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F. H. Bellamine
Researcher at University of Waterloo
Publications - 6
Citations - 59
F. H. Bellamine is an academic researcher from University of Waterloo. The author has contributed to research in topics: Artificial neural network & Differential equation. The author has an hindex of 4, co-authored 6 publications receiving 56 citations. Previous affiliations of F. H. Bellamine include National Institute of Applied Science and Technology.
Papers
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Model order reduction using neural network principal component analysis and generalized dimensional analysis
F. H. Bellamine,Ali Elkamel +1 more
TL;DR: A novel computational intelligence technique to generate concise neural network models for distributed dynamic systems based on artificial neural network architectures that incorporate linear and nonlinear principal component analysis, combined with generalized dimensional analysis.
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Numerical characterization of distributed dynamic systems using tools of intelligent computing and generalized dimensional analysis
TL;DR: The hybrid use of generalized dimensional analysis and neural networks is a powerful tool that can be employed for the solution of differential equations modeling physical processes and the results obtained prove the effectiveness of this approach when compared to the traditional discretisation simulation schemes.
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Modeling of complex dynamic systems using differential neural networks with the incorporation of a priori knowledge
TL;DR: In this paper, neural algorithms, including the multi-layered perceptron (MLP) differential approximator, generalized hybrid power series, discrete Hopfield neural network, and hybrid numerical, are used for constructing models that incorporate a priori knowledge in the form of differential equations for dynamic engineering processes.
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Computer facilitated generalized coordinate transformations of partial differential equations with engineering applications
TL;DR: The use of Maple or similar computer algebraic systems (e.g. Mathematica, Reduce, etc.) will help researchers and students use uncommon transformations more frequently at the very least for situations where the transformations provide smarter and easier solutions.
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Numerical simulation of distributed dynamic systems using hybrid intelligent computing combined with generalized similarity analysis
TL;DR: The hybrid use of generalized similarity analysis with intelligent computing tools such as neural networks and fuzzy logic, provide accurate and fast numerical simulation for distributed dynamic systems.