| 摘要 |
Systems and methods for adaptive database management and monitoring are disclosed. According to various embodiments, the present invention comprises training a neural network of a classification engine with real time performance data of a database. Once the neural network has been trained, real time performance data for the database may be input to the classification engine. If the classification engine detects a deviation in performance, it may cause an alert to be sent to a database administrator. In addition, the classification engine may send results of its analysis to a host, which posts the results on a web page. Users may provide feedback on the results to a batch relearn entries database or file. The classification may read the batch relearn entries to use in a backpropogation algorithm to update/retrain the neural network of the classification engine.
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