文件名称:FuzzyTemporal
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Fault management is used to detect, isolate, and repair
problems in communication networks. Alarms are
considered an external manifestation of faults occurring
inside the managed network. These faults may affect the
network’s hardware and software components. Alarm
correlation identifies the relationships between reported
alarms to produce a new, smaller list of alarms. This
allows operators to quickly and more accurately to
identify the root cause of problems and resolve them
faster. Temporal reasoning, reasoning about time, plays a
critical role in monitoring network alarms. In this paper,
a fuzzy-logic model is proposed for finding the temporal
relation between events for correlation purposes. A fuzzyinference
rule base is used to integrate fuzzy membership
functions to determine the “best” temporal relation
between events. The proposed model is compared to the
traditional crisp temporal reasoning.
problems in communication networks. Alarms are
considered an external manifestation of faults occurring
inside the managed network. These faults may affect the
network’s hardware and software components. Alarm
correlation identifies the relationships between reported
alarms to produce a new, smaller list of alarms. This
allows operators to quickly and more accurately to
identify the root cause of problems and resolve them
faster. Temporal reasoning, reasoning about time, plays a
critical role in monitoring network alarms. In this paper,
a fuzzy-logic model is proposed for finding the temporal
relation between events for correlation purposes. A fuzzyinference
rule base is used to integrate fuzzy membership
functions to determine the “best” temporal relation
between events. The proposed model is compared to the
traditional crisp temporal reasoning.
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