Abstract: A failure analysis device 10 is provided with an identification unit 11 that discriminates whether a predetermined failure has occurred on the basis of a learning model for discriminating the presence or absence of an occurrence of the predetermined failure learned by using a cause attribute which is associated with a cause of the predetermined failure and on the basis of a value of the attribute, and that identifies the cause of the predetermined failure discriminated to have occurred and countermeasures therefor.

Abstract: An object of the present disclosure is to provide a control apparatus that controls a plurality of communication systems so that the plurality of communication systems can perform analysis with high accuracy. The control apparatus (30) according to the present disclosure includes a communication unit (31) and a determination unit (32). The communication unit (31) receives, from an analysis apparatus (10) configured to perform machine learning using communication logs collected from a communication apparatus in order to generate a learning model, statistical information about each of the communication logs and information about the learning model. The determination unit (32) determines an analysis apparatus (20) to which the information about the learning model is applied based on the statistical information.

Abstract: A first prediction unit 83 predicts the amount of future communication quality deterioration or the presence or absence of occurrence of future communication quality deterioration in a communication section between one communication device and another communication device communicably connected to the one communication device by using a first learning model generated on the basis of first attributes being attributes related to a cause of communication quality deterioration in the communication section. A second prediction unit 84 predicts the amount of future communication quality deterioration or the presence or absence of occurrence of future communication quality deterioration outside the communication section regarding one communication device by using a second learning model generated on the basis of second attributes being attributes related to a cause of communication quality deterioration outside the communication section regarding the one communication device.

Abstract: An object of the present disclosure is to provide a control apparatus that controls a plurality of communication systems so that the plurality of communication systems can perform analysis with high accuracy. The control apparatus (30) according to the present disclosure includes a communication unit (31) and a determination unit (32). The communication unit (31) receives, from an analysis apparatus (10) configured to perform machine learning using communication logs collected from a communication apparatus in order to generate a learning model, statistical information about each of the communication logs and information about the learning model. The determination unit (32) determines an analysis apparatus (20) to which the information about the learning model is applied based on the statistical information.

Abstract: A first prediction unit 83 predicts the amount of future communication quality deterioration or the presence or absence of occurrence of future communication quality deterioration in a communication section between one communication device and another communication device communicably connected to the one communication device by using a first learning model generated on the basis of first attributes being attributes related to a cause of communication quality deterioration in the communication section. A second prediction unit 84 predicts the amount of future communication quality deterioration or the presence or absence of occurrence of future communication quality deterioration outside the communication section regarding one communication device by using a second learning model generated on the basis of second attributes being attributes related to a cause of communication quality deterioration outside the communication section regarding the one communication device.

Abstract: A failure analysis device 10 is provided with an identification unit 11 that discriminates whether a predetermined failure has occurred on the basis of a learning model for discriminating the presence or absence of an occurrence of the predetermined failure learned by using a cause attribute which is associated with a cause of the predetermined failure and on the basis of a value of the attribute, and that identifies the cause of the predetermined failure discriminated to have occurred and countermeasures therefor.

Abstract: An object of the present disclosure is to provide an analysis apparatus capable of solving a problem that the amount of data processing increases and the processing load thus increases. An analysis apparatus (10) according to the present disclosure includes: a prediction unit (13) configured to perform machine learning using past traffic data in a communication system to thereby predict future traffic data in the communication system; an analysis unit (11) configured to analyze the future traffic data using first input data and generate a first analysis result corresponding to a first purpose; and an analysis unit (12) configured to analyze the future traffic data using second input data and generate a second analysis result corresponding to a second purpose.

Abstract: A feature calculation unit 81 calculates a feature that is likely to influence cancellation by a user based on a communication state log that indicates a communication state of a base station when the user has been engaged in communication or making a call. A learning device 82 learns a model representing a behavioral characteristic of the user by using the calculated feature as an explanatory variable. A prediction device 83 predicts the behavioral characteristic of the user using the feature generated from the communication state log and the model.

Abstract: Provided is a private branch exchange capable of independently adjusting call voice level and call quality according to a connection type of a communication line or a telephone.

Abstract: Provided is a private branch exchange capable of independently adjusting call voice level and call quality according to a connection type of a communication line or a telephone.