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36 articles for “Non-Linear Methods”
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Research ArticleOpen accessIn the keywordsA Non-Linear Absolutely-Stable Explicit Numerical Integration Algorithm for Stiff Initial-Value ProblemsEssam R. El-ZaharThe time-step in integration process has two restrictions. The first one is the time step restriction due to accuracy requirement τac and the second one is the time-step restriction due to stability requirement τst. The most of explicit methods have small stability regions and consequently small τst. It obliges us to solve stiff problems with small step size τst << … …American Journal of Applied Sciences, Vol. 10, Issue 11 · 11 Sep 2013 · 7,559 accessesView PDFCite
Research ArticleOpen accessIn the abstractDengue Fever Prediction Empowered by Radial Basis Function Networks, Dynamic Mode Decomposition, and Learning-Based Foraging AlgorithmArchana T, Faritha Banu JDengue fever is presently considered a major health threat that must be addressed. External and internal factors that induce nonlinear oscillations in the occurrence of dengue disease have made optimal resource allocation stimulating. Public health initiatives aimed at eradicating this vector use accurate and timely data through field processes. In dengue-endemic nations, early dengue prediction remains a main concern for … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 1,496 accessesView PDFCite
Review ArticleOpen accessIn the abstractUnleashing 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 accessIn the abstractIntelligent Intrusion Detection System Using RF, SVM, and DT: A Comparison-Based KDD Data SetWalaa Hassan Elashmawi, Alaa Sheta, Ahmad Al-QeremThe rapid growth of technology has brought about many advantages, but has also made networks more susceptible to security threats. Intrusion Detection Systems (IDS) play a vital role in protecting computer networks against malicious activities. Given the dynamic and constantly evolving nature of cyber threats, these systems must continuously adapt to maintain their effectiveness. Machine Learning (ML) methods have gained … …Journal of Computer Science, Vol. 21, Issue 8 · 28 Aug 2025 · 5,818 accessesView PDFCite
Research ArticleOpen accessIn the abstractBeatbox Classification to Distinguish User Experiences Using Machine Learning ApproachesJason Martanto, Iman Herwidiana KartowisastroResearch regarding beatbox classification has generated a relatively significant growth in the past decade. Although the differences between contributors’ expertise within a vocal percussion dataset have been mentioned in previous works, the impact of those discrepancies has not been thoroughly investigated. In this study, the authors explore performances of machine learning algorithms for beatbox classification, with an emphasis on prior … …Journal of Computer Science, Vol. 21, Issue 4 · 18 Mar 2025 · 5,208 accessesView PDFCite
Research ArticleOpen accessIn the abstractState-Space Modelling of a Rocket for Optimal Control System DesignAliyu Bhar Kisabo, Aliyu Funmilayo Adebimpe, Odooh Clement Okwo, Sholiyi Olusegun SamuelIn this study, we present the derivation of the mathematical model for a rocket’s autopilot in state-space. The basic equations defining the airframe dynamics of a typical six-Degree-of-Freedom (6DoF) are non-linear and coupled. Separation of these nonlinear coupled dynamics is presented as lateral and longitudinal dynamic equations. The need to determine aerodynamic coefficients and there derivative components are brought to … …Journal of Aircraft and Spacecraft Technology, Vol. 3, Issue 1 · 25 May 2019 · 13,632 accessesView PDFCite
Research ArticleOpen accessIn the abstractMetabolic Potential Versus Genome SizeAtanas Todorov Atanasov, Dimitar Todorov ValevAlberch, P. (1983). Development and Evolution: Embryos, Genes, and Evolution. The Developmental-Genetic Basis of Evolutionary Change. Science, 221(4607), 257–258. https://doi.org/10.1126/science.221.4607.257 Andrews, C. B., Mackenzie, S. A., & Gregory, T. R. (2009). Genome size and wing parameters in passerine birds. Proceedings of the Royal Society B, 276(1654), 55–61. https://doi.org/10.1098/rspb.2008.1012 Atanasov, A. T. (2005). The linear alometric relationship between total metabolic energy … …Physics International, Vol. 13, Issue 1 · 15 Jun 2022 · 7,229 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Surface Drag Interval in the Variable SituationsParisa Ashrafi, Amir Hossein Ashrafi, Hossein Gholami et al.Tools applied in different fields of engineering are artificial neural networks to model non-linear systems which are efficient and useful. Artificial neural networks consist of input and output layers with one or more hidden layers between them. In fact, one or more processing elements or neurons are used in each layer. Input layer neurons are the independent variables studied and … …American Journal of Engineering and Applied Sciences, Vol. 15, Issue 1 · 12 Mar 2022 · 6,001 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Review of the Recent Advances Made in the Black-Scholes Models and Respective Solutions MethodsYasir Hamad Al Saedi, Gurudeo Anand TularamThe Black-Scholes model has been a major advance in finance over a period of time; this paper examines this model in some detail, in terms of the latest developments in both analytical and numerical solutions. The paper initially briefly examines historical aspects but quickly moves to a critical analysis of the works in the applications, solutions and implications for the … …Journal of Mathematics and Statistics, Vol. 14, Issue 1 · 8 Jan 2018 · 8,621 accessesView PDFCite
Research ArticleOpen accessIn the abstractFault-Tolerant Control of a Nonlinear Uncertain System: A Neural Network-Based Passive Approaches and Comparative Study with State-of-the-Art Control ApproachesSejal K. Raval, Himanshukumar Rajendrabhai Patel, Vipul A. ShahThis article suggests passive methods for designing Fault-Tolerant Control (FTC) for nonlinear uncertain systems with actuator and leak faults. To anticipate the Fault-Tolerant Control (FTC) action to overcome the actuator and leak faults, two-layer Feed-Forward Back-Propagation Neural Network (FFBPNN) and two-layer Cascade Forward Neural Network (CFNN) have been used, it will also tolerate external process additive disturbances. We employ the … …Journal of Computer Science, Vol. 17, Issue 7 · 3 Aug 2021 · 6,736 accessesView PDFCite