Search Results - (( problem implementation phase algorithm ) OR ( based optimization method algorithm ))
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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Thesis -
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Article -
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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4
Distance based sweep nearest algorithm to solve capacitated vehicle routing problem
Published 2016“…Among several methods, Sweep algorithm in 2-phase approach is popular in solving CVRP. …”
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Proceeding Paper -
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Development of committee machine models for multiple response optimization problems
Published 2014“…Three phases are considered to solve MRO problems and they include design of experiments, modeling, and optimization. …”
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Solving vehicle routing problem by using improved genetic algorithm for optimal solution
Published 2023Article -
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Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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Smart Routing For Solid Waste Collection
Published 2023“…The proposed solution is to implement a route optimization algorithm to predict the probability of each feasible route for the garbage truck collection. …”
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Final Year Project Report / IMRAD -
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Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution
Published 2017“…Approach: The approach has been presented based on two phases: firstly, the algorithms have been adapted to solve the research problem, where its procedure is different than the common algorithm. …”
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Performance optimization method in OFDM based on majorization and minimization technique
Published 2019“…Another type of noise is known as Additive White Gaussian Noise (AWGN) or thermal noise whose effect is negligible comparing to phase noise. In this paper, we demonstrate and simulate a practical algorithm to mitigate phase noise which induces ICI .This algorithm is termed as Tight Quadratic Majorization (TQM) and is derived for phase noise estimation. …”
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…The existing literature extensively explores the utilization of powerful Metaheuristic Algorithms (MAs) to address the complex constrained optimization problem in PV systems and achieve optimal solutions. …”
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Overhead view based person counting using deep learning
Published 2022“…In conventional video surveillance systems, most of the person detection methods are based on frontal view, which may have lower accuracy stemming from the occlusion problem. …”
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Final Year Project / Dissertation / Thesis -
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Graph theory approach for managing lecturers’ schedule using graph colouring method / Siti Nor Ba Basri, Nur Su’aidah Khozaid and Farhana Hazwani Ismail
Published 2023“…Different colours are allocated to each vertex using graph colouring techniques such as the vertices algorithm or the edges algorithm, ensuring that clashing courses and lecturers are assigned different time slots. …”
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Student Project -
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A Constrained Optimization based Extreme Learning Machine for noisy data regression
Published 2023“…Artificial intelligence; Benchmarking; Data handling; Knowledge acquisition; Lagrange multipliers; Learning systems; Optimization; Regression analysis; Benchmark data; Constrained optimization methods; Data regression; Extreme learning machine; Kernel function; Noisy data; Optimization problems; Support vector regression (SVR); Constrained optimization; nitric oxide; algorithm; Article; artificial intelligence; artificial neural network; classifier; combustion; entropy; exhaust gas; extreme learning machine; fuzzy system; generalized regression neural network; generalized regression neural network and fuzzy art; housing; kernel method; logistic regression analysis; machine learning; Malaysia; priority journal; probabilitistic entropy based neural network; process optimization; radial based function; regression analysis; support vector machine…”
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Modeling Of Electrical Distribution Networks With Particle Swarm Optimization Technique For The Improvement Of Voltage Profile And Loss Reduction
Published 2016“…The method is accurate and has advantage as easy to implement which accomplished with Carson's equations. …”
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Festive season balancing groceries optimization / Fairuz Mohamed Razi
Published 2012“…An Artificial Intelligence method or technique is selected to provide a solution to this problem. The cause of the shortage in supply-demand is taken to be implemented in the Genetic Algorithms optimization concepts. …”
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Force and impedance control for hydraulically driven hexapod robot walking on uneven terrain
Published 2012“…Three new adaptive impedance controller are designed and proposed: Optimal single leg impedance control based on body inertia, Optimal center of mass—based impedance control based on body inertia and Single leg impedance control with self-tuning stiffness. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Multi-objective optimisation of assembly line balancing type-e problem with resource constraints
Published 2016“…In the second phase of this research, an algorithm will be developed to optimise the problem. …”
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