Search Results - (( parallel optimization sensor algorithm ) OR ( variable iteration method algorithm ))
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Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance
Published 2021“…The thesis was set to three objectives as follows; to develop a new augmentation algorithm of Simplex method from the existed augmentation studies; to integrate the superiorities of the QSM and BLSA algorithms that can enhance computational performance; to compare the performance of the new augmentation algorithm with the conventional Simplex, QSM and BLSA in reducing iteration number. …”
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Thesis -
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Partial Newton methods for a system of equations
Published 2013“…This is because it uses only one or two variables instead of all the search variables in each iteration.…”
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly
Published 2023“…The next method is simplex method. The simplex method is a conceptual model approach for analysing linear programming problems with any number of variables. …”
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Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin
Published 2018“…Broyden-Fletcher-Goldfarb-Shanno (BFGS) is one of a well-known Quasi-Newton update formula. This method is generally considered as the most efficient method among other variable metric methods for solving unconstrained optimization problems. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…Stereo vision sensor consists of two stereo cameras, mounted parallel in stationary position. …”
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Model selection approaches of water quality index data
Published 2016“…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh
Published 2018“…The obtained results are compared with the results of four algorithms. These algorithms are Genetic Algorithms (GA), Parallel Genetic Algorithm (PGA), Particle Swarm Optimization (PSO) and Accelerated Particle Swarm Optimization (APSO). …”
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Performance monitoring algorithm for optimizing electrical power generated by using photovoltaic system
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Conference or Workshop Item -
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…The model employs a two-level structure, where the first level uses standard soft constraints as the objective function to evaluate solution quality, while the second level dynamically adapts to faculty-specific preferences. A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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The efficiency of conjugate gradient methods with global convergence / Siti Nur Hafiza Shamsudin
Published 2019“…Numerical result shows that algorithm 2 which is one of the proposed CG methods is more efficiency when compared to other algorithms.…”
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Existence and uniqueness for the evolutionary impulse control problem using an asynchronous algorithms
Published 2025“…Our approach unfolds through a four-step methodology, leveraging distinctive features of a discrete iterative technique. This methodology integrates semi-implicit techniques with respect to the variable t and employs spatial approximation via finite element methods. …”
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Towards large scale unconstrained optimization
Published 2007“…This method computes a Newton-type direction by truncating the conjugate Gradient method iterates (inner iterations) whenever a required accuracy is nobtained, thereby the superlinear convergence is guaranteed. …”
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Inaugural Lecture -
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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm
Published 2019“…Therefore, in this study SUREAutometrics is improvised using two MLE methods, which are iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm, named as SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics algorithms. …”
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FPGA implementation of variable precision Euclid’s GCD algorithm
Published 2017“…Methodology: In this paper, we implement a fast GCD coprocessor based on Euclid's method with variable precisions (32-bit to 1024-bit). …”
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Design of digital circuit structure based on evolutionary algorithm method
Published 2008“…The proposed method is an iterative procedure that consists of a constant-size population of individuals, each one encoding a possible solution in a given problem space. …”
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