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Full-Text Articles in Physical Sciences and Mathematics
Artificial Intelligence – Ii: Anomaly Detection In Data Streams Using Fuzzy Logic, Muhammad Umair Khan
Artificial Intelligence – Ii: Anomaly Detection In Data Streams Using Fuzzy Logic, Muhammad Umair Khan
International Conference on Information and Communication Technologies
Unsupervised data mining techniques require human intervention for understanding and analysis of the clustering results. This becomes an issue in dynamic users/applications and there is a need for real-time decision making and interpretation. In this paper we will present an approach to automate the annotation of results obtained from data stream clustering to facilitate interpreting that whether the given cluster is an anomaly or not. We use fuzzy logic to label the data. The results will be obtained on the basis of density function & the number of elements in a certain cluster.
Artificial Intelligence – I: A Two-Step Approach For Improving Efficiency Of Feedforward Multilayer Perceptrons Network, Shoukat Ullah, Zakia Hussain
Artificial Intelligence – I: A Two-Step Approach For Improving Efficiency Of Feedforward Multilayer Perceptrons Network, Shoukat Ullah, Zakia Hussain
International Conference on Information and Communication Technologies
An artificial neural network has got greater importance in the field of data mining. Although it may have complex structure, long training time, and uneasily understandable representation of results, neural network has high accuracy and is preferable in data mining. This research paper is aimed to improve efficiency and to provide accurate results on the basis of same behaviour data. To achieve these objectives, an algorithm is proposed that uses two data mining techniques, that is, attribute selection method and cluster analysis. The algorithm works by applying attribute selection method to eliminate irrelevant attributes, so that input dimensionality is reduced …