M
Maharani Abu Bakar
Researcher at Universiti Malaysia Terengganu
Publications - 11
Citations - 111
Maharani Abu Bakar is an academic researcher from Universiti Malaysia Terengganu. The author has contributed to research in topics: Computer science & Soft computing. The author has an hindex of 2, co-authored 11 publications receiving 16 citations.
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Journal ArticleDOI
Application of Euler Neural Networks with Soft Computing Paradigm to Solve Nonlinear Problems Arising in Heat Transfer.
Naveed Ahmad Khan,Osamah Ibrahim Khalaf,Carlos Andrés Tavera Romero,Muhammad Sulaiman,Maharani Abu Bakar +4 more
TL;DR: In this article, a novel application of neurocomputing technique is presented for solving nonlinear heat transfer and natural convection porous fin problems arising in almost all areas of engineering and technology, especially in mechanical engineering.
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Thermal Analysis of Conductive-Convective-Radiative Heat Exchangers With Temperature Dependent Thermal Conductivity
TL;DR: In this paper, an intelligent soft computing paradigm named as the LeNN-WOA-NM algorithm is designed to analyze the mathematical model for the temperature field of convective-conductive-radiative fin with thermal conductivity depending on temperature.
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Mathematical models of CBSC over wireless channels and their analysis by using the LeNN-WOA-NM algorithm
TL;DR: In this article, a novel computational paradigm that uses weighted Legendre polynomials to construct series solutions for mathematical models of the Lorenz Chaotic Attractor and Double Scroll Attractor (DSA) by using Chua's circuits was designed.
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A Modified Bat Algorithm for Solving Large-Scale Bound Constrained Global Optimization Problems
TL;DR: A modified Bat algorithm (MBA) is developed to further enhance the exploration and exploitation search abilities of the original Bat algorithm.
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Large-scale bound constrained optimization based on hybrid teaching learning optimization algorithm
TL;DR: A hybrid TLBO (HTLBO) with aim at to further improve the exploration and exploitation abilities of the baseline TLBO algorithm and are better than some well-known evolutionary algorithms in terms of proximity and diversity.