scispace - formally typeset
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.

Papers
More filters
Journal ArticleDOI

Application of Euler Neural Networks with Soft Computing Paradigm to Solve Nonlinear Problems Arising in Heat Transfer.

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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.