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3 articles for “homogeneous vector”
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Homogeneous geodesics on the solvable homogeneous principal bundles
Abstract: Let $M=G/K$ be a homogeneous differentiable manifold .We consider the homogeneous bundle $\Im=(G,\pi,G/K,K)$ and the tangent bundle $\tau_{G/K}$ of $M=G/K$. Let $G$ be a connected Lie group and $K$a closed subgroup of $G$. We take the Lie algebras $\cal{G}$ and$\cal{K}$ of $G$ and $K$ respectively and define $\xi=(G\times_{K}\cal{ G} / \cal {K}, \rho_{\xi}, \emph{G} / \emph{K},\cal {G} /\cal {K})$ to be the bundle associated with $\Im$. We considerthat $ \xi$ …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 3, Issue 2, 2016 · pp. 26–37 Read article
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AI-Driven Prediction of Mechanical and Thermal Properties in Polymer-Based Functionally Graded Composites
Abstract: The proposed architecture of the current paper is an artificial intelligence (AI)-driven model of forecasting mechanical and thermal aspects of polymer-based functionally-graded composites (FGCs). Traditional micromechanical and finite element models, which are practical in homogeneous composites, might not be able to account in nonlinear interaction that is caused by compositional gradient. To overcome the challenge, machine learning (ML) models like artificial neural network (ANN), support vectors regression (SVR), and gradient-boosted …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 70–89 Read article
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Parameter Estimation of Software Reliability Growth Model
Abstract: Reliability normally covers each and every part of the device thinking about hardware, software program and processes but software program reliability paperwork an important factor as we are continually worried with efficient and quality software program. Software reliability is a crucial characteristic of software, nice for predicting the diploma of creditability of the precise software for the specified time frame and in particular surroundings. Software reliability models are categorized into …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 1, 2020 · pp. 15–22 Read article