Search Results - (( process identification clustering algorithm ) OR ( java application customization algorithm ))
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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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Development of an effective clustering algorithm for older fallers
Published 2022“…Data from the Malaysian Elders Longitudinal Research (MELoR), comprising 1411 subjects aged ≥55 years, were utilized. The proposed algorithm was developed through the stages of: data pre-processing, feature identification and extraction with either t-Distributed Stochastic Neighbour Embedding (t-SNE) or principal component analysis (PCA)), clustering (K-means clustering, Hierarchical clustering, and Fuzzy C-means clustering) and characteristics interpretation with statistical analysis. …”
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Big Data Mining Using K-Means and DBSCAN Clustering Techniques
Published 2022“…The density-based spatial clustering of applications with noise (DBSCAN) and the K-means algorithm were used to develop clustering algorithms. …”
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Automatic clustering of generalized regression neural network by similarity index based fuzzy c-means clustering
Published 2004“…This index indicates the degree of similarity in which data is clustered. Similar data then undergoes fuzzy c-means iterative process to determine their cluster centers. …”
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Dense-cluster based voting approach for license plate identification
Published 2018“…This process gives four clusters for the input image. The number of pixels in clusters (dense cluster) and the standard deviation are computed for deriving new hypotheses. …”
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An assessment of sedimentation in Terengganu River, Malaysia using satellite imagery
Published 2023Article -
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A modified π rough k-means algorithm for web page recommendation system
Published 2018“…The experimental results revealed that the modified πRKM algorithm performed better than the previous version in terms of the correct identification of overlapping objects between positive clusters. …”
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Frequent patterns minning of stock data using hybrid clustering association algorithm
Published 2009“…Patterns and classification of stock or inventory data is very important for business support and decision making. Timely identification of newly emerging trends is also needed in business process. …”
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A hybrid of fuzzy c-means clustering and Latent Dirichlet Allocation for analysing philanthropic corporate social responsibility activities / Nik Siti Madihah Nik Mangsor
Published 2023“…The analysis involved five-year data from the annual reports of 19 CSR-award winning companies in Malaysia where they were converted into a structured format, collated and summarized. Then, text pre-processing for data cleaning was performed followed by identification of the best Latent Dirichlet Allocation (LDA) topic modelling technique that was used to integrate document clustering.…”
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Product Identification Using Image Processing And Radial Basis Function Neural Networks
Published 2015“…This paper presents a product identification using image processing and radial basis function neural networks. …”
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Development of Acute Stroke Lesion Segmentation Algorithm in Brain MRI using Pseudo-colour with K-means Clustering
Published 2021“…This study aims to develop an automatic segmentation by utilizing clustering algorithm for acute ischemic stroke lesion identification. …”
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An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation
Published 2016“…The clustering process in Fast Scanning algorithm is performed by merging pixels with similar neighbor based on an identified threshold and the use of Euclidean Distance as distance measure. …”
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RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION
Published 2010“…The learning method will determine the performance’s capability of the networks for the system identification process which will be one of the key issues to be discussed in the thesis. …”
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A Framework for Green Energy Resources Identification and Integration Supported by Real-Time Monitoring, Control, and Automation Applications
Published 2025“…The process involved clustering by divisions and designing optimal electrical power line routing for each cluster, prioritizing minimum total distance, elevation difference, and average ground flash density. …”
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Detection And Identification Of Stiction In Control Valves Based On Fuzzy Clustering Method
Published 2016“…This modification prevents the fuzzy clustering algorithm from turning into numerical problem. …”
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Learning analytic framework for students’ academic performance and critical learning pathways
Published 2024“…The resulting reduced dataset is then subjected to various clustering algorithms, including partition-based clustering (K-means), hierarchical clustering, and density-based clustering (DBSCAN). …”
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Depth Image Layers Separation (DILS) algorithm of image view synthesis based on stereo vision
Published 2013“…The simulation results show that depth layer separation is able to create inter-view images that may be integrated with other techniques such as occlusion handling processes. The DILS algorithm can be implemented using both simple as well as sophisticated stereo matching methods to synthesize inter-view images.…”
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