Abnormal terminal determination method and device, storage medium and electronic equipment

Abstract

The invention discloses an abnormal terminal determination method and device, a storage medium and electronic equipment. The method comprises the steps that identification information of multiple target terminals is acquired, and the identification information is used for identifying the terminal types of the target terminals; based on the multiple identification information, target evaluation results of the multiple target terminals are determined, and the target evaluation results are used for representing voice communication performance of the target terminals; differential analysis is carried out on the multiple target evaluation results, analysis results of the multiple target terminals are obtained, and the analysis results are used for representing that the multiple target terminals comprise terminals with abnormal communication states; and on the basis of an analysis result, determining an abnormal terminal from the multiple target terminals. The technical problem that the abnormal terminal cannot be accurately determined is solved.

Description

Technical Field

[0001] The present application relates to the field of computer security, and in particular to a method, device, storage medium, and electronic device for determining an abnormal terminal. Background Art

[0002] At present, with the rapid development of the times, mobile terminals are constantly being updated and iterated, and there are more and more types of terminals in mobile networks. Due to the uneven quality of terminals, the technical problem of being unable to accurately identify abnormal terminals arises.

[0003] Currently, no effective solution has been proposed to the above-mentioned technical problem of being unable to accurately identify abnormal terminals. Summary of the Invention

[0004] The embodiments of the present application provide a method, apparatus, storage medium, and electronic device for determining an abnormal terminal, so as to at least solve the technical problem of being unable to accurately determine an abnormal terminal.

[0005] According to one aspect of an embodiment of the present application, a method for determining abnormal terminals is provided. The method may include: obtaining identification information of multiple target terminals, wherein the identification information is used to identify the terminal type of the target terminal; determining target evaluation results for the multiple target terminals based on the multiple identification information, wherein the target evaluation results are used to characterize the voice communication performance of the target terminals; performing differential analysis on the multiple target evaluation results to obtain analysis results for the multiple target terminals, wherein the analysis results are used to characterize whether the multiple target terminals include terminals with abnormal communication states; and determining abnormal terminals from the multiple target terminals based on the analysis results.

[0006] Optionally, based on multiple identification information, target evaluation results of multiple target terminals are determined, including: obtaining demand information of the target terminal and a measurement report of the target terminal, wherein the demand information is used to characterize the user's communication demand for the target terminal; based on the multiple identification information, demand information and measurement reports, respectively determining a first evaluation value, a second evaluation value and a third evaluation value of the multiple target terminals, wherein the first evaluation value is used to evaluate the signal coverage of the target terminal for a preset area, the second evaluation value is used to evaluate the connection status of the target terminal, and the third evaluation value is used to evaluate the data packet loss situation of the target terminal during the communication process; based on multiple first evaluation values, multiple second evaluation values and multiple third evaluation values, multiple target evaluation results are determined.

[0007] Optionally, based on multiple first evaluation values, multiple second evaluation values and multiple third evaluation values, multiple target evaluation results are determined, including: establishing a first matrix based on multiple first evaluation values, multiple second evaluation values and multiple third evaluation values; performing forward processing on the first matrix to obtain a second matrix, wherein the indicator type in the second matrix is smaller than the indicator type in the first matrix; performing normalization processing on the second matrix to obtain a third matrix, wherein the numerical range of the third matrix is smaller than the numerical range of the second matrix; and determining multiple target evaluation results based on the third matrix.

[0008] Optionally, based on the third matrix, multiple target evaluation results are determined, including: obtaining a first target value and a second target value of the third matrix, wherein the first target value is greater than the second target value; based on the third matrix and the first target value, determining a first distance of the target terminal, and based on the third matrix and the second target value, determining a second distance of the target terminal; based on the first distance and the second distance, determining multiple target evaluation results.

[0009] Optionally, differential analysis is performed on multiple target evaluation results respectively to obtain analysis results of multiple target terminals, including: sorting the multiple target evaluation results according to the target sorting strategy to obtain multiple target evaluation results after sorting, wherein the target sorting strategy is used to characterize the rules for sorting multiple data; differential analysis is performed on the multiple target evaluation results after sorting to obtain analysis results.

[0010] Optionally, differential analysis is performed on the multiple target evaluation results after sorting processing to obtain analysis results, including: performing differential processing on the multiple target evaluation results after sorting processing to obtain multiple target evaluation results after differential processing, wherein the target evaluation results are represented by target evaluation values; respectively comparing the multiple target evaluation values after differential processing with the evaluation threshold to obtain comparison results; in response to the comparison result being that any target evaluation value among the multiple target evaluation values after differential processing is greater than the evaluation threshold, determining the analysis result.

[0011] According to another aspect of an embodiment of the present application, a device for determining an abnormal terminal is also provided, including: an acquisition unit, used to acquire identification information of multiple target terminals, wherein the identification information is used to identify the terminal type of the target terminal; a first determination unit, used to determine target evaluation results of multiple target terminals based on multiple identification information, wherein the target evaluation results are used to characterize the voice communication performance of the target terminal; an analysis unit, used to perform differential analysis on multiple target evaluation results respectively to obtain analysis results of multiple target terminals, wherein the analysis results are used to characterize that the multiple target terminals include terminals with abnormal communication status; a second determination unit, used to determine abnormal terminals from the multiple target terminals based on the analysis results.

[0012] According to another aspect of an embodiment of the present application, a non-volatile storage medium is further provided, including: the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute any one of the methods for determining an abnormal terminal.

[0013] According to another aspect of an embodiment of the present application, an electronic device is further provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions to implement any one of the methods for determining an abnormal terminal.

[0014] According to another aspect of an embodiment of the present application, a computer program product is further provided, comprising: computer instructions, wherein when the computer instructions are executed by a processor, any one of the methods for determining an abnormal terminal is implemented.

[0015] In an embodiment of the present application, identification information of multiple target terminals is obtained, wherein the identification information is used to identify the terminal type of the target terminal; based on the multiple identification information, target evaluation results of the multiple target terminals are determined, wherein the target evaluation results are used to characterize the voice communication performance of the target terminal; differential analysis is performed on the multiple target evaluation results to obtain analysis results of the multiple target terminals, wherein the analysis results are used to characterize that the multiple target terminals include terminals with abnormal communication states; based on the analysis results, abnormal terminals are determined from the multiple target terminals. That is to say, in an embodiment of the present application, identification information of multiple target terminals can be obtained first, and then target evaluation results of the multiple target terminals can be determined based on the multiple identification information obtained above. Then, differential analysis can be performed on the multiple target evaluation results respectively to obtain analysis results of the multiple target terminals. Finally, based on the analysis results, abnormal terminals can be determined from the multiple target terminals. Considering that after the target evaluation results of the multiple target terminals are determined based on the identification information of the terminal type used to identify the target terminal, differential analysis can be performed on the multiple target evaluation results, so that it can be determined that the multiple target terminals include terminals with abnormal communication states. At this time, the abnormal terminal can be determined from the multiple target terminals to solve the technical problem of not being able to accurately determine the abnormal terminal, thereby achieving the technical effect of accurately determining the abnormal terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 is a flowchart of a method for determining an abnormal terminal according to an embodiment of the present application;

[0018] Figure 2is a flow chart of a method for identifying abnormal terminal models according to an embodiment of the present application;

[0019] Figure 3 is a schematic diagram of a device for determining an abnormal terminal according to an embodiment of the present application;

[0020] Figure 4 This is a schematic diagram of an exemplary electronic device for implementing an embodiment of the present application according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] According to an embodiment of the present application, an embodiment of a method for determining an abnormal terminal is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0024] Figure 1 is a flow chart of a method for determining an abnormal terminal according to an embodiment of the present application, such as Figure 1 As shown, the method includes the following steps:

[0025] Step S102: Acquire identification information of various target terminals.

[0026] In the technical solution provided in the above step S102 of the present application, identification information of multiple target terminals is obtained, wherein the identification information is used to identify the terminal type of the target terminal. The target terminal refers to a device that receives information during communication or data transmission, which can be called an evaluation object, or simply referred to as a terminal, and can be represented by i, such as a smart phone, a tablet computer, etc.

[0027] Optionally, the terminal type of the target terminal is obtained by identifying the type allocation code (TAC) of the target terminal, wherein the terminal type is used to characterize different terminals representing different terminal models, such as mobile device terminals.

[0028] For example, by identifying the TAC identifiers of different terminals, the terminal model corresponding to each mobile terminal can be identified. It should be noted that this is only an example and does not specifically limit the process and method of obtaining identification information of multiple target terminals.

[0029] Step S104: determining target evaluation results of multiple target terminals based on multiple identification information.

[0030] In the technical solution provided in the above step S104 of the present application, after obtaining a plurality of identification information, the target evaluation results of the target terminals corresponding to the plurality of identification information can be determined respectively, wherein the target evaluation results are used to characterize the voice communication performance of the target terminal, which can be represented by a target evaluation value, which can be called a voice performance value and can be represented by S. Then, the target evaluation value of the i-th target terminal can be represented by S. i To express.

[0031] For example, after identifying target terminals of multiple different terminal models, target evaluation results of the multiple different terminal models can be determined based on user demand information, thereby evaluating the voice communication performance of each terminal and improving the accuracy of the evaluation.

[0032] It should be noted that this is only a preferred implementation method for determining the target evaluation results of multiple target terminals, and no examples are given for determining the target evaluation results of multiple target terminals. As long as the process and method for determining the target evaluation results of multiple target terminals are based on multiple identification information, they are within the scope of protection of this application and are not listed here.

[0033] Step S106 , performing differential analysis on the multiple target evaluation results respectively to obtain analysis results of multiple target terminals.

[0034] In the technical solution provided in the above step S106 of the present application, differential analysis is performed on the multiple target evaluation results obtained to obtain analysis results of multiple target terminals, wherein the analysis results are used to characterize whether the multiple target terminals include terminals with abnormal communication status.

[0035] Optionally, a differential detection algorithm is used to perform differential analysis on multiple target evaluation results to obtain analysis results of multiple target terminals, wherein the differential detection algorithm is used to detect and identify changes or differences in data or signals.

[0036] For example, after obtaining multiple target evaluation results, since the voice performance calculated by normal terminals varies greatly, and the performance calculated by terminals with abnormal voice performance is significantly different from that calculated and processed by normal terminals, it can be understood that there is a large jump in voice performance. Therefore, a differential detection algorithm is used to perform differential analysis on multiple target evaluation results to achieve the purpose of determining whether the target terminals include terminals with abnormal communication status, and thus accurately identify abnormal terminals.

[0037] It can be understood that this is only a preferred implementation method for obtaining analysis results of multiple target terminals, and does not specifically limit the process and method of obtaining analysis results of multiple target terminals. As long as differential analysis is performed on multiple target evaluation results respectively, the process and method of obtaining analysis results of multiple target terminals are within the scope of protection of this application and will not be listed here.

[0038] Step S108: Based on the analysis result, abnormal terminals are determined from the multiple target terminals.

[0039] In the technical solution provided in the above step S108 of the present application, based on the analysis results, abnormal terminals can be determined from a variety of target terminals, thereby preventing potential security threats.

[0040] Optionally, when the analysis results have determined that multiple target terminals include terminals with abnormal communication status, the abnormal terminals can be filtered out from the multiple target terminals according to the filtering rules. For example, while using a differential detection algorithm to detect that multiple target terminals include terminals with abnormal communication status, the abnormal terminals can be filtered out.

[0041] It should be noted that this is only a preferred implementation method for determining abnormal terminals from multiple target terminals, and does not specifically limit the process and method for determining abnormal terminals from multiple target terminals. As long as it is based on the analysis results, the process and method for determining abnormal terminals from multiple target terminals are within the scope of protection of this application and will not be repeated here.

[0042] In an embodiment of the present application, identification information of multiple target terminals is obtained, wherein the identification information is used to identify the terminal type of the target terminal; based on the multiple identification information, target evaluation results of the multiple target terminals are determined, wherein the target evaluation results are used to characterize the voice communication performance of the target terminal; differential analysis is performed on the multiple target evaluation results to obtain analysis results of the multiple target terminals, wherein the analysis results are used to characterize that the multiple target terminals include terminals with abnormal communication states; based on the analysis results, abnormal terminals are determined from the multiple target terminals. That is to say, in an embodiment of the present application, identification information of multiple target terminals can be obtained first, and then target evaluation results of the multiple target terminals can be determined based on the multiple identification information obtained above. Then, differential analysis can be performed on the multiple target evaluation results respectively to obtain analysis results of the multiple target terminals. Finally, based on the analysis results, abnormal terminals can be determined from the multiple target terminals. Considering that after the target evaluation results of the multiple target terminals are determined based on the identification information of the terminal type used to identify the target terminal, differential analysis can be performed on the multiple target evaluation results, so that it can be determined that the multiple target terminals include terminals with abnormal communication states. At this time, the abnormal terminal can be determined from the multiple target terminals to solve the technical problem of not being able to accurately determine the abnormal terminal, thereby achieving the technical effect of accurately determining the abnormal terminal.

[0043] In some embodiments of the present application, target evaluation results of multiple target terminals are determined based on multiple identification information, including: obtaining demand information of the target terminal and a measurement report of the target terminal, wherein the demand information is used to characterize the user's communication demand for the target terminal; based on the multiple identification information, demand information and measurement reports, respectively determining a first evaluation value, a second evaluation value and a third evaluation value of the multiple target terminals, wherein the first evaluation value is used to evaluate the signal coverage of the target terminal for a preset area, the second evaluation value is used to evaluate the connection status of the target terminal, and the third evaluation value is used to evaluate the data packet loss situation of the target terminal during the communication process; based on multiple first evaluation values, multiple second evaluation values and multiple third evaluation values, multiple target evaluation results are determined.

[0044] In this embodiment, the demand information and measurement report (Measurement Report, abbreviated as MR) of the target terminal can be obtained, and then the first evaluation value, second evaluation value and third evaluation value of multiple target terminals can be determined respectively based on multiple identification information, demand information and measurement reports. Based on the multiple first evaluation values, multiple second evaluation values and multiple third evaluation values obtained above, the purpose of determining multiple target evaluation results can be achieved.

[0045] Optionally, the first evaluation value may be MR coverage, where MR coverage refers to the proportion of received signal reference power (RSRP) in the measurement report that is greater than or equal to a preset threshold. RSRP is a parameter for measuring the signal strength received by the user equipment, for example, 95%.

[0046] Furthermore, MR coverage can be obtained by using Deep Packet Inspection (DPI) data obtained by the DPI technology and MR data from the wireless network management to obtain the MR values of various terminal models from the start of the voice call to the end of the call.

[0047] Optionally, the second evaluation value may be a connection rate, which may be referred to as a voice connection rate, wherein the connection rate is used to represent the proportion of calls that successfully establish connections in a communication system, particularly a call center or a telephone network, for example, 85%.

[0048] Furthermore, the connection rate can be obtained by aggregating and outputting the end-to-end voice connection rate of each terminal model based on DPI data (for example, using the network connection rate, and excluding records of unconnected calls due to user or business reasons).

[0049] Optionally, the third evaluation value may be a packet loss rate, which may be referred to as a voice packet loss rate. The packet loss rate is used to indicate the proportion of data packets lost during data transmission. Specifically, the packet loss rate refers to the ratio of the number of data packets sent by the sender that fail to successfully reach the receiver to the total number of data packets sent within a period of time, for example, 0%.

[0050] Furthermore, the packet loss rate can be obtained by collecting the uplink packet loss rate of each terminal based on the DPI data and using the Real-time Transport Protocol (RTP).

[0051] For example, after obtaining demand information, measurement reports and multiple identification information, the MR coverage, connection rate and packet loss rate corresponding to each terminal can be determined respectively. Then, based on the three indicators obtained above, the target evaluation value of each terminal can be determined to evaluate the voice communication performance of the terminal.

[0052] In some optional embodiments of the present application, multiple target evaluation results are determined based on multiple first evaluation values, multiple second evaluation values, and multiple third evaluation values, including: establishing a first matrix based on multiple first evaluation values, multiple second evaluation values, and multiple third evaluation values; performing forward processing on the first matrix to obtain a second matrix, wherein the indicator type in the second matrix is smaller than the indicator type in the first matrix; performing normalization processing on the second matrix to obtain a third matrix, wherein the numerical range of the third matrix is smaller than the numerical range of the second matrix; and determining multiple target evaluation results based on the third matrix.

[0053] In this embodiment, a first matrix is established based on a plurality of first evaluation values, a plurality of second evaluation values, and a plurality of third evaluation values. The first matrix is then forward processed to obtain a second matrix. The second matrix is then normalized to obtain a third matrix. Based on the third matrix obtained in this manner, multiple target evaluation results can be determined. The plurality of first evaluation values, the plurality of second evaluation values, and the plurality of third evaluation values can be collectively referred to as raw data, and the forward processing can be referred to as forward normalization processing.

[0054] Optionally, the first matrix can be called a calculation matrix. When there are n target terminals, that is, n evaluation objects, and m evaluation indicators, the dimension of the calculation matrix is n*m. The second matrix can be called a forward matrix, which can be represented by X, that is, matrix X, then x ij is the element in the second matrix. The third matrix can be represented by Y, which can be called matrix Y, then y ij are the elements in the third matrix.

[0055] Alternatively, matrix forward processing refers to the situation in which, in practical applications, larger indicators indicate better results, smaller indicators indicate better results, and there are also issues of positive and negative correlation. In this case, the original data needs to be forward-normalized to achieve an evaluation result where larger indicators indicate better results. Normalization of the forward-normalized matrix is used to eliminate the influence of different dimensions.

[0056] For example, the raw data is formed into a calculation matrix. Each row can represent the three key dimensions corresponding to a terminal: MR coverage, connection rate, and packet loss rate. Each row has three columns. By performing forward processing on the calculation matrix, a forward matrix can be obtained. Assuming there are n evaluation objects and m evaluation indicators (which have been forward-normalized), the forward matrix that can be constructed is as follows:

[0057]

[0058] The standardized matrix is then recorded as Y, and each element of Y can be expressed by the following formula:

[0059]

[0060] Among them, y ij is an element in the matrix Y, x ij is an element in the matrix X. The standardized matrix is processed in the following steps to determine the target evaluation result of each target terminal, that is, the target evaluation value.

[0061] In some optional embodiments of the present application, multiple target evaluation results are determined based on a third matrix, including: obtaining a first target value and a second target value of the third matrix, wherein the first target value is greater than the second target value; determining a first distance of the target terminal based on the third matrix and the first target value, and determining a second distance of the target terminal based on the third matrix and the second target value; and determining multiple target evaluation results based on the first distance and the second distance.

[0062] In this embodiment, after obtaining the third matrix, the first target value and the second target value of the third matrix are obtained, and then the first distance can be determined according to the first target value of the third matrix, and the second distance can be determined according to the third matrix and the second target value. According to the first distance and the second distance obtained above, multiple target evaluation results of the target terminal can be determined. Among them, the first target value is the maximum value, which can be obtained by Y + The second target value is the minimum value, which can be expressed by Y - The first distance can be represented by D + The second distance can be represented by D - The target evaluation value can be called a score.

[0063] Optionally, the maximum value and minimum value of each column in the third matrix are obtained, and then the first distance of the target terminal can be determined based on the element corresponding to the target terminal in the third matrix and the maximum value of each column. According to the above execution steps, the first distance of each target terminal can be obtained, and the second distance of the target terminal can be determined based on the element corresponding to the target terminal in the third matrix and the minimum value of each column. According to the above execution steps, the second distance of each target terminal can be obtained. Based on the multiple first distances and multiple second distances obtained above, multiple target evaluation values can be determined.

[0064] Optionally, a difference operation is performed between the element of the target terminal in the third matrix and the maximum value of each column to obtain multiple first difference values; the multiple first difference values are squared respectively to obtain multiple first difference values after square processing; the multiple first difference values after square processing are summed to obtain a first sum value; and a square root operation is performed on the first sum value to obtain a first distance.

[0065] Optionally, a difference operation is performed between the element of the target terminal in the third matrix and the minimum value of each column to obtain multiple second difference values; the multiple second difference values are squared respectively to obtain multiple second difference values after square processing; the multiple second difference values after square processing are summed to obtain a second sum value; and a square root operation is performed on the second sum value to obtain a second distance.

[0066] For example, first identify the maximum and minimum values of each column in the third matrix, as shown below:

[0067] Y + ={max(y 11 …y n1 )max(y 12 …y n2 )…max(y 1m …y nm )}

[0068] Y - ={min(y 11 …y n1 )min(y 12 …y n2 )…min(y 1m …y nm )}

[0069] Then the first distance is the distance between the i-th evaluation object and the maximum value, and can be obtained by the following formula:

[0070]

[0071] Furthermore, the second distance is the distance between the i-th evaluation object and the minimum value, and can be expressed by the following formula:

[0072]

[0073] After obtaining the first distance and the second distance, the score of the i-th evaluation object can be obtained, which can be expressed by the following formula:

[0074]

[0075] Where 0≤S i ≤1, and S i The larger it is, the closer it is to the maximum value. i A larger value indicates better terminal voice performance, and a smaller value indicates worse terminal performance.

[0076] In some embodiments of the present application, differential analysis is performed on multiple target evaluation results to obtain analysis results of multiple target terminals, including: sorting the multiple target evaluation results according to the target sorting strategy to obtain multiple target evaluation results after sorting, wherein the target sorting strategy is used to characterize the rules for sorting multiple data; differential analysis is performed on the multiple target evaluation results after sorting to obtain analysis results.

[0077] In this embodiment, according to the target sorting strategy, it is necessary to sort the multiple target evaluation values to obtain the sorted multiple target evaluation values, and then perform differential analysis on the sorted multiple target evaluation values to obtain analysis results. In particular, according to the target sorting strategy, the sorting of the multiple target evaluation values can be performed in ascending order.

[0078] Optionally, a bubble algorithm is used to sort the multiple target evaluation values in ascending order to obtain multiple target evaluation values sorted from small to large, and then a differential analysis is performed on the multiple target evaluation values sorted from small to large to obtain an analysis result. The bubble algorithm can be called a bubble sort algorithm or a bubble sort.

[0079] Specifically, the process of using bubble sort to sort multiple target evaluation values in ascending order is as follows: In the first round of bubble sort, the first and second numbers are compared. If the first number is greater than the second, the two numbers are swapped; otherwise, they remain unchanged. Next, the second and third numbers are compared, and this process is repeated until the last two numbers in the current round of numbers (a total of n evaluation objects) have been processed. The second round of bubble sort performs the same sorting as the first round, swapping the larger number to the n-1 position. This process is repeated for a total of n-1 rounds of bubble sort, and the data is sorted in ascending order.

[0080] The core idea of the bubble sorting algorithm is to compare two adjacent numbers in a set of numbers to be sorted. If the first number is larger than the second, the two numbers are swapped; otherwise, they are not swapped. This process continues until the sorting is complete. As can be seen, during the sorting process, larger numbers sink to the bottom and smaller numbers float to the top, just like bubbles. This is why this sorting algorithm is called bubble sort.

[0081] In some optional embodiments of the present application, differential analysis is performed on multiple target evaluation results after sorting processing to obtain analysis results, including: performing differential processing on multiple target evaluation results after sorting processing to obtain multiple target evaluation results after differential processing, wherein the target evaluation results are represented by target evaluation values; comparing the multiple target evaluation values after differential processing with evaluation thresholds respectively to obtain comparison results; and determining the analysis result in response to the comparison result being that any target evaluation value among the multiple target evaluation values after differential processing is greater than the evaluation threshold.

[0082] In this embodiment, the multiple target evaluation values after sorting are subjected to differential processing to obtain multiple target evaluation values after differential processing. The multiple target evaluation values after differential processing are respectively compared with the evaluation threshold to obtain comparison results. If the comparison result shows that any target evaluation value among the multiple target evaluation values after differential processing is greater than the evaluation threshold, the analysis result is determined. The evaluation threshold can be a preset threshold or a calculated value, such as 10.

[0083] Optionally, a target terminal whose target evaluation value among multiple target evaluation values after differential processing is greater than the evaluation threshold is determined as an abnormal terminal. For example, when the target evaluation value is 11, the target evaluation value is greater than the evaluation threshold 10, then the target terminal corresponding to the target evaluation value can be determined as an abnormal terminal.

[0084] Optionally, differential calculations are performed on the multiple target evaluation values after sorting to obtain multiple first differential values; the multiple first differential values are averaged to obtain a first mean; the absolute values of the multiple first differential values are calculated to obtain multiple second differential values; the multiple second differential values are compared with the first mean to obtain comparison results; in response to the comparison result being that any second differential value among the multiple second differential values is greater than the first mean, the analysis result is determined.

[0085] For example, first calculate the S i The values are then differentiated one by one (in descending order), and the differences are averaged to obtain the mean. The results of the differential calculations are then converted to absolute values and compared with the absolute value of the mean difference values, starting from the last value. The terminal type with the first result of 10 or greater is output. Terminals before this value are considered abnormal terminals with abnormal voice performance.

[0086] In an embodiment of the present application, identification information of multiple target terminals is first obtained, and then target evaluation results of the multiple target terminals are determined based on the multiple identification information obtained above. Then, differential analysis is performed on the multiple target evaluation results to obtain analysis results of the multiple target terminals. Finally, based on the analysis results, abnormal terminals can be determined from the multiple target terminals. Considering that after the target evaluation results of the multiple target terminals are determined based on the identification information of the terminal type used to identify the target terminal, differential analysis can be performed on the multiple target evaluation results, so that it can be determined that the multiple target terminals include terminals with abnormal communication states. At this time, the abnormal terminal can be determined from the multiple target terminals to solve the technical problem of not being able to accurately determine the abnormal terminal, thereby achieving the technical effect of accurately determining the abnormal terminal.

[0087] The technical solutions of the embodiments of the present application are illustrated below with reference to preferred implementation methods.

[0088] At present, with the rapid development and update iteration of mobile terminals, there are more and more terminal types in the fourth generation mobile communication technology (4G) or fifth generation mobile communication technology (5G) 5G networks. However, due to the uneven quality of terminals, the technical problem of being unable to accurately identify abnormal terminals has arisen.

[0089] In order to solve the above problems, the present application proposes a method for determining abnormal terminals, which can first obtain identification information of multiple target terminals, and then determine target evaluation results of multiple target terminals based on the multiple identification information obtained above, and then perform differential analysis on the multiple target evaluation results respectively to obtain analysis results of the multiple target terminals. Finally, based on the analysis results, the abnormal terminal can be determined from the multiple target terminals. Considering that after the target evaluation results of the multiple target terminals are determined based on the identification information of the terminal type used to identify the target terminal, the multiple target evaluation results can be differentially analyzed, so that it can be determined that the multiple target terminals include terminals with abnormal communication states. At this time, the abnormal terminal can be determined from the multiple target terminals to solve the technical problem of not being able to accurately determine the abnormal terminal, and achieve the technical effect of accurately determining the abnormal terminal.

[0090] In order to facilitate those skilled in the art to better understand the technical solution of the present application, a specific embodiment is now described.

[0091] In an embodiment of the present application, a method for identifying abnormal terminal models is proposed. The method mainly identifies terminal models with abnormal voice capabilities based on the DPI data of the core network and the MR data of the wireless network management. First, based on the actual usage perception of voice users, the MR coverage rate, voice connection rate and voice packet loss rate of voice terminals are introduced as three key dimensions for evaluating the voice capabilities of terminals; next, the three key evaluation indicators of each terminal model are associated with the DPI data and MR data, and finally the voice capabilities of each terminal model are ranked to achieve the purpose of identifying terminal models with abnormal voice capabilities. Taking into account the identification of abnormal terminals with abnormal voice capabilities based on DPI data and MR data, problem users are discovered and the user's voice perception is guaranteed.

[0092] Figure 2 is a flow chart of a method for identifying abnormal terminal models according to an embodiment of the present application, such as Figure 2 As shown, the method may include the following steps:

[0093] Step S201: Determine the voice key indicators of the terminal.

[0094] In this embodiment, during daily voice usage, mobile users are primarily concerned with whether a call can be connected and whether the conversation can proceed normally after the call is connected. This allows the terminal's key voice indicators to be determined. Since the ability to connect and the ability to conduct conversations are the two areas of greatest concern to users in our daily work, we have derived the three most relevant indicators for these two situations: the user's MR coverage, voice connection rate, and voice packet loss rate. (Since the downlink voice packet loss rate is provided by the terminal and can be somewhat deceptive, the uplink voice packet loss rate is used as the voice packet loss rate in this application.)

[0095] Step S202: Identify the key indicators of each terminal model to obtain the voice performance value of each terminal.

[0096] In this embodiment, the terminal model corresponding to each mobile terminal can be identified through the TAC identifier, thereby identifying the key indicators of each terminal model to obtain the voice performance value of each terminal, where the key indicators include three types, namely, connection rate, packet loss rate and MR coverage.

[0097] Optionally, MR coverage can be calculated by using DPI data obtained through deep packet inspection (DPI) and MR data from wireless network management (WNM) to obtain the MR values for various terminal models from the start to the end of a voice call. The MR value refers to the RSRP value of a specific MR, and MR coverage can be understood as the proportion of all MRs in an area with RSRP values greater than a certain value.

[0098] Optionally, the connection rate can be obtained by aggregating and outputting the end-to-end voice connection rates of each terminal model based on DPI data (for example, using the network connection rate, and excluding records of unconnected calls due to user or business reasons).

[0099] Optionally, the packet loss rate may be obtained by collecting the uplink packet loss rate of each terminal based on DPI data and using the real-time transport protocol.

[0100] Step S203: sorting the voice performance values of the terminals.

[0101] In this embodiment, the speech performance values of each terminal are ranked using the near-ideal solution ranking method. This method is a commonly used comprehensive evaluation method that fully utilizes the original data information and reflects the differences between the various alternative solutions. The near-ideal solution ranking method mainly consists of four steps: matrixing the original data, matrix forwarding, normalizing the forward matrix, and score calculation, as shown below:

[0102] The original data is matrixed to form a calculation matrix. Each row can represent the three key dimensions corresponding to a terminal, namely MR coverage, connection rate, and packet loss rate, and each has three columns.

[0103] The original matrix is normalized, which means that in practical applications, the larger the indicators are, the better the results are, and the smaller the indicators are, the better the results are, as well as the positive and negative problems. In this case, the original data needs to be normalized to achieve an evaluation result in which the larger the indicator result is, the better the effect is.

[0104] The normalization matrix is used to eliminate the influence of different dimensions. Assuming there are n evaluation objects and m evaluation indicators (already normalized), the normalization matrix that can be constructed is as follows:

[0105]

[0106] The standardized matrix is then recorded as Y, and each element of Y can be expressed by the following formula:

[0107]

[0108] Among them, y ij is an element in the matrix Y, x ij are the elements in the matrix X.

[0109] To calculate the score, first identify the maximum and minimum values of each column in the matrix Y, as shown below:

[0110] Y + ={max(y 11 …y n1 )max(y12 …y n2 )…max(y 1m …y nm )}

[0111] Y - ={min(y 11 …y n1 )min(y 12 …y n2 )…min(y 1m …y nm )}

[0112] Then the first distance is the distance between the i-th evaluation object and the maximum value, and can be obtained by the following formula:

[0113]

[0114] Furthermore, the second distance is the distance between the i-th evaluation object and the minimum value, and can be expressed by the following formula:

[0115]

[0116] After obtaining the first distance and the second distance, the score of the i-th evaluation object can be obtained, which can be expressed by the following formula:

[0117]

[0118] Where 0≤S i ≤1, and S i The larger it is, the closer it is to the maximum value. i A larger value indicates better terminal voice performance, and a smaller value indicates worse terminal performance.

[0119] Optionally, after obtaining the S of each terminal i After the value is obtained, the bubble algorithm is used to calculate the S of each terminal. i To sort the values in ascending order, the process is as follows: In the first round of bubble sort, the first and second numbers are compared. If the first number is greater than the second, the two numbers are swapped; otherwise, they remain unchanged. Next, the second and third numbers are compared, and this process is repeated until the last two numbers in the series (a total of n evaluation objects) have been processed. The second round of bubble sort performs the same sorting as the first round, swapping the larger number to position n-1. This process is repeated for a total of n-1 rounds of bubble sort until the data is sorted in ascending order.

[0120] The core idea of the bubble sorting algorithm is to compare two adjacent numbers in a set of numbers to be sorted. If the first number is larger than the second, the two numbers are swapped; otherwise, they are not swapped. This process continues until the sorting is complete. As a result, during the sorting process, larger numbers sink to the bottom and smaller numbers float to the top, just like bubbles. This is why this sorting algorithm is called bubble sort.

[0121] Step S204: output the abnormal terminal.

[0122] In this embodiment, a differential detection algorithm is used to output abnormal terminals. Since the voice performance calculated by normal terminals varies greatly, and the performance calculated by terminals with abnormal voice performance is significantly different from that calculated and processed by normal terminals, it can be understood that there is a large jump in voice performance, and thus a differential detection algorithm is used to output abnormal terminals.

[0123] Optionally, the process of outputting abnormal terminals using the differential detection algorithm is as follows: First, the calculated S i The values are then differentiated one by one (in descending order), and the differences are averaged to obtain the mean. The results of the differential calculations are then converted to absolute values and compared with the absolute value of the mean difference values, starting from the last value. The terminal type with the first result of 10 or greater is output. Terminals before this value are considered abnormal terminals with abnormal voice performance.

[0124] In an embodiment of the present application, identification information of multiple target terminals is first obtained, and then target evaluation results of the multiple target terminals are determined based on the multiple identification information obtained above. Then, differential analysis is performed on the multiple target evaluation results to obtain analysis results of the multiple target terminals. Finally, based on the analysis results, abnormal terminals can be determined from the multiple target terminals. Considering that after the target evaluation results of the multiple target terminals are determined based on the identification information of the terminal type used to identify the target terminal, differential analysis can be performed on the multiple target evaluation results, so that it can be determined that the multiple target terminals include terminals with abnormal communication states. At this time, the abnormal terminal can be determined from the multiple target terminals to solve the technical problem of not being able to accurately determine the abnormal terminal, thereby achieving the technical effect of accurately determining the abnormal terminal.

[0125] Figure 3 is a schematic diagram of a device for determining an abnormal terminal according to an embodiment of the present application, such as Figure 3 As shown, the abnormal terminal determination device 300 includes: an acquisition unit 301 , a first determination unit 302 , an analysis unit 303 and a second determination unit 304 .

[0126] The acquiring unit 301 is configured to acquire identification information of multiple target terminals, wherein the identification information is used to identify the terminal type of the target terminal.

[0127] The first determining unit 302 is configured to determine target evaluation results of multiple target terminals based on multiple identification information, wherein the target evaluation results are used to characterize the voice communication performance of the target terminals.

[0128] The analyzing unit 303 is configured to perform differential analysis on the multiple target evaluation results to obtain analysis results of multiple target terminals, wherein the analysis results are used to indicate that the multiple target terminals include terminals in abnormal communication states.

[0129] The second determining unit 304 is configured to determine abnormal terminals from the multiple target terminals based on the analysis result.

[0130] Optionally, the first determination unit 302 includes: a first acquisition module, used to obtain demand information of the target terminal and a measurement report of the target terminal, wherein the demand information is used to characterize the user's communication demand for the target terminal; a first determination module, used to determine the first evaluation value, the second evaluation value and the third evaluation value of multiple target terminals based on multiple identification information, demand information and measurement reports, wherein the first evaluation value is used to evaluate the signal coverage of the target terminal for a preset area, the second evaluation value is used to evaluate the connection status of the target terminal, and the third evaluation value is used to evaluate the data packet loss situation of the target terminal during the communication process; a second determination module, used to determine multiple target evaluation results based on multiple first evaluation values, multiple second evaluation values and multiple third evaluation values.

[0131] Optionally, the second determination module may include: an establishment submodule for establishing a first matrix based on multiple first evaluation values, multiple second evaluation values and multiple third evaluation values; a first acquisition submodule for performing forward processing on the first matrix to obtain a second matrix, wherein the indicator type in the second matrix is smaller than the indicator type in the first matrix; a second acquisition submodule for performing standardization processing on the second matrix to obtain a third matrix, wherein the numerical range of the third matrix is smaller than the numerical range of the second matrix; and a first determination submodule for determining multiple target evaluation results based on the third matrix.

[0132] Optionally, the first determination submodule is also used to: obtain a first target value and a second target value of the third matrix, wherein the first target value is greater than the second target value; determine a first distance of the target terminal based on the third matrix and the first target value, and determine a second distance of the target terminal based on the third matrix and the second target value; and determine multiple target evaluation results based on the first distance and the second distance.

[0133] Optionally, the analysis unit 303 includes: a second acquisition module, used to sort the multiple target evaluation results according to the target sorting strategy to obtain multiple target evaluation results after sorting, wherein the target sorting strategy is used to characterize the rules for sorting multiple data; a third acquisition module, used to perform differential analysis on the multiple target evaluation results after sorting to obtain analysis results.

[0134] Optionally, the third acquisition module may include: a third acquisition sub-module, used to perform differential processing on the multiple target evaluation results after sorting processing to obtain multiple target evaluation results after differential processing, wherein the target evaluation results are represented by target evaluation values; a fourth acquisition sub-module, used to compare the multiple target evaluation values after differential processing with the evaluation threshold respectively to obtain a comparison result; a second determination sub-module, used to determine the analysis result in response to the comparison result being that any target evaluation value among the multiple target evaluation values after differential processing is greater than the evaluation threshold.

[0135] In the device, identification information of multiple target terminals is obtained by an acquisition unit 301, wherein the identification information is used to identify the terminal type of the target terminal; target evaluation results of the multiple target terminals are determined based on the multiple identification information by a first determination unit 302, wherein the target evaluation results are used to characterize the voice communication performance of the target terminal; differential analysis is performed on the multiple target evaluation results by an analysis unit 303 to obtain analysis results of the multiple target terminals, wherein the analysis results are used to characterize that the multiple target terminals include terminals with abnormal communication states; abnormal terminals are determined from the multiple target terminals based on the analysis results by a second determination unit 304, so as to solve the technical problem of being unable to accurately determine the abnormal terminals, thereby achieving the technical effect of being able to accurately determine the abnormal terminals.

[0136] According to another aspect of an embodiment of the present application, a non-volatile storage medium is further provided. The non-volatile storage medium includes a stored program, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute any one of the methods for determining an abnormal terminal.

[0137] Specifically, the above storage medium is used to store program instructions for the following functions to implement the following functions:

[0138] Obtain identification information of multiple target terminals, wherein the identification information is used to identify the terminal type of the target terminal; determine target evaluation results of the multiple target terminals based on the multiple identification information, wherein the target evaluation results are used to characterize the voice communication performance of the target terminals; perform differential analysis on the multiple target evaluation results respectively to obtain analysis results of the multiple target terminals, wherein the analysis results are used to characterize that the multiple target terminals include terminals with abnormal communication states; and determine abnormal terminals from the multiple target terminals based on the analysis results.

[0139] Alternatively, in this embodiment, the storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any suitable combination thereof. More specific examples of the storage medium may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0140] In an exemplary embodiment of the present application, a computer program product is further provided, including a computer program, which implements any of the above-mentioned methods for determining an abnormal terminal when executed by a processor.

[0141] Optionally, the computer program may implement the following steps when executed by a processor:

[0142] Obtain identification information of multiple target terminals, wherein the identification information is used to identify the terminal type of the target terminal; determine target evaluation results of the multiple target terminals based on the multiple identification information, wherein the target evaluation results are used to characterize the voice communication performance of the target terminals; perform differential analysis on the multiple target evaluation results respectively to obtain analysis results of the multiple target terminals, wherein the analysis results are used to characterize that the multiple target terminals include terminals with abnormal communication states; and determine abnormal terminals from the multiple target terminals based on the analysis results.

[0143] According to an embodiment of the present application, an electronic device is provided, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any of the above-mentioned methods for determining an abnormal terminal.

[0144] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0145] Figure 4Schematic diagram of an example electronic device for implementing an embodiment of the present application according to an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0146] like Figure 4 As shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 403. Various programs and data required for the operation of the device 400 can also be stored in the RAM 403. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0147] Various components in device 400 are connected to I / O interface 405, including an input unit 406, such as a keyboard, mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a magnetic disk, optical disk, etc.; and a communication unit 409, such as a network card, modem, wireless communication transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0148] The computing unit 401 can be a variety of general-purpose and / or specialized processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 401 performs the various methods and processes described above, such as the method for determining abnormal terminals. For example, in some embodiments, the method for determining abnormal terminals can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as the storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the method for determining abnormal terminals described above can be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute the abnormal terminal determination method in any other appropriate manner (for example, by means of firmware).

[0149] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0150] The program code for implementing the methods of the present application can be written in any combination of one or more programming languages. Such program code can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the program code is executed by the processor or controller, the functions / operations specified in the flow charts and / or block diagrams are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0151] In the context of the present application, a machine-readable medium can be a tangible medium that can contain or store a program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0152] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0153] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0154] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0155] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0156] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0157] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0158] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0159] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0160] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0161] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining an abnormal terminal, characterized in that: include: Acquiring identification information of multiple target terminals, wherein the identification information is used to identify the terminal type of the target terminal; Determining target evaluation results of the target terminals based on the multiple identification information, wherein the target evaluation results are used to characterize the voice communication performance of the target terminals; Performing differential analysis on the plurality of target evaluation results respectively to obtain analysis results of the plurality of target terminals, wherein the analysis results are used to indicate that the plurality of target terminals include a terminal in an abnormal communication state; Based on the analysis result, an abnormal terminal is determined from the multiple target terminals.

2. The method according to claim 1, characterized in that Determining target evaluation results of the target terminals based on the multiple identification information includes: Acquiring demand information of the target terminal and a measurement report of the target terminal, wherein the demand information is used to characterize the user's communication demand for the target terminal; Determine, based on the multiple identification information, the requirement information, and the measurement reports, a first evaluation value, a second evaluation value, and a third evaluation value of the multiple target terminals, respectively, wherein the first evaluation value is used to evaluate the signal coverage of the target terminal for a preset area, the second evaluation value is used to evaluate the connection status of the target terminal, and the third evaluation value is used to evaluate the data packet loss status of the target terminal during the communication process; A plurality of the target evaluation results are determined based on a plurality of the first evaluation values, a plurality of the second evaluation values, and a plurality of the third evaluation values.

3. The method according to claim 2, characterized in that Determining a plurality of target evaluation results based on a plurality of the first evaluation values, a plurality of the second evaluation values, and a plurality of the third evaluation values includes: establishing a first matrix based on a plurality of the first evaluation values, a plurality of the second evaluation values, and a plurality of the third evaluation values; Performing forward processing on the first matrix to obtain a second matrix, wherein the indicator type in the second matrix is smaller than the indicator type in the first matrix; performing normalization processing on the second matrix to obtain a third matrix, wherein a numerical range of the third matrix is smaller than a numerical range of the second matrix; Based on the third matrix, a plurality of target evaluation results are determined.

4. The method according to claim 3, characterized in that Based on the third matrix, a plurality of target evaluation results are determined, including: Obtaining a first target value and a second target value of the third matrix, wherein the first target value is greater than the second target value; determining a first distance of the target terminal based on the third matrix and the first target value, and determining a second distance of the target terminal based on the third matrix and the second target value; Based on the first distance and the second distance, a plurality of target evaluation results are determined.

5. The method according to claim 1, wherein Perform differential analysis on the multiple target evaluation results respectively to obtain analysis results of the multiple target terminals, including: Sorting the plurality of target evaluation results according to a target sorting strategy to obtain the plurality of target evaluation results after sorting, wherein the target sorting strategy is used to represent a rule for sorting the plurality of data; Perform differential analysis on the plurality of target evaluation results after sorting to obtain the analysis result.

6. The method according to claim 5, characterized in that Performing differential analysis on the plurality of target evaluation results after sorting to obtain the analysis results, including: Performing differential processing on the plurality of target evaluation results after sorting processing to obtain the plurality of target evaluation results after differential processing, wherein the target evaluation results are represented by target evaluation values; Comparing the plurality of target evaluation values after the difference processing with the evaluation threshold respectively to obtain a comparison result; In response to the comparison result being that any one of the plurality of target evaluation values after the differential processing is greater than the evaluation threshold, the analysis result is determined.

7. A device for determining an abnormal terminal, characterized in that: include: an acquiring unit, configured to acquire identification information of multiple target terminals, wherein the identification information is used to identify the terminal type of the target terminal; A first determining unit is configured to determine target evaluation results of a plurality of target terminals based on the plurality of identification information, wherein the target evaluation results are used to characterize the voice communication performance of the target terminals; an analyzing unit, configured to perform differential analysis on each of the plurality of target evaluation results to obtain analysis results of the plurality of target terminals, wherein the analysis results are used to indicate that the plurality of target terminals include a terminal in an abnormal communication state; The second determining unit is configured to determine an abnormal terminal from the multiple target terminals based on the analysis result.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored executable program, wherein when the executable program is run, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 6.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1 to 6.

10. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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