Search Results - (( _ evaluation tool algorithm ) OR ( based identification clustering algorithm ))*
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Development of an effective clustering algorithm for older fallers
Published 2022“…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. …”
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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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KP-Rank: a semantic-based unsupervised approach for keyphrase extraction from text data
Published 2021“…In the proposed approach, we exploited Latent Semantic Analysis (LSA) and clustering techniques and a novel frequency-based algorithm for candidate ranking is introduced which considers locality-based sentence, paragraph and section frequencies. …”
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The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes
Published 2019“…Pattern recognition approach based on Auto-Regressive (AR) algorithm is an alternative way to provide a more accurate defect identification from stress wave propagated along ASTM A179 heat exchanger tubes. …”
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Efficient tag grouping RFID anti-collision algorithm for internet of things applications based on improved k-means clustering
Published 2023“…Variants of the proposed kg-DFSA, traditional DFSA and another grouping based DFSA algorithm (FCM-DFSA) were implemented in MATLAB. …”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…In this paper, a novel gas identification approach based on Cluster-k-Nearest Neighbor. …”
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Evaluation of FCV and FCM clustering algorithms in cluster-based compound selection
Published 2011“…One of most used clustering method is cluster-based compound selection, which involves subdividing a set of compounds into clusters and choosing one compound or a small number of compounds from each cluster. …”
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Document clustering for knowledge discovery using nature-inspired algorithm
Published 2014“…As the internet is overload with information, various knowledge based systems are now equipped with data analytics features that facilitate knowledge discovery.This includes the utilization of optimization algorithms that mimics the behavior of insects or animals.This paper presents an experiment on document clustering utilizing the Gravitation Firefly algorithm (GFA).The advantage of GFA is that clustering can be performed without a pre-defined value of k clusters.GFA determines the center of clusters by identifying documents with high force.Upon identification of the centers, clusters are created based on cosine similarity measurement.Experimental results demonstrated that GFA utilizing a random positioning of documents outperforms existing clustering algorithm such as Particles Swarm Optimization (PSO) and K-means.…”
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Application of fuzzy clustering analysis to compound datasets for drug lead identification
Published 2012“…However, there are little study on overlapping method such as fuzzy cmean (FCM) and fuzzy c-varieties (FCV) clustering algorithms. Therefore, these two clustering algorithms are applied and their performance is compared based on the effectiveness of the clustering results in terms of separation between actives and inactives (Pa) into different clusters and mean intercluster molecular dissimilarity (MIMDS). …”
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Bottleneck-based heuristic for permutation flowshop scheduling
Published 2017“…The heuristic performance was evaluated based on the average makespan ratio, average percentage error, and percentage of solution performance obtained. …”
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Unsupervised segmentation technique for acute leukemia cells using clustering algorithms
Published 2015“…Based on the good sensitivity value that has been obtained, the results indicate that moving k-means clustering algorithm has successfully produced the fully segmented blast region in acute leukaemia image. …”
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Big Data Mining Using K-Means and DBSCAN Clustering Techniques
Published 2022“…Density-based clustering with three clusters outperformed the K-Means algorithm with three clusters in terms of accuracy. …”
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Automatic clustering of generalized regression neural network by similarity index based fuzzy c-means clustering
Published 2004“…This technique uses the conventional fuzzy c-means clustering preceded by a technique based on similarity indexing to automatically cluster input data which are relevant to the system. …”
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An efficient fuzzy clustering algorithm for mining user session clusters on web log data
Published 2021“…This paper proposes an efficient Fuzzy Clustering algorithm for mining client session clusters from web access log information to find the groups of client profiles. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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Dense-cluster based voting approach for license plate identification
Published 2018“…This paper presents a new method called Dense Cluster based Voting (DCV) for identifying an input license plate image as normal or taxi such that suitable recognition algorithms can be used to achieve better recognition rate. …”
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RFID-enabled supply chain detection using clustering algorithms
Published 2015“…We will apply various clustering algorithms to analyzed and determine every attribute in the dataset structure pattern. …”
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