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49 results for “Hybrid Datasets”
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Research ArticleOpen accessIn the abstractAn Independent Rough Set Approach Hybrid with Artificial Bee Colony Algorithm for Dimensionality ReductionNambiraj Suguna, Keppana Gowder ThanushkodiProblem statement: Dimensionality reduction is viewed as an important pre-processing step for pattern recognition and data mining. As the classical rough set model considers the entire attribute set as a whole to find the subset, comparing all possible combinations of sets of attributes is difficult. Approach: In this study, we have introduced an improved Rough Set-based Attribute Reduction (RSAR) namely … …American Journal of Applied Sciences, Vol. 8, Issue 3 · 25 Mar 2011 · 8,334 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybridization of Neural Learning Algorithms Using Evolutionary and Discrete Gradient ApproachesRanadhir Ghosh, John Yearwood, Moumita Ghosh, Adil BagirovIn this study we investigated a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient … …Journal of Computer Science, Vol. 1, Issue 3 · 30 Sep 2005 · 6,587 accessesView PDFCite
Research ArticleOpen accessIn the abstractParallel Memetic Algorithm for VLSI Circuit Partitioning Problem using Graphical Processing UnitsP. Subbaraj, P. SivakumarProblem statement: Memetic Algorithm (MA) is a form of population-based hybrid Genetic Algorithm (GA) coupled with an individual learning procedure capable of performing local refinements. Here we used genetic algorithm to explore the search space and simulated annealing as a local search method to exploit the information in the search region for the optimization of VLSI netlist bi-Partitioning problem. However, … …Journal of Computer Science, Vol. 8, Issue 5 · 27 Feb 2012 · 7,090 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Cooperative Algorithm Based on PSO and K-Means for Data ClusteringMehdi Neshat, Shima Farshchian Yazdi, Daneyal Yazdani, Mehdi SargolzaeiProblem statement: Data clustering has been applied in multiple fields such as machine learning, data mining, wireless sensor networks and pattern recognition. One of the most famous clustering approaches is K-means which effectively has been used in many clustering problems, but this algorithm has some drawbacks such as local optimal convergence and sensitivity to initial points. Approach: Particle Swarm Optimization … …Journal of Computer Science, Vol. 8, Issue 2 · 19 Nov 2011 · 7,967 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 749 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,427 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordHybrid Deep Learning Models for Text Classification: Performance Evaluation of TriDistilBERT and BiGRU ArchitecturesAmira Samy TalaatText can be a valuable source of information, but its unstructured nature makes analysis challenging and time-consuming. Machine Learning (ML) algorithms can efficiently analyze and structure text, enabling organizations to automate processes and uncover insights that support better decision-making. This study focuses on applying ML to a classification problem using two datasets. Four deep learning models are introduced, combining Bi … …Journal of Computer Science, Vol. 21, Issue 9 · 10 Oct 2025 · 2,792 accessesView PDFCite
Review ArticleOpen accessAll words, across the recordUnleashing the Power of Image Denoising: A Comprehensive Review of Classical to Deep Learning MethodsArchana Saini, Ayush DograImage denoising is a vital step in many image processing and computer vision professions that aims to improve picture quality by decreasing noise while maintaining important image information. In this article, a detailed overview is presented of traditional and deep learning based picture denoising approaches. Classical methods, such as linear filtering, transform domain techniques, and patch-based approaches like Non-Local Means … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 3,107 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordFast Algorithms for Discovering Sequential Patterns in Massive DatasetsS. Dharani, Justus Rabi, Nanda Kumar, DarlyProblem statement: Sequential pattern mining is one of the specific data mining tasks, particularly from retail data. The task is to discover all sequential patterns with a user-specified minimum support, where support of a pattern is the number of data-sequences that contain the pattern. Approach: To find a sequence patterns variety of algorithm like AprioriAll and Generalized Sequential Patterns (GSP) … …Journal of Computer Science, Vol. 7, Issue 9 · 23 Jul 2011 · 7,280 accessesView PDFCite