WO2021115116A1 - Early-warning method and apparatus for performance indicator, and device and storage medium - Google Patents
Early-warning method and apparatus for performance indicator, and device and storage medium Download PDFInfo
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
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Definitions
- the embodiments of the present application relate to the field of communication technology, and in particular, to an early warning method, device, equipment, and storage medium for performance indicators.
- KPI key performance indicators
- the communication system can be measured according to KPI indicators such as traffic, connection rate, or dropped call rate.
- the running state is good or bad.
- the deterioration of KPI indicators usually has two forms: one is a rapid decline, that is, the KPI indicators have a large change in a short period of time; the other is a slow decline, that is, the KPI indicators have a large difference in a longer period of time.
- the traditional way is to measure the operating status of the communication system by manually observing the changes of KPI indicators on a regular basis, which not only increases the manpower, but also fails to understand the operating status of the communication system in time.
- the embodiments of the present application provide an early warning method, device, equipment, and storage medium for performance indicators, so as to solve the problem of not being able to understand the operating status of the communication system in time to at least a certain extent.
- an embodiment of the present application provides an early warning method for a performance indicator, which includes: determining predicted data of the performance indicator within a set time period based on historical data of the performance indicator; and based on the predicted data and the performance The difference between the actual data of the indicator in the set time period is determined, and the change trend curve of the difference is determined; if the difference reaches the corresponding difference threshold in the change trend curve and the duration is less than the set duration, then it is determined The performance index is degraded.
- an embodiment of the present application also provides an early warning device for a performance indicator, including: a prediction data determining module, configured to determine the predicted data of the performance indicator in a set time period according to the historical data of the performance indicator; and a curve;
- the determining module is used to determine the change trend curve of the difference according to the difference between the predicted data and the actual data of the performance index in a set time period;
- the performance index deterioration determining module is used to determine if the difference is When the time period when the value reaches the corresponding difference threshold in the change trend curve is less than the set time period, it is determined that the performance index is degraded.
- an embodiment of the present application also provides a device, including: one or more processors; a memory, used to store one or more programs; when the one or more programs are used by the one or more When the processor is executed, the one or more processors implement the early warning method of the performance index as described in the first aspect.
- an embodiment of the present application also provides a storage medium on which a computer program is stored, and when the program is executed by a processor, the early warning method of the performance index as described in the first aspect is realized.
- FIG. 1 is a flowchart of an early warning method for performance indicators provided by an embodiment of the application
- FIG. 3 is a schematic diagram of a variation trend curve of a difference provided by an embodiment of the application.
- FIG. 4 is an implementation flowchart of an early warning method for performance indicators provided by an embodiment of the application.
- FIG. 5 is a structural diagram of a performance indicator early warning device provided by an embodiment of the application.
- Fig. 6 is a structural diagram of a device provided by an embodiment of the application.
- Figure 1 is a flow chart of an early warning method for performance indicators provided by an embodiment of the application.
- This embodiment is suitable for intelligent monitoring of changes in performance indicators, especially for monitoring changes in performance indicators in unattended communication systems.
- the method can be implemented by an early warning device of performance indicators, which can be implemented in software and/or hardware and integrated in a computer and other equipment. With reference to Figure 1, the method includes the following steps:
- S110 According to the historical data of the performance indicator, determine the predicted data of the performance indicator within a set time period.
- the performance index is called KPI index.
- the KPI index can be determined according to the measured content. For example, when measuring the operating status of the communication system, the traffic, the connection rate, the traffic volume, or the dropped call rate can be used as the KPI index.
- the historical data of the KPI indicator is the data of the KPI indicator in the historical time period. Among them, the size of the historical time period affects the accuracy of the predicted data. For example, if the historical time period is too small, it is easy to cause insufficient information, which makes the predicted data and the actual value If the historical time period is too large, it will not only increase the processing complexity and processing time, but also increase the risk of over-fitting, which will also cause a large deviation between the predicted data and the actual value.
- the historical time period in this embodiment takes 7 days as an example, that is, the historical data is the data of the KPI indicator within 7 days before the current time.
- the predicted data is the data corresponding to the KPI indicator in the set time period after the current time.
- the KPI indicator in the communication system has periodic characteristics, that is, it changes regularly within 24 hours.
- the set time period is 24 hours. , That is, according to historical data, determine the data of KPI indicators within 24 hours after the current time as forecast data.
- the size of the set time period can be used to determine the amount of forecast data on the one hand, and can be used to determine the time point of the next cycle on the other hand.
- the triple exponential smoothing algorithm can be used to predict the data of the KPI indicator in the next 24 hours in combination with historical data.
- the Holt-Winters algorithm can predict time series that contain both trend and seasonality, and meets the trend and seasonality characteristics of KPI indicators such as traffic and traffic in the communication system.
- the historical data of KPI indicators can be substituted into the Holt-Winters algorithm, the parameters included in the Holt-Winters algorithm can be obtained by fitting, and the KPI indicators in the next 24 hours can be predicted according to the fitted parameter values to obtain the prediction data.
- S120 Determine a change trend curve of the difference according to the difference between the predicted data and the actual data of the performance indicator in a set time period.
- the actual data of the KPI indicator is the actual data of the KPI indicator in the set time period. According to the forecast data and actual data, the difference between the KPI indicators in the set time period can be determined. In order to understand the change of KPI indicators in advance, the operation and maintenance personnel are notified in time before the risk of the communication system occurs. The embodiment predicts the change trend of the difference according to the difference between the predicted data of the KPI indicator and the actual data, and obtains the change trend of the difference. curve.
- the curve fitting method may be combined with the difference value within a set time period to obtain the change trend curve of the difference value, wherein the curve fitting method may be the least square method.
- the least square method also known as the least square method, is a commonly used curve fitting method.
- the embodiment does not limit the specific fitting process.
- the difference is predicted on the basis of the difference, and the change trend curve of the difference is obtained.
- the change trend curve the change of the KPI index can be predicted in advance, so that when the deterioration of the KPI index is predicted, the operator is notified in advance. Maintenance personnel deal with it, reducing the risk.
- the change trend curve reflects the change of the difference over time, and each difference corresponds to a time point.
- the difference threshold is a point in the change trend curve.
- the multiple differences are arranged in chronological order, and the difference at the last time point is used as the basis for whether the KPI indicator has deteriorated. That is, if the time period during which the difference value corresponding to the last time point in the set time period reaches the difference value threshold is less than the set time period, it is determined that the KPI indicator is degraded.
- the alarm information of the deterioration of the KPI indicator may be sent to the terminal corresponding to the operation and maintenance personnel in a short message or email, so that the operation and maintenance personnel can take measures in advance to eliminate alarms and potential safety hazards.
- the embodiment of the present application provides an early warning method for performance indicators.
- the predicted data of the performance indicators within a set time period is determined, and the predicted data of the performance indicators are within the set time period based on the predicted data and the performance indicators.
- Determine the change trend curve of the difference value by the difference value of the actual data if the difference value reaches the corresponding difference value threshold in the change trend curve for a duration less than the set duration, then determine that the performance index is degraded.
- the embodiment of the application does not need to manually check regularly, which saves manpower, and can predict the change trend of the difference based on the historical data and actual data of the performance indicator, predict the change of the performance indicator in advance, and timely understand the operating status of the communication system corresponding to the performance indicator .
- the prediction data of the KPI indicator within a set time period can be determined in the following manner:
- the predicted data of the performance index in a set time period is determined.
- the prediction algorithm of this embodiment takes the Holt-Winters algorithm as an example.
- the Holt-Winters algorithm contains three parameters to be fitted, namely ⁇ , ⁇ , and ⁇ . ⁇ , ⁇ , and ⁇ are between 0-1. According to history The data can be fitted to the specific values of ⁇ , ⁇ and ⁇ . When ⁇ , ⁇ , and ⁇ are determined, substitute the Holt-Winters algorithm to predict the data of the KPI indicator in the future set time period.
- the embodiment does not limit the fitting process of ⁇ , ⁇ , and ⁇ .
- Fig. 2 is a flowchart of another early warning method for performance indicators provided by an embodiment of the application.
- the method includes the following steps:
- S210 According to the historical data of the performance indicator, determine the predicted data of the performance indicator within a set time period.
- S220 Acquire actual data of the performance index at every set time interval within the set time period.
- the actual data of the KPI indicator is acquired at a set time interval as the actual data of the KPI indicator. In some embodiments, it can be obtained every 15 minutes, so that multiple actual data within a set time period can be obtained.
- S230 Determine respectively the difference between the actual data and the predicted data at the time points corresponding to the actual data.
- the difference between the predicted data and the actual data at that point in time is calculated to obtain multiple differences.
- the embodiment records each actual data as a point.
- S240 Determine a fitting curve of the difference according to each of the difference and the curve fitting algorithm, as a change trend curve of the difference.
- the change trend curve of the difference it can be determined according to the obtained differences, or a part of the difference can be selected from it.
- the embodiment takes the partial difference as an example.
- the differences can be arranged in the order of time points, and the differences corresponding to the last three time points are selected as the change.
- the curve fitting algorithm takes the least square method as an example.
- S240 includes:
- a polynomial fitting curve is determined as the fitting curve of the difference.
- the polynomial parameters of the least squares method can be determined according to the size of the selected three differences, combined with the least square method, and the polynomial parameters are substituted into the equation corresponding to the least square method to obtain the corresponding polynomial fitting equation, and draw the polynomial Fit the curve corresponding to the equation to obtain a polynomial fitting curve.
- the least square method can be used to fit the trend of the difference value, thereby predicting the time limit for exceeding the limit, and assisting the operation and maintenance personnel in decision-making, which not only reduces labor intensity, but also improves work efficiency.
- FIG. 3 is a schematic diagram of a variation trend curve of a difference provided by an embodiment of the application.
- the curve in Figure 3 is the difference change trend curve obtained by fitting the least square method and difference A, difference B and difference C.
- the time points corresponding to difference A, difference B and difference C are respectively t1 , T2 and t3, the time point corresponding to the difference threshold M is t0.
- the embodiment uses the time length of the time point t3 corresponding to the difference value C and the time point t0 corresponding to the difference value threshold M as the basis to determine whether the KPI indicator has deteriorated. Specifically, if the time period from t3 to t0 is less than the set time period, the KPI indicator is considered to be degraded, otherwise, the KPI indicator is considered to be normal.
- the early warning information of the deterioration of the KPI indicator is automatically pushed to the operation and maintenance personnel to notify the operation and maintenance personnel to deal with it in time and reduce the risk.
- the early warning method for performance indicators provided in the embodiments of this application is based on the above embodiments, according to the difference between the predicted data and the actual data in a set time period, combined with the curve fitting algorithm to obtain the change trend curve of the difference, which realizes
- the prediction of the difference can predict in advance whether the KPI indicator will deteriorate, which not only reduces labor intensity and improves work efficiency, but also informs the operation and maintenance personnel to deal with it in time before the KPI indicator deteriorates, reducing the risk.
- Fig. 4 is an implementation flowchart of a performance indicator warning method provided by an embodiment of the application.
- Figure 4 takes the prediction algorithm as the Holt-Winters algorithm, and the curve fitting algorithm takes the least square method as an example.
- the acquired historical data of the KPI indicator is predicted to obtain the predicted data of the KPI indicator in a set time period, and the difference between the predicted data and the actual data of the KPI indicator in the set time period is made , Get a finite number of differences, and then predict the change trend of the difference according to the difference of the last three times and the least square method, and get the change trend curve.
- the difference threshold and the time point corresponding to the last difference get the latest The time when the difference reaches the difference threshold. If the time is less than the set time, the KPI indicator is determined to be degraded, and the early warning information of the KPI indicator degradation is displayed to notify the operation and maintenance personnel to deal with it in time.
- Fig. 5 is a structural diagram of an early warning device with performance indicators provided by an embodiment of the application.
- the device can execute the early warning method of performance indicators described in the foregoing embodiment. Referring to FIG. 5, the device includes:
- the forecast data determining module 510 is configured to determine the forecast data of the performance index in a set time period according to the historical data of the performance index;
- the curve determination module 520 is configured to determine the change trend curve of the difference according to the difference between the predicted data and the actual data of the performance index in a set time period;
- the performance index deterioration determining module 530 is configured to determine that the performance index is deteriorated if the time period during which the difference value reaches the corresponding difference value threshold in the change trend curve is less than a set time period.
- the embodiment of the present application provides an early warning device for a performance indicator, which determines the predicted data of the performance indicator in a set time period according to historical data of the performance indicator, and determines the predicted data of the performance indicator in a set time period according to the predicted data and the performance indicator. Determine the change trend curve of the difference value by the difference value of the actual data, if the difference value reaches the corresponding difference value threshold in the change trend curve for a duration less than the set duration, then determine that the performance index is degraded.
- the embodiment of the application does not need to manually check regularly, which saves manpower, and can predict the change trend of the difference based on the historical data and actual data of the performance indicator, predict the change of the performance indicator in advance, and timely understand the operating status of the communication system corresponding to the performance indicator .
- the prediction data determining module 510 is specifically configured to:
- the predicted data of the performance index in a set time period is determined.
- the curve determination module 520 includes:
- the actual data acquisition unit is configured to acquire the actual data of the performance index at every set time interval within the set time period;
- the difference determining unit is used to determine the difference between each of the actual data and the predicted data at the time point corresponding to the actual data;
- the curve determination unit is configured to determine the fitting curve of the difference according to each of the difference and the curve fitting algorithm, as the change trend curve of the difference.
- the curve determination unit is specifically used for:
- a polynomial fitting curve is determined as the fitting curve of the difference.
- the performance index deterioration determining module 530 is specifically configured to:
- the device further includes:
- the information display module is configured to display the early warning information of the performance index deterioration after the performance index deterioration is determined.
- the early-warning device for performance indicators provided in the embodiments of the present application can execute the early-warning method for performance indicators provided in the above-mentioned embodiments of the present application, and has the corresponding functional modules and beneficial effects of the execution method.
- Fig. 6 is a structural diagram of a device provided by an embodiment of the application.
- the device includes a processor 610, a memory 620, an input device 630, and an output device 640.
- the number of processors 610 in the device may be one or more. In FIG. 6, one processor 610 is taken as an example.
- the processor 610, the memory 620, the input device 630, and the output device 640 may be connected by a bus or other methods. In FIG. 6, the connection by a bus is taken as an example.
- the memory 620 can be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the early warning method of performance indicators in the embodiments of the present application.
- the processor 610 executes various functional applications and data processing of the device by running the software programs, instructions, and modules stored in the memory 620, that is, realizes the early warning method of the performance indicators of the foregoing embodiments.
- the memory 620 mainly includes a program storage area and a data storage area.
- the program storage area can store an operating system and an application program required by at least one function; the data storage area can store data created according to the use of the terminal, and the like.
- the memory 620 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices.
- the memory 620 may further include a memory remotely provided with respect to the processor 610, and these remote memories may be connected to the device through a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
- the input device 630 may be used to receive inputted numeric or character information, and generate key signal input related to user settings and function control of the device.
- the output device 640 may include a display device such as a display screen, a speaker, and an audio device such as a buzzer.
- An embodiment of the present application further provides a storage medium on which a computer program is stored, and when the program is executed by a processor, the method for early warning of performance indicators as described in the foregoing embodiment of the present application is implemented.
- a storage medium containing computer-executable instructions provided by the embodiments of the present application is not limited to the operations in the early warning method for performance indicators as described above, and can also execute the operations provided in any of the embodiments of the present application.
- the related operations in the early warning method of the performance indicators of the system and have corresponding functions and beneficial effects.
- the embodiment of the application provides an early warning method, device, equipment, and storage medium of a performance indicator.
- the predicted data of the performance indicator in a set time period is determined, and the predicted data of the performance indicator is determined according to the predicted data and the performance.
- the difference between the actual data of the indicator in the set time period is determined, and the change trend curve of the difference is determined. If the difference reaches the corresponding difference threshold in the change trend curve and the duration is less than the set duration, then it is determined The performance index is degraded.
- the embodiment of the application does not require manual periodic checking, which saves manpower, and can predict the change trend of the difference based on the historical data and actual data of the performance indicator, predict the change of the performance indicator in advance, and timely understand the operating status of the communication system corresponding to the performance indicator .
- ROM Read-Only Memory
- RAM Random Access Memory
- FLASH Flash memory
- hard disk or optical disk etc.
- a computer device which can be a robot, A personal computer, a server, or a network device, etc.
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Abstract
An early-warning method and apparatus for a performance indicator, and a device and a storage medium. The early-warning method for a performance indicator comprises: according to the historical data of a performance indicator, determining the predicted data of the performance indicator within a set time period (S110); determining the change trend curve of a difference according to the difference between the predicted data and the actual data of the performance indicator in the set time period (S120); and if the time period during which the difference value reaches a corresponding difference value threshold in the change trend curve is less than a set time period, determining that the performance indicator is degraded (S130).
Description
相关申请的交叉引用Cross-references to related applications
本申请基于申请号为201911283180.8、申请日为2019年12月13日的中国专利申请提出,并要求该中国专利申请的优先权,该中国专利申请的全部内容在此引入本申请作为参考。This application is filed based on the Chinese patent application with the application number 201911283180.8 and the filing date on December 13, 2019, and claims the priority of the Chinese patent application. The entire content of the Chinese patent application is hereby incorporated into this application by reference.
本申请实施例涉及通信技术领域,尤其涉及一种性能指标的预警方法、装置、设备及存储介质。The embodiments of the present application relate to the field of communication technology, and in particular, to an early warning method, device, equipment, and storage medium for performance indicators.
在通信系统的日常运维过程中,通常采用一些关键绩效指标(Key Performance Indicator,KPI)来衡量通信系统的运行状态,例如可以根据流量、接通率或掉话率等KPI指标来衡量通信系统运行状态的好坏。KPI指标的劣化通常存在两种形态:一种是急速下跌,即KPI指标在短时间内出现大幅度变化;另一种是缓慢下滑,即KPI指标在较长的时间内出现较大的差异。针对缓慢下滑的情况,传统的方式是通过人工定期观察KPI指标的变化来衡量通信系统的运行状态,不仅增加了人力,而且无法及时的了解通信系统的运行状态。In the daily operation and maintenance of the communication system, some key performance indicators (KPI) are usually used to measure the operating status of the communication system. For example, the communication system can be measured according to KPI indicators such as traffic, connection rate, or dropped call rate. The running state is good or bad. The deterioration of KPI indicators usually has two forms: one is a rapid decline, that is, the KPI indicators have a large change in a short period of time; the other is a slow decline, that is, the KPI indicators have a large difference in a longer period of time. In view of the slow decline, the traditional way is to measure the operating status of the communication system by manually observing the changes of KPI indicators on a regular basis, which not only increases the manpower, but also fails to understand the operating status of the communication system in time.
发明内容Summary of the invention
本申请实施例提供一种性能指标的预警方法、装置、设备及存储介质,以在至少一定程度上解决无法及时了解通信系统运行状态的问题。The embodiments of the present application provide an early warning method, device, equipment, and storage medium for performance indicators, so as to solve the problem of not being able to understand the operating status of the communication system in time to at least a certain extent.
第一方面,本申请实施例提供了一种性能指标的预警方法,包括:根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据;根据所述预测数据和所述性能指标在设定时间段内的实际数据的差值,确定所述差值的变化趋势曲线;如果所述差值达到所述变化趋势曲线中对应的差值阈值的时长小于设定时长,则确定所述性能指标劣化。In the first aspect, an embodiment of the present application provides an early warning method for a performance indicator, which includes: determining predicted data of the performance indicator within a set time period based on historical data of the performance indicator; and based on the predicted data and the performance The difference between the actual data of the indicator in the set time period is determined, and the change trend curve of the difference is determined; if the difference reaches the corresponding difference threshold in the change trend curve and the duration is less than the set duration, then it is determined The performance index is degraded.
第二方面,本申请实施例还提供了一种性能指标的预警装置,包括:预测数据确定模块,用于根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据;曲线确定模块,用于根据所述预测数据和所述性能指标在设定时间段内的实际数据的差值,确定所述差值的变化趋势曲线;性能指标劣化确定模块,用于如果所述差值达到所述变化趋势曲线中对应的差值阈值的时长小于设定时长,则确定所述性能指标劣化。In a second aspect, an embodiment of the present application also provides an early warning device for a performance indicator, including: a prediction data determining module, configured to determine the predicted data of the performance indicator in a set time period according to the historical data of the performance indicator; and a curve; The determining module is used to determine the change trend curve of the difference according to the difference between the predicted data and the actual data of the performance index in a set time period; the performance index deterioration determining module is used to determine if the difference is When the time period when the value reaches the corresponding difference threshold in the change trend curve is less than the set time period, it is determined that the performance index is degraded.
第三方面,本申请实施例还提供了一种设备,包括:一个或多个处理器;存储器,用于存储一个或多个程序;当所述一个或多个程序被所述一个或多个处理器执行时,使得所述一个或多个处理器实现如第一方面所述的性能指标的预警方法。In a third aspect, an embodiment of the present application also provides a device, including: one or more processors; a memory, used to store one or more programs; when the one or more programs are used by the one or more When the processor is executed, the one or more processors implement the early warning method of the performance index as described in the first aspect.
第四方面,本申请实施例还提供了一种存储介质,其上存储有计算机程序,该程序被处 理器执行时实现如第一方面所述的性能指标的预警方法。In a fourth aspect, an embodiment of the present application also provides a storage medium on which a computer program is stored, and when the program is executed by a processor, the early warning method of the performance index as described in the first aspect is realized.
图1为本申请实施例提供的一种性能指标的预警方法的流程图;FIG. 1 is a flowchart of an early warning method for performance indicators provided by an embodiment of the application;
图2为本申请实施例提供的另一种性能指标的预警方法的流程图;2 is a flowchart of another early warning method for performance indicators provided by an embodiment of the application;
图3为本申请实施例提供的一种差值的变化趋势曲线示意图;FIG. 3 is a schematic diagram of a variation trend curve of a difference provided by an embodiment of the application;
图4为本申请实施例提供的一种性能指标的预警方法的实现流程图;FIG. 4 is an implementation flowchart of an early warning method for performance indicators provided by an embodiment of the application;
图5为本申请实施例提供的一种性能指标的预警装置的结构图;FIG. 5 is a structural diagram of a performance indicator early warning device provided by an embodiment of the application;
图6为本申请实施例提供的一种设备的结构图。Fig. 6 is a structural diagram of a device provided by an embodiment of the application.
下面结合附图和实施例对本申请作进一步的详细说明。可以理解的是,此处所描述的具体实施例仅仅用于解释本申请,而非对本申请的限定。另外还需要说明的是,为了便于描述,附图中仅示出了与本申请相关的部分而非全部结构。此外,在不冲突的情况下,本申请中的实施例及实施例中的特征可以相互组合。The application will be further described in detail below with reference to the drawings and embodiments. It is understandable that the specific embodiments described here are only used to explain the application, but not to limit the application. In addition, it should be noted that, for ease of description, the drawings only show a part of the structure related to the present application instead of all of the structure. In addition, if there is no conflict, the embodiments in the application and the features in the embodiments can be combined with each other.
图1为本申请实施例提供的一种性能指标的预警方法的流程图,本实施例可适用于智能监测性能指标的变化情况,尤其是监测无人值守的通信系统中性能指标的变化情况,以根据性能指标的变化情况提前了解通信系统的运行状态。该方法可以由性能指标的预警装置来执行,该装置可以采用软件和/或硬件的方式实现,并集成在电脑等设备中,参考图1,该方法包括如下步骤:Figure 1 is a flow chart of an early warning method for performance indicators provided by an embodiment of the application. This embodiment is suitable for intelligent monitoring of changes in performance indicators, especially for monitoring changes in performance indicators in unattended communication systems. In order to understand the operating status of the communication system in advance based on changes in performance indicators. The method can be implemented by an early warning device of performance indicators, which can be implemented in software and/or hardware and integrated in a computer and other equipment. With reference to Figure 1, the method includes the following steps:
S110、根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据。S110: According to the historical data of the performance indicator, determine the predicted data of the performance indicator within a set time period.
本实施例将性能指标称为KPI指标,KPI指标可以根据衡量的内容确定,例如衡量通信系统运行状态的优劣时,可以将流量、接通率、话务量或掉话率等作为KPI指标。KPI指标的历史数据为KPI指标在历史时间段内的数据,其中,历史时间段的大小影响预测数据的准确度,例如如果历史时间段过小,容易导致信息不充分,使得预测数据与实际值的偏差较大,如果历史时间段过大,不仅增加了处理复杂度与处理时间,也增加了过拟合的风险,同样会使预测数据与实际值的偏差较大。本实施例的历史时间段以7天为例,即历史数据为KPI指标在当前时间之前7天内的数据。In this embodiment, the performance index is called KPI index. The KPI index can be determined according to the measured content. For example, when measuring the operating status of the communication system, the traffic, the connection rate, the traffic volume, or the dropped call rate can be used as the KPI index. . The historical data of the KPI indicator is the data of the KPI indicator in the historical time period. Among them, the size of the historical time period affects the accuracy of the predicted data. For example, if the historical time period is too small, it is easy to cause insufficient information, which makes the predicted data and the actual value If the historical time period is too large, it will not only increase the processing complexity and processing time, but also increase the risk of over-fitting, which will also cause a large deviation between the predicted data and the actual value. The historical time period in this embodiment takes 7 days as an example, that is, the historical data is the data of the KPI indicator within 7 days before the current time.
预测数据为KPI指标在当前时间之后设定时间段内对应的数据,考虑到通信系统中KPI指标具有周期特性,即在24小时内规律变化,在一些实施例中,设定时间段为24小时,即根据历史数据,确定KPI指标在当前时间之后24小时内的数据,作为预测数据。设定时间段的大小一方面可以用于确定预测数据的数量,另一方面可以用于确定下一个周期的时间点。The predicted data is the data corresponding to the KPI indicator in the set time period after the current time. Considering that the KPI indicator in the communication system has periodic characteristics, that is, it changes regularly within 24 hours. In some embodiments, the set time period is 24 hours. , That is, according to historical data, determine the data of KPI indicators within 24 hours after the current time as forecast data. The size of the set time period can be used to determine the amount of forecast data on the one hand, and can be used to determine the time point of the next cycle on the other hand.
在一些实施例中,可以通过三次指数平滑算法,简称Holt-Winters算法,结合历史数据预测KPI指标在未来24小时内的数据。Holt-Winters算法可以对同时含有趋势和季节性的 时间序列进行预测,满足了通信系统中话务量和流量等KPI指标存在趋势性和季节性的特点。具体的,可以将KPI指标的历史数据代入Holt-Winters算法,拟合得到Holt-Winters算法中包含的各项参数,根据拟合出的参数值对未来24小时内的KPI指标进行预测,得到预测数据。In some embodiments, the triple exponential smoothing algorithm, Holt-Winters algorithm for short, can be used to predict the data of the KPI indicator in the next 24 hours in combination with historical data. The Holt-Winters algorithm can predict time series that contain both trend and seasonality, and meets the trend and seasonality characteristics of KPI indicators such as traffic and traffic in the communication system. Specifically, the historical data of KPI indicators can be substituted into the Holt-Winters algorithm, the parameters included in the Holt-Winters algorithm can be obtained by fitting, and the KPI indicators in the next 24 hours can be predicted according to the fitted parameter values to obtain the prediction data.
S120、根据所述预测数据和所述性能指标在设定时间段内的实际数据的差值,确定所述差值的变化趋势曲线。S120: Determine a change trend curve of the difference according to the difference between the predicted data and the actual data of the performance indicator in a set time period.
KPI指标的实际数据为KPI指标在设定时间段内实际的数据。根据预测数据和实际数据,可以确定KPI指标在设定时间段内的差值。为了提前了解KPI指标的变化情况,在通信系统出现风险之前及时通知运维人员处理,实施例根据KPI指标的预测数据和实际数据的差值,预测差值的变化趋势,得到差值的变化趋势曲线。The actual data of the KPI indicator is the actual data of the KPI indicator in the set time period. According to the forecast data and actual data, the difference between the KPI indicators in the set time period can be determined. In order to understand the change of KPI indicators in advance, the operation and maintenance personnel are notified in time before the risk of the communication system occurs. The embodiment predicts the change trend of the difference according to the difference between the predicted data of the KPI indicator and the actual data, and obtains the change trend of the difference. curve.
在一些实施例中,可以根据设定时间段内的差值结合曲线拟合方法,得到差值的变化趋势曲线,其中,曲线拟合方法可以是最小二乘法。最小二乘法又称最小平方法,是一种常用的曲线拟合方法。实施例对具体的拟合过程不进行限定。本实施例在差值的基础上,对差值进行预测,得到差值的变化趋势曲线,根据该变化趋势曲线可以提前预测KPI指标的变化情况,从而在预测出KPI指标劣化时,提前通知运维人员进行处理,降低了风险。In some embodiments, the curve fitting method may be combined with the difference value within a set time period to obtain the change trend curve of the difference value, wherein the curve fitting method may be the least square method. The least square method, also known as the least square method, is a commonly used curve fitting method. The embodiment does not limit the specific fitting process. In this embodiment, the difference is predicted on the basis of the difference, and the change trend curve of the difference is obtained. According to the change trend curve, the change of the KPI index can be predicted in advance, so that when the deterioration of the KPI index is predicted, the operator is notified in advance. Maintenance personnel deal with it, reducing the risk.
S130、如果所述差值达到所述变化趋势曲线中对应的差值阈值的时长小于设定时长,则确定所述性能指标劣化。S130: If the time period during which the difference value reaches the corresponding difference value threshold in the change trend curve is less than a set time period, determine that the performance index is degraded.
变化趋势曲线反映了差值随时间变化的情况,每个差值对应一个时间点。差值阈值为变化趋势曲线中的一点。在确定KPI指标是否劣化时,可以根据预测数据和实际数据的差值达到差值阈值时的时长确定,例如当预测数据和实际数据的差值达到差值阈值的时长小于设定时长,确定该KPI指标劣化,否则,确定KPI指标正常,其中,设定时长的大小可以根据实际情况设置,例如可以设置为1小时。考虑到设定时间段内存在多个预测数据和实际数据,即存在多个差值,将这多个差值按照时间顺序排列,将最后一个时间点的差值作为KPI指标是否劣化的依据,即如果设定时间段内最后一个时间点对应的差值达到差值阈值的时长小于设定时长,确定该KPI指标劣化。The change trend curve reflects the change of the difference over time, and each difference corresponds to a time point. The difference threshold is a point in the change trend curve. When determining whether the KPI indicator is degraded, it can be determined according to the time period when the difference between the predicted data and the actual data reaches the difference threshold. For example, when the difference between the predicted data and the actual data reaches the difference threshold, the time period is less than the set time. The KPI indicator is degraded, otherwise, it is determined that the KPI indicator is normal, where the size of the set duration can be set according to the actual situation, for example, it can be set to 1 hour. Considering that there are multiple predicted data and actual data in the set time period, that is, there are multiple differences, the multiple differences are arranged in chronological order, and the difference at the last time point is used as the basis for whether the KPI indicator has deteriorated. That is, if the time period during which the difference value corresponding to the last time point in the set time period reaches the difference value threshold is less than the set time period, it is determined that the KPI indicator is degraded.
在一些实施例中,在确定KPI指标劣化后,可以以短信或邮件的方式将KPI指标劣化的告警信息发送至运维人员对应的终端,使运维人员提前采取措施,消除告警和安全隐患。In some embodiments, after determining the deterioration of the KPI indicator, the alarm information of the deterioration of the KPI indicator may be sent to the terminal corresponding to the operation and maintenance personnel in a short message or email, so that the operation and maintenance personnel can take measures in advance to eliminate alarms and potential safety hazards.
本申请实施例提供一种性能指标的预警方法,根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据,根据所述预测数据和所述性能指标在设定时间段内的实际数据的差值,确定所述差值的变化趋势曲线,如果所述差值达到所述变化趋势曲线中对应的差值阈值的时长小于设定时长,则确定所述性能指标劣化。本申请实施例无需人工定期查看,节省了人力,而且可以根据性能指标的历史数据和实际数据预测差值的变化趋势,提前预测 性能指标的变化情况,及时了解性能指标所对应通信系统的运行状态。The embodiment of the present application provides an early warning method for performance indicators. According to historical data of the performance indicators, the predicted data of the performance indicators within a set time period is determined, and the predicted data of the performance indicators are within the set time period based on the predicted data and the performance indicators. Determine the change trend curve of the difference value by the difference value of the actual data, if the difference value reaches the corresponding difference value threshold in the change trend curve for a duration less than the set duration, then determine that the performance index is degraded. The embodiment of the application does not need to manually check regularly, which saves manpower, and can predict the change trend of the difference based on the historical data and actual data of the performance indicator, predict the change of the performance indicator in advance, and timely understand the operating status of the communication system corresponding to the performance indicator .
在上述实施例的基础上,在一些实施例中,可以通过如下方式确定KPI指标在设定时间段内的预测数据:On the basis of the foregoing embodiments, in some embodiments, the prediction data of the KPI indicator within a set time period can be determined in the following manner:
获取所述性能指标在历史时间段内的历史数据;Acquiring historical data of the performance indicator in a historical time period;
根据预测算法和所述历史数据,确定所述预测算法的参数信息;Determine the parameter information of the prediction algorithm according to the prediction algorithm and the historical data;
根据所述参数信息,确定所述性能指标在设定时间段内的预测数据。According to the parameter information, the predicted data of the performance index in a set time period is determined.
本实施例的预测算法以Holt-Winters算法为例,Holt-Winters算法包含待拟合的三个参数,分别为α、β和γ,α、β和γ介于0-1之间,根据历史数据可以拟合出α、β和γ的具体值。当α、β和γ确定时,代入Holt-Winters算法,即可预测出KPI指标在未来设定时间段内的数据。实施例对α、β和γ的拟合过程不进行限定。The prediction algorithm of this embodiment takes the Holt-Winters algorithm as an example. The Holt-Winters algorithm contains three parameters to be fitted, namely α, β, and γ. α, β, and γ are between 0-1. According to history The data can be fitted to the specific values of α, β and γ. When α, β, and γ are determined, substitute the Holt-Winters algorithm to predict the data of the KPI indicator in the future set time period. The embodiment does not limit the fitting process of α, β, and γ.
图2为本申请实施例提供的另一种性能指标的预警方法的流程图。Fig. 2 is a flowchart of another early warning method for performance indicators provided by an embodiment of the application.
本实施例是在上述实施例的基础上进行优化,参考图2,该方法包括如下步骤:This embodiment is optimized on the basis of the above embodiment. Referring to FIG. 2, the method includes the following steps:
S210、根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据。S210: According to the historical data of the performance indicator, determine the predicted data of the performance indicator within a set time period.
S220、在所述设定时间段内每隔设定时间间隔获取所述性能指标的实际数据。S220: Acquire actual data of the performance index at every set time interval within the set time period.
考虑到时间的连续特性,预测数据和实际数据较多,实施例每隔设定时间间隔获取一次KPI指标的实际数据,作为KPI指标的实际数据。在一些实施例中,可每隔15分钟获取一次,从而可以得到设定时间段内的多个实际数据。Considering the continuous characteristics of time, there are many forecast data and actual data. In the embodiment, the actual data of the KPI indicator is acquired at a set time interval as the actual data of the KPI indicator. In some embodiments, it can be obtained every 15 minutes, so that multiple actual data within a set time period can be obtained.
S230、分别确定各所述实际数据和所述实际数据所对应时间点的预测数据的差值。S230: Determine respectively the difference between the actual data and the predicted data at the time points corresponding to the actual data.
每获取一个实际数据,计算该时间点中预测数据和实际数据的差值,得到多个差值。实施例将每个实际数据记为一个点。Every time a piece of actual data is obtained, the difference between the predicted data and the actual data at that point in time is calculated to obtain multiple differences. The embodiment records each actual data as a point.
S240、根据各所述差值和曲线拟合算法,确定所述差值的拟合曲线,作为所述差值的变化趋势曲线。S240: Determine a fitting curve of the difference according to each of the difference and the curve fitting algorithm, as a change trend curve of the difference.
在确定差值的变化趋势曲线时,可以根据得到的各个差值确定,也可以从中选取部分差值确定,实施例以部分差值为例。当选取部分差值时,差值的个数需要同时兼顾精确性和预警的及时性,本实施例可将差值按照时间点的顺序排列,选取最后三个时间点对应的差值,作为变化趋势曲线的确定依据。其中,曲线拟合算法以最小二乘法为例。相应的,S240包括:When determining the change trend curve of the difference, it can be determined according to the obtained differences, or a part of the difference can be selected from it. The embodiment takes the partial difference as an example. When selecting partial differences, the number of differences needs to take into account both accuracy and timeliness of early warning. In this embodiment, the differences can be arranged in the order of time points, and the differences corresponding to the last three time points are selected as the change. The basis for determining the trend curve. Among them, the curve fitting algorithm takes the least square method as an example. Correspondingly, S240 includes:
根据各所述差值和曲线拟合算法,确定所述曲线拟合算法的参数信息;Determine the parameter information of the curve fitting algorithm according to each of the differences and the curve fitting algorithm;
根据所述曲线拟合算法的参数信息,确定多项式拟合曲线,作为所述差值的拟合曲线。According to the parameter information of the curve fitting algorithm, a polynomial fitting curve is determined as the fitting curve of the difference.
根据所选定的三个差值的大小,结合最小二乘法即可确定最小二乘法的多项式参数,将多项式参数代入最小二乘法对应的方程,即可得到对应的多项式拟合方程,绘制该多项式拟合方程对应的曲线,得到多项式拟合曲线。通过最小二乘法可以拟合出差值变化的趋势,从而可以预测越限时长,协助运维人员决策,既降低了劳动强度,又提高了工作效率。The polynomial parameters of the least squares method can be determined according to the size of the selected three differences, combined with the least square method, and the polynomial parameters are substituted into the equation corresponding to the least square method to obtain the corresponding polynomial fitting equation, and draw the polynomial Fit the curve corresponding to the equation to obtain a polynomial fitting curve. The least square method can be used to fit the trend of the difference value, thereby predicting the time limit for exceeding the limit, and assisting the operation and maintenance personnel in decision-making, which not only reduces labor intensity, but also improves work efficiency.
图3为本申请实施例提供的一种差值的变化趋势曲线示意图。FIG. 3 is a schematic diagram of a variation trend curve of a difference provided by an embodiment of the application.
图3中的曲线为根据最小二乘法以及差值A、差值B和差值C拟合得到的差值变化趋势曲线,差值A、差值B和差值C对应的时刻点分别为t1、t2和t3,差值阈值M对应的时刻点为t0。The curve in Figure 3 is the difference change trend curve obtained by fitting the least square method and difference A, difference B and difference C. The time points corresponding to difference A, difference B and difference C are respectively t1 , T2 and t3, the time point corresponding to the difference threshold M is t0.
S250、根据所述变化趋势曲线中差值阈值对应的时刻点和所述差值中距离所述时刻点最近的差值的时刻点,确定距离所述时刻点最近的差值达到所述差值阈值的时长。S250. Determine, according to the time point corresponding to the difference threshold value in the change trend curve and the time point of the difference value closest to the time point in the difference value, that the difference value closest to the time point reaches the difference value The duration of the threshold.
参考图3,实施例以差值C对应的时刻点t3和差值阈值M对应的时刻点t0的时长为依据,判断KPI指标是否劣化。具体的,如果t3到t0的时长小于设定时长,则认为KPI指标劣化,否则,认为KPI指标正常。Referring to FIG. 3, the embodiment uses the time length of the time point t3 corresponding to the difference value C and the time point t0 corresponding to the difference value threshold M as the basis to determine whether the KPI indicator has deteriorated. Specifically, if the time period from t3 to t0 is less than the set time period, the KPI indicator is considered to be degraded, otherwise, the KPI indicator is considered to be normal.
S260、所述时长是否小于设定时长,若是,执行S270,否则,执行S290。S260. Whether the duration is less than the set duration, if yes, execute S270; otherwise, execute S290.
S270、确定所述性能指标劣化。S270. Determine that the performance index has deteriorated.
S280、展示所述性能指标劣化的预警信息。S280. Display the early warning information of the deterioration of the performance index.
在一些实施例中,在确定KPI指标劣化后,自动向运维人员推送KPI指标劣化的预警信息,以通知运维人员及时处理,降低风险。In some embodiments, after determining the deterioration of the KPI indicator, the early warning information of the deterioration of the KPI indicator is automatically pushed to the operation and maintenance personnel to notify the operation and maintenance personnel to deal with it in time and reduce the risk.
S290、确定所述性能指标正常。S290. Determine that the performance index is normal.
本申请实施例提供的性能指标的预警方法,在上述实施例的基础上,根据设定时间段内预测数据和实际数据的差值,结合曲线拟合算法得到差值的变化趋势曲线,实现了对差值的预测,从而可以提前预测KPI指标是否出现劣化,既降低了劳动强度,提高了工作效率,又可以在KPI指标劣化之前,及时通知运维人员处理,降低了风险。The early warning method for performance indicators provided in the embodiments of this application is based on the above embodiments, according to the difference between the predicted data and the actual data in a set time period, combined with the curve fitting algorithm to obtain the change trend curve of the difference, which realizes The prediction of the difference can predict in advance whether the KPI indicator will deteriorate, which not only reduces labor intensity and improves work efficiency, but also informs the operation and maintenance personnel to deal with it in time before the KPI indicator deteriorates, reducing the risk.
图4为本申请实施例提供的一种性能指标的预警方法的实现流程图。Fig. 4 is an implementation flowchart of a performance indicator warning method provided by an embodiment of the application.
图4以预测算法为Holt-Winters算法,曲线拟合算法以最小二乘法为例。具体的,根据Holt-Winters算法对获取的KPI指标的历史数据进行预测,得到KPI指标在设定时间段内的预测数据,将该预测数据与KPI指标在设定时间段内的实际数据作差,得到有限个差值,然后根据最近三次的差值和最小二乘法,对差值的变化趋势进行预测,得到变化趋势曲线,根据差值阈值和最近一次差值对应的时间点,得到最近一次差值达到差值阈值的时长,如果时长小于设定时长,确定KPI指标劣化,并展示KPI指标劣化的预警信息,以通知运维人员及时处理。Figure 4 takes the prediction algorithm as the Holt-Winters algorithm, and the curve fitting algorithm takes the least square method as an example. Specifically, according to the Holt-Winters algorithm, the acquired historical data of the KPI indicator is predicted to obtain the predicted data of the KPI indicator in a set time period, and the difference between the predicted data and the actual data of the KPI indicator in the set time period is made , Get a finite number of differences, and then predict the change trend of the difference according to the difference of the last three times and the least square method, and get the change trend curve. According to the difference threshold and the time point corresponding to the last difference, get the latest The time when the difference reaches the difference threshold. If the time is less than the set time, the KPI indicator is determined to be degraded, and the early warning information of the KPI indicator degradation is displayed to notify the operation and maintenance personnel to deal with it in time.
图5为本申请实施例提供的一种性能指标的预警装置的结构图。该装置可以执行上述实施例所述的性能指标的预警方法,参考图5,该装置包括:Fig. 5 is a structural diagram of an early warning device with performance indicators provided by an embodiment of the application. The device can execute the early warning method of performance indicators described in the foregoing embodiment. Referring to FIG. 5, the device includes:
预测数据确定模块510,用于根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据;The forecast data determining module 510 is configured to determine the forecast data of the performance index in a set time period according to the historical data of the performance index;
曲线确定模块520,用于根据所述预测数据和所述性能指标在设定时间段内的实际数据 的差值,确定所述差值的变化趋势曲线;The curve determination module 520 is configured to determine the change trend curve of the difference according to the difference between the predicted data and the actual data of the performance index in a set time period;
性能指标劣化确定模块530,用于如果所述差值达到所述变化趋势曲线中对应的差值阈值的时长小于设定时长,则确定所述性能指标劣化。The performance index deterioration determining module 530 is configured to determine that the performance index is deteriorated if the time period during which the difference value reaches the corresponding difference value threshold in the change trend curve is less than a set time period.
本申请实施例提供一种性能指标的预警装置,根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据,根据所述预测数据和所述性能指标在设定时间段内的实际数据的差值,确定所述差值的变化趋势曲线,如果所述差值达到所述变化趋势曲线中对应的差值阈值的时长小于设定时长,则确定所述性能指标劣化。本申请实施例无需人工定期查看,节省了人力,而且可以根据性能指标的历史数据和实际数据预测差值的变化趋势,提前预测性能指标的变化情况,及时了解性能指标所对应通信系统的运行状态。The embodiment of the present application provides an early warning device for a performance indicator, which determines the predicted data of the performance indicator in a set time period according to historical data of the performance indicator, and determines the predicted data of the performance indicator in a set time period according to the predicted data and the performance indicator. Determine the change trend curve of the difference value by the difference value of the actual data, if the difference value reaches the corresponding difference value threshold in the change trend curve for a duration less than the set duration, then determine that the performance index is degraded. The embodiment of the application does not need to manually check regularly, which saves manpower, and can predict the change trend of the difference based on the historical data and actual data of the performance indicator, predict the change of the performance indicator in advance, and timely understand the operating status of the communication system corresponding to the performance indicator .
在上述实施例的基础上,预测数据确定模块510,具体用于:On the basis of the foregoing embodiment, the prediction data determining module 510 is specifically configured to:
获取所述性能指标在历史时间段内的历史数据;Acquiring historical data of the performance indicator in a historical time period;
根据预测算法和所述历史数据,确定所述预测算法的参数信息;Determine the parameter information of the prediction algorithm according to the prediction algorithm and the historical data;
根据所述参数信息,确定所述性能指标在设定时间段内的预测数据。According to the parameter information, the predicted data of the performance index in a set time period is determined.
在上述实施例的基础上,曲线确定模块520,包括:On the basis of the foregoing embodiment, the curve determination module 520 includes:
实际数据获取单元,用于在所述设定时间段内每隔设定时间间隔获取所述性能指标的实际数据;The actual data acquisition unit is configured to acquire the actual data of the performance index at every set time interval within the set time period;
差值确定单元,用于分别确定各所述实际数据和所述实际数据所对应时间点的预测数据的差值;The difference determining unit is used to determine the difference between each of the actual data and the predicted data at the time point corresponding to the actual data;
曲线确定单元,用于根据各所述差值和曲线拟合算法,确定所述差值的拟合曲线,作为所述差值的变化趋势曲线。The curve determination unit is configured to determine the fitting curve of the difference according to each of the difference and the curve fitting algorithm, as the change trend curve of the difference.
在上述实施例的基础上,曲线确定单元,具体用于:On the basis of the foregoing embodiment, the curve determination unit is specifically used for:
根据各所述差值和曲线拟合算法,确定所述曲线拟合算法的参数信息;Determine the parameter information of the curve fitting algorithm according to each of the differences and the curve fitting algorithm;
根据所述曲线拟合算法的参数信息,确定多项式拟合曲线,作为所述差值的拟合曲线。According to the parameter information of the curve fitting algorithm, a polynomial fitting curve is determined as the fitting curve of the difference.
在上述实施例的基础上,性能指标劣化确定模块530,具体用于:On the basis of the foregoing embodiment, the performance index deterioration determining module 530 is specifically configured to:
根据所述变化趋势曲线中差值阈值对应的时刻点和所述差值中距离所述时刻点最近的差值的时刻点,确定距离所述时刻点最近的差值达到所述差值阈值的时长;According to the time point corresponding to the difference threshold value in the change trend curve and the time point of the difference value closest to the time point in the difference value, it is determined that the difference value closest to the time point reaches the difference value threshold value. duration;
如果所述时长小于设定时长,则确定所述性能指标劣化。If the duration is less than the set duration, it is determined that the performance index is degraded.
在上述实施例的基础上,该装置还包括:On the basis of the foregoing embodiment, the device further includes:
信息展示模块,用于在确定所述性能指标劣化之后,展示所述性能指标劣化的预警信息。The information display module is configured to display the early warning information of the performance index deterioration after the performance index deterioration is determined.
本申请实施例提供的性能指标的预警装置可执行本申请上述实施例所提供的性能指标的预警方法,具备执行方法相应的功能模块和有益效果。The early-warning device for performance indicators provided in the embodiments of the present application can execute the early-warning method for performance indicators provided in the above-mentioned embodiments of the present application, and has the corresponding functional modules and beneficial effects of the execution method.
图6为本申请实施例提供的一种设备的结构图。Fig. 6 is a structural diagram of a device provided by an embodiment of the application.
参考图6,该设备包括:处理器610、存储器620、输入装置630和输出装置640,设备中处理器610的数量可以是一个或多个,图6中以一个处理器610为例,设备中的处理器610、存储器620、输入装置630和输出装置640可以通过总线或其他方式连接,图6中以通过总线连接为例。Referring to FIG. 6, the device includes a processor 610, a memory 620, an input device 630, and an output device 640. The number of processors 610 in the device may be one or more. In FIG. 6, one processor 610 is taken as an example. The processor 610, the memory 620, the input device 630, and the output device 640 may be connected by a bus or other methods. In FIG. 6, the connection by a bus is taken as an example.
存储器620作为一种计算机可读存储介质,可用于存储软件程序、计算机可执行程序以及模块,如本申请实施例中的性能指标的预警方法对应的程序指令/模块。处理器610通过运行存储在存储器620中的软件程序、指令以及模块,从而执行设备的各种功能应用以及数据处理,即实现上述实施例的性能指标的预警方法。As a computer-readable storage medium, the memory 620 can be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the early warning method of performance indicators in the embodiments of the present application. The processor 610 executes various functional applications and data processing of the device by running the software programs, instructions, and modules stored in the memory 620, that is, realizes the early warning method of the performance indicators of the foregoing embodiments.
存储器620主要包括存储程序区和存储数据区,其中,存储程序区可存储操作系统、至少一个功能所需的应用程序;存储数据区可存储根据终端的使用所创建的数据等。此外,存储器620可以包括高速随机存取存储器,还可以包括非易失性存储器,例如至少一个磁盘存储器件、闪存器件、或其他非易失性固态存储器件。在一些实例中,存储器620可进一步包括相对于处理器610远程设置的存储器,这些远程存储器可以通过网络连接至设备。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。The memory 620 mainly includes a program storage area and a data storage area. The program storage area can store an operating system and an application program required by at least one function; the data storage area can store data created according to the use of the terminal, and the like. In addition, the memory 620 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some examples, the memory 620 may further include a memory remotely provided with respect to the processor 610, and these remote memories may be connected to the device through a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
输入装置630可用于接收输入的数字或字符信息,以及产生与设备的用户设置以及功能控制有关的键信号输入。输出装置640可包括显示屏等显示设备、扬声器以及蜂鸣器等音频设备。The input device 630 may be used to receive inputted numeric or character information, and generate key signal input related to user settings and function control of the device. The output device 640 may include a display device such as a display screen, a speaker, and an audio device such as a buzzer.
本申请实施例提供的设备与上述实施例提供的性能指标的预警方法属于同一构思,未在本实施例中详尽描述的技术细节可参见上述实施例,并且本实施例具备执行性能指标的预警方法相同的有益效果。The equipment provided in this embodiment of the application and the performance indicator warning method provided in the above embodiment belong to the same concept. For technical details not described in this embodiment in detail, please refer to the above embodiment, and this embodiment has an early warning method for executing performance indicators. The same beneficial effect.
本申请实施例还提供一种存储介质,其上存储有计算机程序,该程序被处理器执行时实现如本申请上述实施例所述的性能指标的预警方法。An embodiment of the present application further provides a storage medium on which a computer program is stored, and when the program is executed by a processor, the method for early warning of performance indicators as described in the foregoing embodiment of the present application is implemented.
当然,本申请实施例所提供的一种包含计算机可执行指令的存储介质,其计算机可执行指令不限于如上所述的性能指标的预警方法中的操作,还可以执行本申请任意实施例所提供的性能指标的预警方法中的相关操作,且具备相应的功能和有益效果。Of course, a storage medium containing computer-executable instructions provided by the embodiments of the present application is not limited to the operations in the early warning method for performance indicators as described above, and can also execute the operations provided in any of the embodiments of the present application. The related operations in the early warning method of the performance indicators of the system, and have corresponding functions and beneficial effects.
本申请实施例提供一种性能指标的预警方法、装置、设备及存储介质,根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据,根据所述预测数据和所述性能指标在设定时间段内的实际数据的差值,确定所述差值的变化趋势曲线,如果所述差值达到所述变化趋势曲线中对应的差值阈值的时长小于设定时长,则确定所述性能指标劣化。本申请实施例无需人工定期查看,节省了人力,而且可以根据性能指标的历史数据和实际数据预测差值的变化趋势,提前预测性能指标的变化情况,及时了解性能指标所对应通信系统的运行状态。The embodiment of the application provides an early warning method, device, equipment, and storage medium of a performance indicator. According to historical data of the performance indicator, the predicted data of the performance indicator in a set time period is determined, and the predicted data of the performance indicator is determined according to the predicted data and the performance. The difference between the actual data of the indicator in the set time period is determined, and the change trend curve of the difference is determined. If the difference reaches the corresponding difference threshold in the change trend curve and the duration is less than the set duration, then it is determined The performance index is degraded. The embodiment of the application does not require manual periodic checking, which saves manpower, and can predict the change trend of the difference based on the historical data and actual data of the performance indicator, predict the change of the performance indicator in advance, and timely understand the operating status of the communication system corresponding to the performance indicator .
通过以上关于实施方式的描述,所属领域的技术人员可以清楚地了解到,本申请可借助软件及必需的通用硬件来实现,当然也可以通过硬件实现,但很多情况下前者是更佳的实施方式。基于这样的理解,本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来,该计算机软件产品可以存储在计算机可读存储介质中,如计算机的软盘、只读存储器(Read-Only Memory,ROM)、随机存取存储器(Random Access Memory,RAM)、闪存(FLASH)、硬盘或光盘等,包括若干指令用以使得一台计算机设备(可以是机器人,个人计算机,服务器,或者网络设备等)执行本申请上述实施例所述的性能指标的预警方法。Through the above description of the implementation manners, those skilled in the art can clearly understand that this application can be implemented with the help of software and necessary general-purpose hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation. . Based on this understanding, the technical solution of this application essentially or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk. , Read-Only Memory (ROM), Random Access Memory (RAM), Flash memory (FLASH), hard disk or optical disk, etc., including several instructions to make a computer device (which can be a robot, A personal computer, a server, or a network device, etc.) execute the early warning method of performance indicators described in the above-mentioned embodiments of this application.
注意,上述仅为本申请的较佳实施例及所运用技术原理。本领域技术人员会理解,本申请不限于这里所述的特定实施例,对本领域技术人员来说能够进行各种明显的变化、重新调整和替代而不会脱离本申请的保护范围。因此,虽然通过以上实施例对本申请进行了较为详细的说明,但是本申请不仅仅限于以上实施例,在不脱离本申请构思的情况下,还可以包括更多其他等效实施例,而本申请的范围由所附的权利要求范围决定。Note that the above are only the preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions can be made to those skilled in the art without departing from the protection scope of the present application. Therefore, although the application has been described in more detail through the above embodiments, the application is not limited to the above embodiments, and can also include more other equivalent embodiments without departing from the concept of the application. The scope of is determined by the scope of the appended claims.
Claims (10)
- 一种性能指标的预警方法,包括:An early warning method for performance indicators, including:根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据;According to the historical data of the performance index, determine the predicted data of the performance index within a set time period;根据所述预测数据和所述性能指标在设定时间段内的实际数据的差值,确定所述差值的变化趋势曲线;Determine the change trend curve of the difference according to the difference between the predicted data and the actual data of the performance indicator in a set time period;如果所述差值达到所述变化趋势曲线中对应的差值阈值的时长小于设定时长,则确定所述性能指标劣化。If the time period during which the difference value reaches the corresponding difference value threshold in the change trend curve is less than the set time period, it is determined that the performance index is degraded.
- 根据权利要求1所述的方法,其中,所述根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据,包括:The method according to claim 1, wherein the determining the predicted data of the performance indicator in a set time period according to the historical data of the performance indicator comprises:获取所述性能指标在历史时间段内的历史数据;Acquiring historical data of the performance indicator in a historical time period;根据预测算法和所述历史数据,确定所述预测算法的参数信息;Determine the parameter information of the prediction algorithm according to the prediction algorithm and the historical data;根据所述参数信息,确定所述性能指标在设定时间段内的预测数据。According to the parameter information, the predicted data of the performance index in a set time period is determined.
- 根据权利要求1所述的方法,其中,所述根据所述预测数据和所述性能指标在设定时间段内的实际数据的差值,确定所述差值的变化趋势曲线,包括:The method according to claim 1, wherein the determining the change trend curve of the difference according to the difference between the predicted data and the actual data of the performance indicator in a set time period comprises:在所述设定时间段内每隔设定时间间隔获取所述性能指标的实际数据;Acquiring actual data of the performance index at every set time interval within the set time period;分别确定各所述实际数据和所述实际数据所对应时间点的预测数据的差值;Respectively determine the difference between the actual data and the predicted data at the time points corresponding to the actual data;根据各所述差值和曲线拟合算法,确定所述差值的拟合曲线,作为所述差值的变化趋势曲线。According to each of the difference and the curve fitting algorithm, a fitting curve of the difference is determined as a change trend curve of the difference.
- 根据权利要求3所述的方法,其中,所述根据各所述差值和曲线拟合算法,确定所述差值的拟合曲线,包括:The method according to claim 3, wherein said determining the fitting curve of the difference according to each of the difference and a curve fitting algorithm comprises:根据各所述差值和曲线拟合算法,确定所述曲线拟合算法的参数信息;Determining the parameter information of the curve fitting algorithm according to each of the differences and the curve fitting algorithm;根据所述曲线拟合算法的参数信息,确定多项式拟合曲线,作为所述差值的拟合曲线。According to the parameter information of the curve fitting algorithm, a polynomial fitting curve is determined as the fitting curve of the difference.
- 根据权利要求3所述的方法,其中,所述如果所述差值达到所述变化趋势曲线中对应的差值阈值的时长小于设定时长,则确定所述性能指标劣化,包括:3. The method according to claim 3, wherein the determining that the performance index is degraded if the time period during which the difference value reaches the corresponding difference value threshold in the change trend curve is less than a set time period comprises:根据所述变化趋势曲线中差值阈值对应的时刻点和所述差值中距离所述时刻点最近的差值的时刻点,确定距离所述时刻点最近的差值达到所述差值阈值的时长;According to the time point corresponding to the difference threshold value in the change trend curve and the time point of the difference value closest to the time point in the difference value, it is determined that the difference value closest to the time point reaches the difference value threshold value. duration;如果所述时长小于设定时长,则确定所述性能指标劣化。If the duration is less than the set duration, it is determined that the performance index is degraded.
- 根据权利要求1-5任一项所述的方法,其中,在确定所述性能指标劣化之后,还包括:The method according to any one of claims 1 to 5, wherein after determining that the performance index has deteriorated, the method further comprises:展示所述性能指标劣化的预警信息。Display the early warning information of the deterioration of the performance index.
- 一种性能指标的预警装置,包括:An early warning device for performance indicators, including:预测数据确定模块,用于根据性能指标的历史数据,确定设定时间段内所述性能指标的预测数据;A predictive data determining module, which is used to determine the predictive data of the performance index in a set time period according to the historical data of the performance index;曲线确定模块,用于根据所述预测数据和所述性能指标在设定时间段内的实际数据的差值,确定所述差值的变化趋势曲线;A curve determination module, configured to determine the change trend curve of the difference according to the difference between the predicted data and the actual data of the performance index in a set time period;性能指标劣化确定模块,用于如果所述差值达到所述变化趋势曲线中对应的差值阈值的时长小于设定时长,则确定所述性能指标劣化。The performance index degradation determining module is configured to determine that the performance index is degraded if the time period during which the difference reaches the corresponding difference threshold in the change trend curve is less than a set time period.
- 根据权利要求7所述的装置,其中,所述预测数据确定模块用于:The device according to claim 7, wherein the predictive data determining module is configured to:获取所述性能指标在历史时间段内的历史数据;Acquiring historical data of the performance indicator in a historical time period;根据预测算法和所述历史数据,确定所述预测算法的参数信息;Determine the parameter information of the prediction algorithm according to the prediction algorithm and the historical data;根据所述参数信息,确定所述性能指标在设定时间段内的预测数据。According to the parameter information, the predicted data of the performance index in a set time period is determined.
- 一种设备,包括:A device that includes:一个或多个处理器;One or more processors;存储器,用于存储一个或多个程序;Memory, used to store one or more programs;当所述一个或多个程序被所述一个或多个处理器执行时,使得所述一个或多个处理器实现如权利要求1-6中任一项所述的性能指标的预警方法。When the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the early warning method for performance indicators according to any one of claims 1-6.
- 一种存储介质,其上存储有计算机程序,其中,该程序被处理器执行时实现如权利要求1-6中任一项所述的性能指标的预警方法。A storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the early warning method of the performance index according to any one of claims 1 to 6 is realized.
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