Disclosed are embodiments for automatically resolving faults in a complex network system. Some embodiments monitor one or more of system operational parameter values and message exchanges between network components. A machine learning model detects a fault in the complex network system, and an action is selected based on a cause of the fault. After the action is applied to the complex network system, additional monitoring is performed to either determine the fault has been resolved or additional actions are to be applied to further resolve the fault.

Disclosed are embodiments for automatically resolving faults in a complex network system. Some embodiments monitor one or more of system operational parameter values and message exchanges between network components. A machine learning model detects a fault in the complex network system, and an action is selected based on a cause of the fault. After the action is applied to the complex network system, additional monitoring is performed to either determine the fault has been resolved or additional actions are to be applied to further resolve the fault.

A multi-point measurement system and a multi-point measurement method are provided. The multi-point measurement system is for measuring a device under testing and comprises a plurality of sensors and a computing device. The sensors are respectively attached to a plurality of measuring points of the device under testing. The computing device comprises a computing unit and a storage unit; the computing unit comprises a learning module, and the computing device establishes communication connections to the sensors respectively. The sensors generate original sensing data and transmit them to the storage unit for storage. The computing unit inputs processed sensing data obtained by preprocessing the original sensing data into the learning module for data analysis, and obtains a plurality of reference values corresponding to the sensors respectively. At least two adjacent sensors form a group; the computing unit sequentially inputs the processed sensing data corresponding to the sensors in the group into the learning module for a merge operation, and obtains a plurality of merged reference values corresponding to the groups respectively. The computing unit performs a determination operation using the merged reference values corresponding to each group and the reference values corresponding to the sensors in the group and generates a suitability determination for the measuring points.

Disclosed are embodiments for automatically resolving faults in a complex network system. Some embodiments monitor one or more of system operational parameter values and message exchanges between network components. A machine learning model detects a fault in the complex network system, and an action is selected based on a cause of the fault. After the action is applied to the complex network system, additional monitoring is performed to either determine the fault has been resolved or additional actions are to be applied to further resolve the fault.

A multi-point measurement system and a multi-point measurement method are provided. The multi-point measurement system is for measuring a device under testing and comprises a plurality of sensors and a computing device. The sensors are respectively attached to a plurality of measuring points of the device under testing. The computing device comprises a computing unit and a storage unit; the computing unit comprises a learning module, and the computing device establishes communication connections to the sensors respectively. The sensors generate original sensing data and transmit them to the storage unit for storage. The computing unit inputs processed sensing data obtained by preprocessing the original sensing data into the learning module for data analysis, and obtains a plurality of reference values corresponding to the sensors respectively. At least two adjacent sensors form a group; the computing unit sequentially inputs the processed sensing data corresponding to the sensors in the group into the learning module for a merge operation, and obtains a plurality of merged reference values corresponding to the groups respectively. The computing unit performs a determination operation using the merged reference values corresponding to each group and the reference values corresponding to the sensors in the group and generates a suitability determination for the measuring points.

Disclosed are embodiments for automatically resolving faults in a complex network system. Some embodiments monitor one or more of system operational parameter values and message exchanges between network components. A machine learning model detects a fault in the complex network system, and an action is selected based on a cause of the fault. After the action is applied to the complex network system, additional monitoring is performed to either determine the fault has been resolved or additional actions are to be applied to further resolve the fault.

Disclosed are embodiments for automatically resolving faults in a complex network system. Some embodiments monitor one or more of system operational parameter values and message exchanges between network components. A machine learning model detects a fault in the complex network system, and an action is selected based on a cause of the fault. After the action is applied to the complex network system, additional monitoring is performed to either determine the fault has been resolved or additional actions are to be applied to further resolve the fault.

The first aid presentation system comprises: a storage unit that stores one or more pieces of notification information associated with one another from among notification information received from one or more monitoring targets, and one or more pieces of registration information registered by a user and information representing a first aid for the monitoring target that correspond to the notification information; a presentation unit that acquires, from the storage unit, one or more pieces of registration information and a first aid that correspond to notification information associated with specified notification information and that presents the one or more pieces of registration information and the first aid; and a registration unit that newly registers registration information in association with the specified notification information.