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- Clustering algorithms (2)
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- Artificial neural networks (1)
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- Caching (1)
- Calibration (1)
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Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Networks - Ii: A Survey Of Data Management Issues & Frameworks For Mobile Ad Hoc Networks, Noman Islam, Zubair A. Shaikh
Networks - Ii: A Survey Of Data Management Issues & Frameworks For Mobile Ad Hoc Networks, Noman Islam, Zubair A. Shaikh
International Conference on Information and Communication Technologies
Data Management is the execution of a pool of activities on a set of data to conform to the end user data requisitions. MANET is an emerging discipline of computer networks in which a group of roaming hosts spontaneously establishes the network among themselves. The employment of data management in MANET can engender a number of useful applications. However, data management in MANET is a taxing job as it requires deliberation on a number of research issues (e.g. knowledge representation, knowledge discovery, caching, and security etc.). This paper provides a detailed account of the data management problem and its issues, …
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.
Data Mining: Assessment Of Features Quality Of Class Discrimination Using Arif Index And Its Application To Physiological Datasets, Dr. Muhammad Arif, A. Fida
Data Mining: Assessment Of Features Quality Of Class Discrimination Using Arif Index And Its Application To Physiological Datasets, Dr. Muhammad Arif, A. Fida
International Conference on Information and Communication Technologies
Quality of features determines the maximum achievable accuracy by any arbitrary classifier in pattern classification problem. In this paper, we have proposed an index that can assess the quality of features in discrimination of patterns in different classes. This index is in-sensitive to the complexity of boundary separating different classes if there is no overlap among features of different classes. Proposed index is model free and requires no clustering algorithm to discover the clustering structure present in the feature space. It is only based on the information of local neighborhood of feature vectors in the feature space. This index can …
Data Mining: Analyzing Impact Of Outliers' Detection And Removal From The Test Sample In Blind Source Extraction Using Multivariate Calibration Techniques, S. R. Naqvi, F. Rehman, S. S. Naqvi, A. Amin, I. Qayyum, S. Khan, W. A. Khan
Data Mining: Analyzing Impact Of Outliers' Detection And Removal From The Test Sample In Blind Source Extraction Using Multivariate Calibration Techniques, S. R. Naqvi, F. Rehman, S. S. Naqvi, A. Amin, I. Qayyum, S. Khan, W. A. Khan
International Conference on Information and Communication Technologies
Blind source extraction (BSE) may be an essential but a challenging task where multiple sources are convolved and/or time delayed. In this article we discuss the performance of multivariate calibration techniques that comprise of classical least square (CLS), inverse linear regression (ILS), principal component regression (PCR) and partial least square regression (PLS) in achieving this task in robust speech recognition systems with varying signal-to-noise ratios (SNR). We specifically analyze two methods for identifying and removing outliers from the sample, namely; outlier sample removal (OSR) and descriptor selection (DS) for classical least square and factor Based regression respectively, which results in …
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 …