be the coverage of the handover, the source cell causing the coverage of the coverage area is counted, and the number of coverage points generated from the location grid of the problem area is sequentially increased according to the location coverage source cell.
  • the TOPN coverage area is counted; when the problem location grid is determined to be pilot pollution, the cell causing the pilot pollution is counted, and the number of coverage points generated in the grid according to the coverage area is sequentially sorted according to the number of coverage points.
  • the pilot contaminated cell of TOPN is counted.
  • the problem causes the location raster analysis: when the problem location grid is determined as the dropped grid, the reason for the dropped call is separately counted: equipment problem, coverage problem, capacity problem or wireless problem; the number of dropped calls in the location grid, And sorting from more to less, the cause of the TOPN problem is counted; similarly, the position raster analysis method for determining the occurrence of the network abnormal event as the access failure or the poor signal quality is the same as the grid analysis of the dropped call position.
  • a UE mobile terminal
  • the event CDT CDR the CDR includes the service cell information when the call is dropped, and the signal strength of the primary neighbor cell.
  • Alarm analysis The cell RNC and the cell ID (CellID) are associated with the alarm data in the same segment, and the alarm code of the "low power abnormality" is found in the cell. The alarm analysis process determines that the call drop is a device fault.
  • Capacity analysis through the cell RNC and The CellID associated with the cell queries the capacity information of the base station and the core network at that time, and finds no problem; coverage analysis: by analyzing the parameters such as latitude and longitude and signal strength in the CDT data, the weak coverage of the coverage problem is discriminated, and the interference and pilot pollution problems can be eliminated; Wireless parameter analysis: the parameter configuration problem is found by the cell RNC and the cell identity CellID associated wireless configuration parameters; comprehensive analysis: the priority set according to the overall process is high to low: alarm, capacity, coverage, wireless parameters, and the call drop is determined. The cause is a device failure.
  • the problem area location function counts the abnormal CDT bills from 3 pm to 4 pm on December 20, 2013, and counts the dropped calls to the grid of the location where the latitude and longitude occurred.
  • FIG. 2 is a schematic structural diagram of a network association analysis apparatus according to Embodiment 2 of the present invention.
  • the network association analysis apparatus 20 includes: a data acquisition module 201, a location grid determination module 202, and data analysis.
  • the module 203 is configured to acquire call detailed tracking data and multi-dimensional network data in the network; the location raster determining module 202 is configured to be in the call detailed tracking data acquired by the data acquiring module 201.
  • the data analysis module 203 is configured to use the multi-dimensional network data acquired by the data acquiring module 201 and the location raster determining module 202 Determining the location raster information, performing network data analysis of at least one dimension on the location grid where the network abnormal event occurs, and determining a network problem existing in the location grid where the network abnormal event occurs.
  • the network association analysis device 20 further includes: a data pre-processing module, configured to perform pre-processing on filtering multi-dimensional network data acquired by the data acquisition module; and the data analysis module is specifically configured to : multi-dimensional network data preprocessed by the preprocessing module and the location raster determining module
  • the determined location raster information performs at least one dimension of network data analysis on the location grid in which the network anomaly event occurs, and determines a network problem in which the location grid of the network anomaly event occurs.
  • the data analysis module 203 specifically includes: an alarm analysis sub-module, a capacity analysis sub-module, a coverage analysis sub-module, and a wireless parameter analysis sub-module, where the data analysis module is specifically configured according to the pre-processed
  • the multi-dimensional network data and the raster information perform at least one of the following network data analysis on the location grid in which the network anomaly event occurs: alarm analysis, capacity analysis, coverage analysis, and wireless parameter analysis. If at least two network problems in the alarm analysis, capacity analysis, coverage analysis, and wireless parameter analysis exist in the analysis result, the network problem with the highest priority is selected according to the preset priority as the location grid where the network abnormal event occurs. There are network problems. Preferably, the priority levels from high to low are: alarm analysis, capacity analysis, coverage analysis, and wireless parameter analysis.
  • the network association analysis device 20 further includes an area sorting module, and the area sorting module specifically includes: a collection processing sub-module, configured to analyze the corresponding location grid in each area of the network analyzed by the data analysis module The result is a collection process of at least one dimension; the region sorting sub-module is configured to sort the network problems of the differentiated dimensions of the regions according to the processed result of the aggregation processing sub-module.
  • the embodiment of the invention provides a network association analysis method and device. Based on the CDT data, after analyzing the network abnormal event for the CDT data and determining the raster information of the network abnormal event, the network abnormal event occurs.
  • the grid performs at least one dimension of network data analysis to obtain network problems in the grid where network anomalies occur.
  • This solution analyzes the CDT data in the network and the network data of other dimensions. Through this association analysis, the most likely network problem of the grid abnormality event can be obtained more accurately, so as to assist the network optimization engineer to find The problem provides a solution for the maintenance and normal operation of the network.
  • the network association analysis method and apparatus have the following beneficial effects: after obtaining the raster information of the network anomaly event through the CDT data, performing at least one dimension of the data on the grid. Analysis, through this correlation analysis, can more accurately obtain the most likely network problems in the grid where network anomalies occur, to assist network optimization engineers to quickly find problems, and provide a better method for network maintenance and normal operation.
  • the following analysis is performed on the grid in which the network abnormal event occurs: alarm analysis, capacity analysis, coverage analysis, and wireless parameter analysis, and the network problem of the grid is analyzed according to the preset priority from high to low.
  • the obtained analysis results can be more accurate, reasonable, and fast, so that the network optimization engineers can network to the network for the first time.
  • the grid in question has been processed accordingly, which facilitates the work of the network optimization engineer and saves resources waste.

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Abstract

本发明提供了一种网络关联分析方法及装置，所述网络关联分析方法包括：获取网络中的呼叫详细跟踪数据及多维度的网络数据；在所述呼叫详细跟踪数据中查找网络异常事件，并确定发生所述网络异常事件的位置栅格信息；根据获取的多维度的网络数据和所述位置栅格信息，对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析，得到发生所述网络异常事件的位置栅格存在的网络问题。解决了现有技术中只是从某一种维度对网络中的问题进行分析，不能准确且快速地得到解决网络中存在问题的方案的问题，辅助网优工程师快速查找问题，为网络的维护及正常运行提供了较优的方法。

Description

一种网络关联分析方法及装置 技术领域
本发明涉及移动通信领域，尤其涉及一种网络关联分析方法及装置。
背景技术
随着无线网络的发展，移动运营商之间的用户争夺愈演愈烈，对运维质量、定位手段和问题解决周期等要求也越来越高，传统的网络问题分析主要是基于TOPN(前N位)小区的分析和基于个别问题点的处理，分析维度比较单一，分析方法主要基于网优工程师的经验，解决周期长，耗时耗力。因此，对运营商来说，迫切需要综合性问题分析和解决方案，这个解决方案要能够分析和解决网络各个节点问题：核心网、基站侧和无线侧等。传统的无线网络问题分析方法一般包括如下几种：
DT(Drive Test，路测)/CQT(Call Quality Test，呼叫质量拨打测试)分析：这是一种覆盖平面上的线性测试，它可以测试用户在特定网络的真实情况，这个方法可以协助定位无线测问题，但这个方法是在问题发生后进行问题复现，无法真实反应问题发生时场景。
OMM(Operation Maintenance Module，操作维护模块)(核心网)的性能数据分析：性能数据可以反映全网的性能情况，但是无法关注定位到具体某一个用户问题。
告警分析：告警分析只能反映具体设备故障，但是很难关联到具体用户问题。
可以看出，传统的分析方法，都无法全面的解决无线网络问题，为解决这个问题，就产生了CDT(Call Detail Trace，呼叫详细跟踪)数据分析：CDT数据反映了系统的真实状况是通话时的无线环境和系统状况的快照，CDT数据分析可以获取到每一个用户的每一次网络呼叫详情，但它只能显示异常事件基本原因值，无法定位到问题具体由哪些设备引起的。
发明内容
本发明实施例提供了一种网络关联分析方法及装置，至少解决了相关技术中只是从某一个维度对网络中的问题进行分析，不能准确地得到解决网络中存在问题的方案的问题。
为了至少解决上述问题，本发明实施例采用以下技术方案：
一种网络关联分析方法，包括：
获取网络中的呼叫详细跟踪数据及多维度的网络数据；
在所述呼叫详细跟踪数据中查找网络异常事件，并确定发生所述网络异常事件的位置栅格信息；
根据获取的多维度的网络数据和所述位置栅格信息，对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析，得到发生所述网络异常事件的位置栅格存在的网络问题。
所述获取网络中的呼叫详细跟踪数据及多维度的网络数据后，还包括：对所述多维度的网络数据进行筛选的预处理；
所述根据获取的多维度的网络数据和所述位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析具体包括：根据预处理后的多维度的网络数据和所述位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析。
根据预处理后的多维度的网络数据和所述位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析具体包括：根据预处理后的多维度的网络数据和所述位置栅格信息对发生所述网络异常事件的位置栅格进行包括以下至少一种网络数据分析：告警分析、容量分析、覆盖分析和无线参数分析。
得到发生所述网络异常事件的位置栅格存在的网络问题具体包括：若分析结果存在所述告警分析、容量分析、覆盖分析和无线参数分析中的至少两种网络问题，则根据预设优先级选择优先级最高的网络问题作为发生所述网络异常事件的位置栅格存在的网络问题。
所述方法还包括：将所述网络中各区域内对应的位置栅格中的分析结果进行至少一种维度的汇集处理；根据所述汇集处理后的结果对所述各区域进行区分维度的网络问题排序。
一种网络关联分析装置，包括：
数据获取模块，设置为获取网络中的呼叫详细跟踪数据及多维度的网络数据；
位置栅格确定模块，设置为在所述数据获取模块获取的呼叫详细跟踪数据中查找网络异常事件，并确定发生所述网络异常事件的位置栅格信息；
数据分析模块，设置为根据所述数据获取模块获取的多维度的网络数据和所述位置栅格确定模块确定的位置栅格信息，对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析，确定发生所述网络异常事件的位置栅格存在的网络问题。
所述装置还包括：数据预处理模块，设置为对所述数据获取模块获取的多维度的网络数据进行筛选的预处理；所述数据分析模块具体设置为：根据所述预处理模块预处理后的多维度的网络数据和所述位置栅格确定模块确定的位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析，确定发生所述网络异常事件的位置栅格存在的网络问题。
所述数据分析模块具体包括：告警分析子模块、容量分析子模块、覆盖分析子模块和无线参数分析子模块，则所述数据分析模块具体设置为根据预处理后的多维度的网络数据和所述栅格信息对发生所述网络异常事件的位置栅格进行包括以下至少一种网络数据分析：告警分析、容量分析、覆盖分析和无线参数分析。
所述数据分析模块分析得到发生所述网络异常事件的位置栅格存在的网络问题具体包括：若分析结果存在所述告警分析、容量分析、覆盖分析和无线参数分析中的至少两种网络问题，则根据预设优先级选择优先级最高的网络问题作为发生所述网络异常事件的位置栅格存在的网络问题。
所述装置还包括区域排序模块，所述区域排序模块具体包括：汇集处理子模块，设置为将所述数据分析模块分析出的所述网络中各区域内对应的位置栅格中的结果进行至少一种维度的汇集处理；区域排序子模块，设置为根据所述汇集处理子模块处理后的结果对所述各区域进行区分维度的网络问题排序。
本发明实施例提供了一种网络关联分析方法及装置，通过获取网络中的CDT数据和多维度的网络数据，根据CDT数据查找网络异常事件，并确定发生该网络异常事件的栅格信息后，对发生该网络异常事件的栅格进行至少一种维度的网络数据分析，得到发生网络异常事件的栅格存在的网络问题。本方案主要是通过CDT数据获取发生网络异常事件的栅格信息后，再对该栅格进行至少一种维度的数据分析，通过这种关联分析，能够更加准确地得到发生网络异常事件的栅格最可能存在的网络问题，以辅助网优工程师快速查找问题，为网络的维护及正常运行提供了较优的方法。
进一步地，对发生网络异常事件的栅格分别进行以下分析：告警分析、容量分析、覆盖分析和无线参数分析，并按照预设优先级从高到低分析出该栅格存在网络问题。这样，通过关联的方式，且从多种维度来对网络中的发生网络异常事件的栅格进行分析，使得得到的分析结果能够更加准确合理，且快速，让网优工程师能够第一时间对网络中存在问题的栅格进行相应的处理，方便了网优工程师的工作，节省了资源的浪费。
附图说明
图1为本发明实施例一提供的网络关联分析方法的流程图；
图2为本发明实施例二提供的网络关联分析装置的结构示意图。
具体实施方式
下面通过具体实施方式结合附图对本发明作进一步详细说明。
如图1所示为本发明实施例一提供的网络关联分析方法的示意图，请参见图1，该方法包括：
S101：获取网络中的呼叫详细跟踪数据及多维度的网络数据。所述呼叫详细跟踪数据包括：话单数据、跟踪接入系统的每一次呼叫的关键性数据以及接入过程中，系统针对该用户接入进行处理过程的关键性数据。即CDT数据反映了系统的真实状况是通话时的无线环境和系统状况的快照。通过对网络中的CDT数据进行分析，可以获取到每一个用户的每一次网络呼叫详情；所述多个维度的网络数据具体包括：工参数据、配置数据、性能数据、告警数据和DT/CQT数据等；该获取网络数据的步骤可以是定时获取也可以是主动操作获取等，如设置每5分钟获取一次。
S102：在所述呼叫详细跟踪数据中查找网络异常事件，并确定发生所述网络异常事件的位置栅格信息。具体地，以CDT数据中的话单为基础，通过掉话、接入、质量差(速率低)等专题评估，找出网络异常事件，并通过CDT话单定位算法，将异常事件定位于某个位置栅格中。这样，通过对所述获取的CDT数据进行分析，从而可以得到哪一个用户出现了网络异常事件；并通过CDT定位算法计算出该网络异常事件发生的位置栅格；所述发生网络异常事件具体包括：发生掉话、接入故障或覆盖较弱等异常问题；所述位置栅格表示的是网络区域中最小的空间单位。
S103：根据获取的多维度的网络数据和所述位置栅格信息，对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析，得到发生所述网络异常事件的位置栅格存在的网络问题。具体地，对发生网络异常事件的位置栅格进行以下至少一种网络数据分析：告警分析、容量分析、覆盖分析和无线参数分析。其中，得到发生所述网络异常事件的位置栅格存在的网络问题具体包括：若分析结果存在所述告警分析、容量分析、覆盖分析和无线参数分析中的至少两种网络问题，则根据预设优先级选择优先级最高的网络问题作为发生所述网络异常事件的位置栅格存在的网络问题。具体地，
所述告警分析具体包括：通过发生网络异常事件的RNC(Radio Network Controller，无线网络控制器)和其所在的小区标识CellID关联查询告警标识(Identification，ID)，如果存在引起发生网络异常事件的告警ID时，即存在关联告警问题时，输出异常分析大类为设备问题，并在详细原因说明中给出具体设备，所述关联告警问题包括如下：上行低功率、载波的基带低功率、载波低功率预告警、RRU(Radio Remote Unit，射频拉远单元)载波低功率预告警、全球定位系统(Global Positioning System，GPS)处于搜星状态、GPS相位偏差过大、GPS天馈开路、HDLC(High-Level Data Link Control，高级数据链路控制)链路异常、过去15分钟内中继链路误码水平超过阈值、中继帧丢失、中继线不可用、中继告警指示信号、PPP(Public-Private-Partnership，公私合作模式)链路故障和PPP链路HDLC故障等；若在对发生网络异常事件的位置栅格中进行告警分析时，存在上述关联告警问题，则可认为该位置栅格存在设备问题。
所述容量分析具体包括：通过发生网络异常事件的RNC和小区标识CellID关联查询基站，核心网当时的容量信息，如果容量达到上限，输出异常分析大类为容量问题，并在详细原因说明中给出具体容量瓶颈设备。容量分析指标包括：系统容量负荷评估、BHCA(Busy Hour Call Attempt，忙时试呼次数交换机目标处理能力)维度资源过载分析、ERL(话务单单位)维度资源过载比例分析、1X和DO载扇过载比例分析、基站侧主要业务板和控制板的过载分析、框间控制流过载分析，接口板的过载分析，业务处理单元资源利用率分析等。
所述覆盖分析具体包括：结合发生网络异常事件的经纬度、信号强度依次分析弱覆盖、干扰、导频污染，越区覆盖输出异常分析大类，并分析出问题的源小区或者目标小区：1)当事件发生时UE接入EC/Io(Energy per Chip平均码片能量/the Total Interference density总干扰功率谱密度)值小于指定门限N时，判定为弱覆盖；2)当事件放生时RAB(Radio Access Bearer，无线接入承载)忙比例小于预定门限(默认 为10％)；RSSI(Received Signal Strength Indication，接收的信号强度指示)高于预定门限(默认为-95dBm)判定为干扰；3)当事件发生时UE接收到导频个数大于等于3；且最强与最弱导频强度差不大于指定门限M时，判定为导频污染。
所述无线参数分析具体包括：结合发生网络异常事件RNC和小区ID，关联无线配置参数，分析小区配置参数取值是否异常。分析指标如下表所示：
Figure PCTCN2015088293-appb-000001
Figure PCTCN2015088293-appb-000002
对发生网络异常事件的位置栅格中的网络数据进行上述分析后，若同一个网络异常事件在上述分析中存在两个或者两个以上上述网络问题时，最终该发生网络异常事件的位置栅格存在的网络问题将按照预设的优先级选择优先级最高的网络问题进行显示。优选地，根据网优专家多年经验和外场大量验证，所述网络问题的优先级从高到低依次为：告警分析、容量分析、覆盖分析、无线参数分析；需要说明的是，对于一些特殊情况或者特殊的网络，可能也会存在其他优先级的排位情况，本方案中并不局限于该种优先级的排位情况。
在进行步骤S101获取网络中的呼叫详细跟踪数据及多维度的网络数据后，还包括：对所述多维度的网络数据进行筛选的预处理；即对所获取的多维度的网络数据进行各种维度内的筛选处理，如，可以设置定时对获取到的多维度的网络数据进行筛选处理，只需选择其对于各维度的网络数据分析时有用的网络数据即可，对网络数据进行精简，减少数据存储空间，保存在指定的FTP(File Transfer Protocol，文件传输协议)(存储计算机)服务器中。对多维度数据进行预处理后，步骤S103根据获取的多维度的网络数据和所述位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析具体包括：根据预处理后的多维度的网络数据和所述位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析。即在对发生网络异常事件的位置栅格进行至少一种维度的网络数据分析前，对其各种维度的网络数据先进行预处理，这样对于其网络数据的分析将大大缩短其分析时间，为网优工程师快速做出解决方案节省了时间。
另外，还包括：将所述网络中各区域内对应的位置栅格中的分析结果进行至少一种维度的汇集处理；根据所述汇集处理后的结果对所述各区域进行区分维度的网络问题排序。具体包括：完成多维度关联分析之后，以位置栅格为维度对发生网络异常事件和网络信号质量进行聚合分析，依次分析出问题位置栅格、问题位置栅格TOPN小区(对网络中各区域进行区分维度的网络问题排序)，问题原因栅格分析。具体地：
所述问题位置栅格的评估包括：接入成功率未达到预设门限N1的判定为接入失败栅格；掉话率达到门限N2的判定为掉话栅格；弱覆盖点数占总点数比例达到门限N3的判定为弱覆盖删格；越区覆盖点数占总点数比例达到门限N4时判定为越区覆盖栅格。
所述问题位置栅格TOPN小区：问题位置栅格被判定为弱覆盖时，统计出所有弱覆盖点的主小区，依次按照每个小区在本栅格产生弱覆盖点数从多到少排序，统计出TOPN的弱覆盖小区；问题位置栅格判定为越区覆盖时，统计出引起越区覆盖的源小区，并依次根据越区覆盖源小区在本问题位置栅格产生越区覆盖点数从多到少排序， 统计出TOPN越区覆盖小区；问题位置栅格判定为导频污染时，统计出引起导频污染的小区，并依次根据越区覆盖小区在本栅格产生越区覆盖点数从多到少排序，统计出TOPN的导频污染小区。
所述问题原因位置栅格分析：问题位置栅格判定为掉话栅格时，分别统计出掉话原因：设备问题、覆盖问题、容量问题或无线问题；在位置栅格内导致掉话次数，并从多到少进行排序，统计出TOPN问题原因；同样地，对于判断所述发生网络异常事件为接入失败或信号质量差的位置栅格分析方法和掉话位置栅格分析相同。
例如，下面以实际例子对本方案进行说明：某UE(移动终端)在2013年12月20号下午3:20在“8_28_0五牛新厂房”小区下发生掉话现象，网元会实时生成UE掉话事件CDT话单，话单中包含掉话时服务小区信息，主邻小区信号强度。告警分析：通过小区RNC和小区标识(CellID)关联同时段内告警数据，发现该小区存在“低功率异常”的告警码，告警分析流程判别该掉话为设备故障；容量分析：通过小区RNC和小区CellID关联查询基站、核心网当时的容量信息，发现无问题；覆盖分析：通过分析CDT数据中经纬度、信号强度等参数，判别为覆盖问题的弱覆盖，并且可排除干扰和导频污染问题；无线参数分析：通过小区RNC和小区标识CellID关联无线配置参数发现无参数配置问题；综合分析：根据总流程设定的优先级由高到低：告警、容量、覆盖、无线参数，判定该掉话的原因是设备故障。问题区域定位功能统计2013年12月20号下午3点～4点内异常CDT话单，并把该掉话事件统计到发生时间经纬度所在位置栅格中。
如图2所示，为本发明实施例二提供的网络关联分析装置的结构示意图，请参见图2，所述网络关联分析装置20包括：数据获取模块201、位置栅格确定模块202和数据分析模块203；所述数据获取模块201设置为获取网络中的呼叫详细跟踪数据及多维度的网络数据；所述位置栅格确定模块202设置为在所述数据获取模块201获取的呼叫详细跟踪数据中查找网络异常事件，并确定发生所述网络异常事件的位置栅格信息；所述数据分析模块203设置为根据所述数据获取模块201获取的多维度的网络数据和所述位置栅格确定模块202确定的位置栅格信息，对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析，确定发生所述网络异常事件的位置栅格存在的网络问题。通过本装置的设置使得网络工程师能够更加准确地判断网络中发生网络异常事件的实际网络问题。
在该实施例中，所述网络关联分析装置20还包括：数据预处理模块，设置为对所述数据获取模块获取的多维度的网络数据进行筛选的预处理；所述数据分析模块具体设置为：根据所述预处理模块预处理后的多维度的网络数据和所述位置栅格确定模块 确定的位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析，确定发生所述网络异常事件的位置栅格存在的网络问题。通过将该网络关联分析装置20所获取的多维度的网络数据进行筛选地预处理后，将不需要的数据进行剔除，再进行各种维度的数据分析，使得在对数据进行分析时，提高了其分析的速度，能够更加快速地得到其网络问题，方便网优工程师的处理。
在该实施例中，所述数据分析模块203具体包括：告警分析子模块、容量分析子模块、覆盖分析子模块和无线参数分析子模块，则所述数据分析模块具体设置为根据预处理后的多维度的网络数据和所述栅格信息对发生所述网络异常事件的位置栅格进行包括以下至少一种网络数据分析：告警分析、容量分析、覆盖分析和无线参数分析。若分析结果存在所述告警分析、容量分析、覆盖分析和无线参数分析中的至少两种网络问题，则根据预设优先级选择优先级最高的网络问题作为发生所述网络异常事件的位置栅格存在的网络问题。优选地，所述优先级从高到低依次为：告警分析、容量分析、覆盖分析和无线参数分析。
所述网络关联分析装置20还包括区域排序模块，所述区域排序模块具体包括：汇集处理子模块，设置为将所述数据分析模块分析出的所述网络中各区域内对应的位置栅格中的结果进行至少一种维度的汇集处理；区域排序子模块，设置为根据所述汇集处理子模块处理后的结果对所述各区域进行区分维度的网络问题排序。通过对网络中各区域的网络质量进行排序，使得人们能够更加了解本网络中的网络质量情况，对于需要提高本网络中的网络质量问题将会得到比较好的解决方案，提高可网优工程师的工作质量和效率。
本发明实施例提供了一种网络关联分析方法及装置，以CDT数据为基础，通过对CDT数据分析出网络异常事件，并确定发生该网络异常事件的栅格信息后，对发生该网络异常事件的栅格进行至少一种维度的网络数据分析，得到发生网络异常事件的栅格存在的网络问题。本方案是对网络中的CDT数据与其他维度的网络数据进行关联分析，通过这种关联分析，能够更加准确地得到发生网络异常事件的栅格最可能存在的网络问题，以辅助网优工程师查找问题，为网络的维护及正常运行提供了解决方法。
以上内容是结合具体的实施方式对本发明所作的进一步详细说明，不能认定本发明的具体实施只局限于这些说明。对于本发明所属技术领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干简单推演或替换，都应当视为属于本发明的保护范围。
工业实用性
如上所述，本发明实施例提供的一种网络关联分析方法及装置，具有以下有益效果：通过CDT数据获取发生网络异常事件的栅格信息后，再对该栅格进行至少一种维度的数据分析，通过这种关联分析，能够更加准确地得到发生网络异常事件的栅格最可能存在的网络问题，以辅助网优工程师快速查找问题，为网络的维护及正常运行提供了较优的方法。
进一步地，对发生网络异常事件的栅格分别进行以下分析：告警分析、容量分析、覆盖分析和无线参数分析，并按照预设优先级从高到低分析出该栅格存在网络问题。这样，通过关联的方式，且从多种维度来对网络中的发生网络异常事件的栅格进行分析，使得得到的分析结果能够更加准确合理，且快速，让网优工程师能够第一时间对网络中存在问题的栅格进行相应的处理，方便了网优工程师的工作，节省了资源的浪费。

Claims (10)

  1. 一种网络关联分析方法，包括：
    获取网络中的呼叫详细跟踪数据及多维度的网络数据；
    在所述呼叫详细跟踪数据中查找网络异常事件，并确定发生所述网络异常事件的位置栅格信息；
    根据获取的多维度的网络数据和所述位置栅格信息，对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析，得到发生所述网络异常事件的位置栅格存在的网络问题。
  2. 根据权利要求1所述的网络关联分析方法，其中，所述获取网络中的呼叫详细跟踪数据及多维度的网络数据后，还包括：对所述多维度的网络数据进行筛选的预处理；
    所述根据获取的多维度的网络数据和所述位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析具体包括：根据预处理后的多维度的网络数据和所述位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析。
  3. 根据权利要求2所述的网络关联分析方法，其中，根据预处理后的多维度的网络数据和所述位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析具体包括：根据预处理后的多维度的网络数据和所述位置栅格信息对发生所述网络异常事件的位置栅格进行包括以下至少一种网络数据分析：告警分析、容量分析、覆盖分析和无线参数分析。
  4. 根据权利要求3所述的网络关联分析方法，其中，得到发生所述网络异常事件的位置栅格存在的网络问题具体包括：若分析结果存在所述告警分析、容量分析、覆盖分析和无线参数分析中的至少两种网络问题，则根据预设优先级选择优先级最高的网络问题作为发生所述网络异常事件的位置栅格存在的网络问题。
  5. 根据权利要求1-4任一项所述的网络关联分析方法，其中，还包括：将所述网络中各区域内对应的位置栅格中的分析结果进行至少一种维度的汇集处理；根据所述汇集处理后的结果对所述各区域进行区分维度的网络问题排序。
  6. 一种网络关联分析装置，包括：
    数据获取模块，设置为获取网络中的呼叫详细跟踪数据及多维度的网络数据；
    位置栅格确定模块，设置为在所述数据获取模块获取的呼叫详细跟踪数据中查找网络异常事件，并确定发生所述网络异常事件的位置栅格信息；
    数据分析模块，设置为根据所述数据获取模块获取的多维度的网络数据和所述位置栅格确定模块确定的位置栅格信息，对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析，确定发生所述网络异常事件的位置栅格存在的网络问题。
  7. 根据权利要求6所述的网络关联分析装置，其中，还包括：数据预处理模块，设置为对所述数据获取模块获取的多维度的网络数据进行筛选的预处理；所述数据分析模块具体设置为：根据所述预处理模块预处理后的多维度的网络数据和所述位置栅格确定模块确定的位置栅格信息对发生所述网络异常事件的位置栅格进行至少一种维度的网络数据分析，确定发生所述网络异常事件的位置栅格存在的网络问题。
  8. 根据权利要求7所述的网络关联分析装置，其中，所述数据分析模块具体包括：告警分析子模块、容量分析子模块、覆盖分析子模块和无线参数分析子模块，则所述数据分析模块具体设置为根据预处理后的多维度的网络数据和所述栅格信息对发生所述网络异常事件的位置栅格进行包括以下至少一种网络数据分析：告警分析、容量分析、覆盖分析和无线参数分析。
  9. 根据权利要求8所述的网络关联分析装置，其中，所述数据分析模块分析得到发生所述网络异常事件的位置栅格存在的网络问题具体包括：若分析结果存在所述告警分析、容量分析、覆盖分析和无线参数分析中的至少两种网络问题，则根据预设优先级选择优先级最高的网络问题作为发生所述网络异常事件的位置栅格存在的网络问题。
  10. 根据权利要求7-9任一项所述的网络关联分析装置，其中，还包括区域排序模块，所述区域排序模块具体包括：汇集处理子模块，设置为将所述数据分析模块分析出的所述网络中各区域内对应的位置栅格中的结果进行至少一种维度的汇集处理；区域排序子模块，设置为根据所述汇集处理子模块处理后的结果对所述各区域进行区分维度的网络问题排序。
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018001141A1 (zh) * 2016-06-28 2018-01-04 中兴通讯股份有限公司 一种质差区域分析的方法、装置及系统
CN109191021A (zh) * 2018-10-30 2019-01-11 全球能源互联网研究院有限公司 电网异常事件的关联规则匹配方法及装置
CN109389181A (zh) * 2018-10-30 2019-02-26 全球能源互联网研究院有限公司 电网异常事件的关联规则生成方法及装置
CN109996271A (zh) * 2017-12-31 2019-07-09 中国移动通信集团四川有限公司 数据流量损失情况的分析方法、装置、设备及介质
CN114245407A (zh) * 2021-12-30 2022-03-25 中国联合网络通信集团有限公司 网络优化方法、装置、设备及存储介质
CN115396908A (zh) * 2022-08-25 2022-11-25 中国联合网络通信集团有限公司 网络评估方法、装置及存储介质

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109600761B (zh) * 2017-09-30 2021-01-15 华为技术有限公司 无线通信的方法
CN110121189B (zh) * 2018-02-05 2021-08-20 大唐移动通信设备有限公司 一种网络监控方法和装置
CN110545557B (zh) * 2018-05-28 2023-04-07 中国移动通信集团设计院有限公司 一种VoLTE问题分析方法、装置、电子设备及存储介质
CN110555452A (zh) * 2018-06-04 2019-12-10 北京亿阳信通科技有限公司 一种基于智能聚类的网络问题处理方法及装置
CN111294841B (zh) * 2018-12-07 2023-08-18 中国移动通信集团陕西有限公司 一种无线网络问题的处理方法、装置及存储介质
CN111328014B (zh) * 2018-12-17 2021-10-01 中国移动通信集团北京有限公司 一种定位移动掉话的方法及装置
CN111385116B (zh) * 2018-12-29 2023-07-14 北京亿阳信通科技有限公司 一种高干扰小区的多维关联特征分析方法和装置
CN112954728B (zh) * 2019-12-11 2023-04-07 中国移动通信集团山东有限公司 一种网络厚度评估方法、装置、存储介质和计算机设备

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101848482A (zh) * 2010-03-26 2010-09-29 浙江大学 一种获取干扰矩阵的方法和装置
CN101925101A (zh) * 2009-06-09 2010-12-22 中兴通讯股份有限公司 一种用户呼叫过程信息采集及统计分析的方法及装置
CN103138963A (zh) * 2011-11-25 2013-06-05 华为技术有限公司 一种基于用户感知的网络问题定位方法及装置
CN103731851A (zh) * 2014-01-15 2014-04-16 中国移动通信集团陕西有限公司 网络性能测评的方法和装置

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101039490B (zh) * 2006-03-14 2010-06-16 中国电信股份有限公司 用于移动通信系统网络优化的覆盖分析系统及方法
US8838774B2 (en) * 2007-08-21 2014-09-16 Inmon Corporation Method, system, and computer program product for identifying common factors associated with network activity with reduced resource utilization
CN101835182A (zh) * 2010-02-04 2010-09-15 西安方诚通讯技术服务有限公司 一种无线网络优化计算机分析系统及分析方法
CN102571407A (zh) * 2010-12-30 2012-07-11 中国移动通信集团河北有限公司 告警关联分析方法及装置
CN103067928B (zh) * 2012-12-04 2015-09-30 大唐移动通信设备有限公司 一种网络覆盖质量的分析方法和系统

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101925101A (zh) * 2009-06-09 2010-12-22 中兴通讯股份有限公司 一种用户呼叫过程信息采集及统计分析的方法及装置
CN101848482A (zh) * 2010-03-26 2010-09-29 浙江大学 一种获取干扰矩阵的方法和装置
CN103138963A (zh) * 2011-11-25 2013-06-05 华为技术有限公司 一种基于用户感知的网络问题定位方法及装置
CN103731851A (zh) * 2014-01-15 2014-04-16 中国移动通信集团陕西有限公司 网络性能测评的方法和装置

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018001141A1 (zh) * 2016-06-28 2018-01-04 中兴通讯股份有限公司 一种质差区域分析的方法、装置及系统
CN109996271A (zh) * 2017-12-31 2019-07-09 中国移动通信集团四川有限公司 数据流量损失情况的分析方法、装置、设备及介质
CN109996271B (zh) * 2017-12-31 2022-04-08 中国移动通信集团四川有限公司 数据流量损失情况的分析方法、装置、设备及介质
CN109191021A (zh) * 2018-10-30 2019-01-11 全球能源互联网研究院有限公司 电网异常事件的关联规则匹配方法及装置
CN109389181A (zh) * 2018-10-30 2019-02-26 全球能源互联网研究院有限公司 电网异常事件的关联规则生成方法及装置
CN109389181B (zh) * 2018-10-30 2020-11-24 全球能源互联网研究院有限公司 电网异常事件的关联规则生成方法及装置
CN109191021B (zh) * 2018-10-30 2021-02-09 全球能源互联网研究院有限公司 电网异常事件的关联规则匹配方法及装置
CN114245407A (zh) * 2021-12-30 2022-03-25 中国联合网络通信集团有限公司 网络优化方法、装置、设备及存储介质
CN115396908A (zh) * 2022-08-25 2022-11-25 中国联合网络通信集团有限公司 网络评估方法、装置及存储介质
CN115396908B (zh) * 2022-08-25 2023-09-08 中国联合网络通信集团有限公司 网络评估方法、装置及存储介质

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