Search Results - (( intelligence based clustering algorithm ) OR ( intelligence data modeling algorithm ))
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Time series data intelligent clustering algorithm for landslide displacement prediction
Published 2018“…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach
Published 2024Subjects:Conference Paper -
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Clustering autism spectrum disorder student’s system based on intelligence, skills and behavior using agglomerative clustering algortihm / Daarin Nadia Nordin
Published 2020“…Data cleaning and data transformation is first carried out, followed by normalization through the Z-score method before being processed in the clustering model. …”
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Expectation maximization clustering algorithm for user modeling in web usage mining system
Published 2009“…The results also indicate that kind of behavior given by EM clustering algorithm has improved the visit-coherence (accuracy) of navigation pattern mining.…”
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An initial state of design and development of intelligent knowledge discovery system for stock exchange database
Published 2004“…Generally our clustering algorithm consists of two steps including training and running steps.The training step is conducted for generating the neural network knowledge based on clustering.In running step, neural network knowledge based is used for supporting the Module in order to generate learned complete data, transformed data and interesting clusters that will help to generate interesting rules.…”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase
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Adaptive Neural Subtractive Clustering Fuzzy Inference System for the Detection of High Impedance Fault on Distribution Power System
Published 2012“…This paper proposes an intelligent algorithm using an adaptive neural- Takagi Sugeno-Kang (TSK) fuzzy modeling approach based on subtractive clustering to detect high impedance fault. …”
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning
Published 2023“…Focusing on clustering algorithms, the study employs popular methods like K-Means Clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Agglomerative Hierarchical Clustering, and Mean Shift Clustering to understand customer characteristics and behaviors. …”
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Detecting High Impedance Fault in Power Distribution Feeder with Fuzzy Subtractive Clustering Model
Published 2013“…This paper proposes an intelligent algorithm using the Takagi Sugeno- Kang (TSK) fuzzy modeling approach based on subtractive clustering to detect the high impedance fault. …”
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A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning And Extended Mobility Features For VANETs
Published 2020“…An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively.…”
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Broken Conductor Detection on Power Distribution Feeder
Published 2013“…It proposes an intelligent algorithm using the Fuzzy Subtractive Clustering Model (FSCM) to detect the high impedance fault. …”
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High Impedance Fault Detection on Power Distribution Feeder
Published 2012“…This paper presents an intelligent algorithm using a Takagi Sugeno-Kang (TSK) fuzzy modeling approach based on subtractive clustering to detect high impedance fault. …”
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Advanced biomedical imaging for plaque lesion diagnosis focusing on Malaysian subjects / Hadzli Hashim
Published 2006“…The system which is based on primary color components from digital images employed new algorithms of data acquisition, data processing, data extraction and application of artificial neural network (ANN) as the decision model to discriminate plaque from other major psoriasis. …”
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Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…Computational intelligence is an ongoing area of research, which has been successfully utilized in the analysis and modeling of the tremendous amount of biological data accumulated under different high throughput genome sequencing projects. …”
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Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…Computational intelligence is an ongoing area of research, which has been successfully utilized in the analysis and modeling of the tremendous amount of biological data accumulated under different high throughput genome sequencing projects. …”
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An application of predicting student performance using kernel k-means and smooth support vector machine
Published 2012“…In this study, psychometric factors used as predictor variables, thereare Interest, Study Behavior, Engaged Time, Believe, and Family Support.The rulemodel developed using Kernel K-means Clustering and Smooth Support Vector MachineClassification.Both of these techniquesbased on kernel methodsand relativelynew algorithms of data mining techniques, recently received increasingly popularity in machine learning community. …”
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