Search Results - (( data distribution clustering algorithm ) OR ( data distribution function algorithm ))
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. We develop the clustering-based procedure for the predicted and residual values obtained from the Down and Mardia model fit of a circular-circular data set. …”
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2
A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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3
Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…The algorithm also improves the calculations of shape and width of membership functions by means of clustering in order to improve the accuracy. …”
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Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
Published 2024“…The functions of private cloud computing clusters for power extensive data management and analysis are realised through MapReduce computing framework and Hbase database. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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6
Density based subspace clustering: a case study on perception of the required skill
Published 2014“…Each dimension will be tested to investigate whether having a relationship with the data on another cluster, using proposed subspace clustering algorithms. …”
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7
Density subspace clustering: a case study on perception of the required skill
Published 2014“…Each dimension will be tested to investigate whether having a relationship with the data on another cluster, using proposed subspace clustering algorithms. …”
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8
ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs
Published 2021“…The proposed multi-trust approach is used to analyze the credibility of sensitive monitored data. A novel and efficient cluster head selection algorithm (ECHSA) is employed to improve the performance of the cluster head (CH) selection process in clustered WSN. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…The silhouette value average score is 0.8504 (highest score is 0.9207) of how well-distributed the resulting clusters. The clustering system has identified the tool to stop cutting at approximate VB = 0.213 mm before the tool condition enters the failure region of abnormal phase (VB < 0.250 mm).s The proposed system functioned effectively in clustering the data obtained from cutting tests performed within a reasonable range of wear stages. …”
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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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11
Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine
Published 2019“…The RX_myKarve is an extended framework from X_myKarve, which consists of the following key components: (i) an Extreme Learning Machine (ELM) neural network for clusters classification using three existing content-based features extraction (Entropy, Byte Frequency Distribution (BFD) and Rate of Change (RoC)) to improve the identification of JPEG images content and support the reassembling process; (ii) a genetic algorithm with Coherence Euclidean Distance (CED) matric and cost function to reconstruct a JPEG image from a set of deformed and fragmented clusters in the scan area. …”
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12
Predicting the popularity of tweets using the theory of point processes.
Published 2019“…The mode of the posterior distribution is used as the estimator of the finite-dimensional parameter, and suitable functionals of the predictive distribution for the number of retweets implied by the estimated model are used to predict the tweet popularity. …”
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Enhancing high-dimensional streaming data analysis: optimizing Online Feature Selection for handling drift using optimization technique and ensemble learning
Published 2024“…In the era of data-driven decision-making, managing dynamic data streams characterized by evolving data distributions and high dimensionality presents a formidable challenge for online feature selection. …”
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14
Fault Detection Relevant Modeling of an Industrial Gas Turbine based on Neuro-Fuzzy Approach
Published 2010“…Structure and network weights for the NF model are determined by a synergetic approach – Data clustering and Gradient Descent algorithm. Operation data collected in 10 seconds interval and for one day is used for model training and validation. …”
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Multi-objective scheduling of MapReduce jobs in big data processing
Published 2018“…The MapReduce computational paradigm is a well-known framework and is considered the main enabler for the distributed and scalable processing of a large amount of data. …”
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Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…The reservoir inflow and rainfall data sets were examined for normal distribution and the best data transformation was used. …”
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17
Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution
Published 2014“…Therefore, in this study, a new algorithm called Scheduled-Activity Energy Aware Distributed Clustering (SA-EADC) is proposed. …”
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18
Fuzzy Soft Set Clustering for Categorical Data
Published 2024“…This research provides categorical data with fuzzy clustering technique due to soft set theory and multinomial distribution. …”
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Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods
Published 2025“…Five tables of summary for choosing appropriate clustering algorithms according to data distribution were produced. …”
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20
A scheduled activity energy aware distributed clustering algorithm for wireless sensor networks with nonuniform node distribution
Published 2014“…Energy aware distributed clustering (EADC) is one of the cluster-based routing protocols proposed for networks with nonuniform node distribution, which can effectively balance the energy consumption among the nodes. …”
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