A Business Concurrency Prediction Method and Prediction System
A prediction method and technology of a prediction system, applied in the field of mobile communication, to achieve the effect of universal applicability
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Embodiment 1
[0053] Such as figure 1 The flow chart of the service concurrency prediction method provided by Embodiment 1 of the present invention, as shown in figure 1 As shown, the business concurrency prediction method includes:
[0054] S101: Determine at least two services;
[0055] Specifically, in order to grasp the usage of each service in advance and improve the carrying capacity of the network, it is necessary to predict the concurrency of services in a certain area in the future, and reasonably determine at least two services according to the forecast demand. For this service, the other Including but not limited to QQ, WeChat, Youku, Tudou, Taobao, Weibo, Baidu Map, etc.
[0056] In some embodiments, when at least two services are determined, according to the use of the services, for example, according to the frequency of use of the services, that is, within a period of time, the service with a higher frequency of use is defined as a frequently used service, and the service wi...
Embodiment 2
[0083] Such as image 3 A schematic structural diagram of the business concurrency prediction system provided in Embodiment 2 of the present invention, as shown in image 3 As shown, the business concurrency prediction system includes a determination module 1, an acquisition module 2, a generation module 3, and a prediction module 4. The determination module 1 is used to determine at least two services, and the acquisition module 2 is used to obtain the , business data corresponding to at least two businesses determined by the determination module 1, the generation module 3 is used to generate a tree-structured relationship network between at least two businesses based on the business data acquired by the acquisition module 2, and the prediction module 4 is used to According to the relationship network generated by the generating module 3, the concurrency of at least two services is predicted.
[0084] Preferably, the determining module 1 is specifically configured to determi...
Embodiment 3
[0091]The services involved in this embodiment are N (N ≥ 2 and positive integer) services most frequently used by users in the existing network, and the concurrency of the services most frequently used by users in the area to be predicted is predicted for a period of time in the future, and obtained In at least one historical time period, the service data corresponding to the most frequently used service by the user, the service data comes from all base stations in a certain area to be predicted in the live network, the at least one historical time period is a continuous time period, and every two The interval between historical time periods is 1 hour, that is, the time granularity is 1 hour, and the time span is 15 consecutive days before the time period to be predicted.
[0092] Such as Figure 4 Part of the data set selected from the sample data provided for Embodiment 3 of the present invention, such as Figure 4 As shown in FIG. 1 , the acquired business data is filtere...
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