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83 results for “Computational Efficiency”
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Research ArticleOpen accessIn the abstractRandom Forest-Based Genome Analysis for Disease Association and SNP Marker IdentificationXiangdong LiuAt present, genomic data analysis has the problems of insufficient model interpretation and limited computational efficiency in disease association research. As a powerful machine learning algorithm, Random Forest has demonstrated excellent ability in processing complex and multi-dimensional data sets and has gradually become a popular tool in the field of bioinformatics. The purpose of this paper is to explore how … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 2 · 25 Jul 2025 · 5,533 accessesView PDFCite
Research ArticleOpen accessIn the abstractSeismic Fragility Assessment of RC Frame Equipped by Visco-Elastic Dampers Using NLTHA and FNAAli A. Rostam Alilou, Majid PouraminianIn recent years, the issue of lower computational cost and analysis time has been the important factors for the structural analysts. In the meantime, after years of its introduction as an analysis having features of nonlinear analysis, the Fast Nonlinear Analysis (FNA) claims to have a higher performance speed than other nonlinear analyses, but has been less used by the … …American Journal of Engineering and Applied Sciences, Vol. 12, Issue 3 · 18 Jul 2019 · 8,413 accessesView PDFCite
Research ArticleOpen accessIn the abstractQuay Crane Scheduling in Container Terminals Using a Hybrid Genetic AlgorithmAidi Sanaa, Torbi Imane, Mazouzi MohamedContainer terminals are crucial nodes within the global supply chain, playing a vital role in the efficient movement of goods. Effective scheduling of Quay Cranes (QCs) is a key factor in maximizing port productivity and minimizing delays. This research investigates the Quay Crane Scheduling Problem (QCSP) using a Hybrid Genetic Algorithm (HGA). The proposed HGA method combines the exploratory power … …Journal of Computer Science, Vol. 21, Issue 1 · 26 Dec 2024 · 6,007 accessesView PDFCite
Review ArticleOpen accessIn the abstractHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptivity in Role-Based Access Control During Stochastic Situations: A Comprehensive Study between Graph and Relational DatabasesKriti Srivastava, Dhruv Jain, Aarya Kamdar et al.Role-based control is straightforward to implement in static systems where there are specific policies for role and resource mapping. The main challenge is faced in dynamic and unpredictable systems with erratic workflows. Conventional methods prove to be inadequate in dynamic environments. Over the Years methods suggested include probabilistic, machine learning, ontology, and decision tree models to improve the adaptability. However, … …Journal of Computer Science, Vol. 20, Issue 12 · 18 Nov 2024 · 5,372 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Integration for Precise Facial Micro-Expression RecognitionViola Bakiasi Shtino, Markela Muça, Senada BushatiThis study advances facial micro-expression recognition through innovative machine-learning techniques, addressing critical needs in psychology, security, and human-computer interaction. The purpose of this study is to improve micro-expression recognition through the optimization of feature transformation and machine learning algorithms. We introduce a novel approach combining Kernel Principal Component Analysis (KPCA) and Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction, … …Journal of Computer Science, Vol. 20, Issue 11 · 22 Oct 2024 · 5,592 accessesView PDFCite
Research ArticleOpen accessIn the abstractCrime Rate Analysis and Mapping from Socio-Economic Data Using Deep Neural NetworksSanthosh Sankara, Nadeson SugithaCrime prediction is the attempt to identify and mitigate future criminal activity. Crime is typically "unpredictable"; it cannot be predicted in advance. Addressing the roots of crime has long been a priority for researchers. Extracting causality from data is difficult if the relevant data aspects are not selected. In this research activity, an innovative classification framework is defined which is … …Journal of Computer Science, Vol. 20, Issue 10 · 17 Aug 2024 · 5,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractSales Forecasting Models: Comparison between ARIMA, LSTM and ProphetDmitry BrykinSales forecasting is crucial for business planning and resource allocation. Data-driven approaches have become popular in this field. This study compares the performance of three forecasting models: Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM) and Prophet within the context of specific sales categories derived from acquiring data provided by a bank. This study uses a time series dataset … …Journal of Computer Science, Vol. 20, Issue 10 · 1 Aug 2024 · 7,981 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Background Knowledge and Random Sampling in Genetic Programming: A Case Study in Learning Boolean Parity FunctionsLappoon R. TangThe Boolean even-N-parity function returns T (i.e., true) if an even number of its Boolean arguments for N arguments are T and otherwise returns NIL (i.e., false). Learning Boolean even-N-parity functions has been recognized as a difficult problem for evolutionary computation (such as genetic programming) especially when N is large (e.g., 20+). A number of approaches have been proposed for … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 5,481 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Computational Method Based on Bernstein Polynomials for Solving FredholmIntegro-Differential Equations under Mixed ConditionsMiloud Moussai, Lakhdar ChiterIn this study, a computational method for solving linear FredholmIntegro-Differential Equation (FIDE) of the first order under the mixed conditions using the Bernstein polynomials. First, we present some properties of these polynomials and the method is explained. These properties are then used to convert the integro-differential equation to a system of linear algebraic equations with unknown Bernstein coefficients. Using Galerkin … …Journal of Mathematics and Statistics, Vol. 13, Issue 1 · 27 Feb 2017 · 7,142 accessesView PDFCite