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96 articles for “Clustering process”
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Research ArticleOpen accessPhrase in the titleA Hybrid Clustering Process using a Genetic Fuzzy System for the Knowledge Base of a Fuzzy Rule-Based SystemHamedoun Lamiae, Attariuas Hicham, Ben Maati Mohamed LarbiThe present paper proposes a new Hybrid clustering Process based on Fuzzy Genetic System. The proposed Approach consists of two steps: (1) Using a method called Fuzzy clustering, all data elements will be clustered into N groups; (2) utilizing a Fuzzy Genetic System, for every level the fuzzy rule of adhesion will be generated. If we compare our research to … …Journal of Computer Science, Vol. 12, Issue 12 · 6 Feb 2017 · 6,644 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDesign of Tree Structure in Context Clustering Process of Hidden Markov Model-Based Thai Speech SynthesisSuphattharachai ChomphanProblem statement: In HMM-based Thai speech synthesis, the tone degradation due to the imbalance of training data of all tones. Some distortion of syllable duration is obviously noticeable when the system is trained with a small amount of data. These problems cause the decrement in naturalness and intelligibility of the synthesized speech. Approach: This study proposes an approach to improve … …American Journal of Applied Sciences, Vol. 9, Issue 3 · 14 Jan 2012 · 6,955 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe Parallel Maximal Cliques Algorithm for Protein Sequence ClusteringKhalid Jaber, Nur’Aini Abdul Rashid, Rosni AbdullahProblem statement: Protein sequence clustering is a method used to discover relations between proteins. This method groups the proteins based on their common features. It is a core process in protein sequence classification. Graph theory has been used in protein sequence clustering as a means of partitioning the data into groups, where each group constitutes a cluster. Mohseni-Zadeh introduced a … …American Journal of Applied Sciences, Vol. 6, Issue 7 · 31 Jul 2009 · 7,100 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Sentiment-Aware Hybrid Ensemble Clustering Framework for Social Network Content Analysis and Community DiscoveryDhimesh Pravinbhai Parmar, Paresh TannaSocial media stages produce huge volumes of short, familiar, and sentiment-rich content that offerings significant encounter for community discovery and thematic analysis. Traditional clustering approach struggle with sparsity, noise, and limited surroundings information present in such texts. To address these limitations, this study introduces a sentiment-aware hybrid ensemble clustering framework designed openly for social network content analysis. The planned method … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,271 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSummarizing Relational Data Using Semi-Supervised Genetic Algorithm-Based Clustering TechniquesRayner AlfredProblem statement: In solving a classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets stored in multiple tables into a single table. Unfortunately, we may loss some information when we join tables with a high degree of one-to-many association. Therefore, data transformation becomes a tedious trial-and-error work and … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,585 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Scalable and Reliable Cost Effective Key Agreement Protocol for Secure Group CommunicationS. Jabeen Begum, Dr. T. PurusothamanProblem statement: In a heterogeneous environment, for a secure multicast communication, the group members have to share a secret key which is used to encrypt/decrypt the secret messages among the members. The Secure Group Communication of large scale multicast group in a dynamic environment is more complex than securing one-to-one communication due to the inherent scalability issue of group key … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 6,960 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Weighting Technique Based Arctic Puffin Optimization for Energy Efficient Data Transmission in Wireless Sensor NetworksM. Bharathraj Kumar, S. Avinash, Prakash G. Gani, Prathapchandra ShettyWireless Sensor Networks (WSNs) are designed using various sensor nodes, which are employed for communication in diverse applications that include healthcare, industrial areas, and smart cities. Specifically, WSNs demand energy-efficient clustering and routing mechanisms that assist in extending network lifetime due to the limited battery capacity of sensor nodes. However, many existing meta-heuristic-based approaches incorporate fixed objective weights that struggle … …Journal of Computer Science, Vol. 22, Issue 9 · 10 Sep 2026 · 767 accessesView PDFCite
Research ArticleOpen accessIn the abstractPolar Disentangled Non-Local Convolutional Neural Network for Skin Cancer Classification Using Dermoscopy ImagesUsha Thirugnanam, Nalini JosephSkin cancer classification is the process of identifying and categorizing various types of skin lesions into cancerous and non-cancerous. This process is performed to achieve accurate detection, which minimizes the risk of severe health complications. However, classifying the severity of skin lesion images is a difficult task because of subtle and overlapping visual patterns, which could lead to inaccurate performance. … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,207 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Wireless Sensor Network Clustering Using a Hybrid Firefly–Bat Algorithm (HFBA)J. Jegan, Senthil kumar P, S. Saravanakumar et al.Wireless Sensor Networks (WSNs) are composed of numerous sensor nodes that collaborate to observe and evaluate various environmental parameters, transmitting the data to a central base station. Each node is equipped with a unique transmitter, receiver, and processor to facilitate sensing, processing, and communication. These networks are often installed in extremely remote and inaccessible areas. A significant challenge arises from … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,431 accessesView PDFCite
Review ArticleOpen accessIn the abstractImproving Classification and Clustering Accuracy of Palembang Duku Fruit Quality via CNN-K-Means IntegrationHenny Hartono, Francka Sakti Lee, Herlina Herlina et al.Duku Palembang (Lansium domesticum Corr.) is a leading commodity from South Sumatra with high economic value. The quality assessment process for duku has traditionally relied on manual visual inspection, which is subjective, time-consuming, and inconsistent, especially at large production scales. This study proposes an integrative framework combining Convolutional Neural Network (CNN) and K-Means Clustering to improve the accuracy of classification … …OnLine Journal of Biological Sciences, Vol. 26, Issue 2 · 8 May 2026 · 1,475 accessesView PDFCite