Pattern Recognition for MCNs Using Fuzzy Linear Programming
This paper presents a data mining system of performance evaluation for multimedia communication networks (MCNs). Two important performance evaluation problems for the MCNs are considered in this paper. They are: (1) the optimization problem for construction of the data mining system of performance evaluation; (2) the problem of categorizing real-time data corresponding to the data mining system by means of dividing the performance data into usual and unusual categories. An algorithm is employed to identify performance data such as throughput capacity, package forwarding rate, and response time. A software named PEDM2.0 (Performance Evaluation Data Miner) is proposed to improve the accuracy and the effectiveness of the fuzzy linear programming (FLP) method compared with decision tree, neural network, and multiple criteria linear programming methods.
KeywordsData Warehouse Unusual Pattern Throughput Capacity Fuzzy Linear Programming Data Mining System
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