Search Results - (( parameter optimization method algorithm ) OR ( using interactive _ algorithm ))*
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Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite
Published 2025“…This study proposes a combinatorial testing method utilizing the Whale Optimization Algorithm (WOA). …”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…Leveraging state-of-the-art Multi-Objective Optimization algorithms, the research delves into the intricate dynamics of tumour and effector cell interactions within the context of chemotherapy. …”
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Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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Using Spiral Dynamic Algorithm for Maximizing Power Production of Wind Farm
Published 2017“…For simplicity, a single row wind farm model with turbulence interaction between turbines is used to validate the proposed approach. …”
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…Extensive experimentation with genetic algorithm parameters has yielded promising results, notably a parameter set (population size = 12, generation size = 30, mutation rate = 0.2) demonstrating robust performance, achieving optimal timetables with swift convergence and minimal conflicts. …”
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Performance properties optimization of triaxial ceramic-palm oil fuel ash by employing Taguchi design and flower pollination algorithm
Published 2018“…In the meantime, both linear and interaction approach of FPA developed following optimal parameters: 5 wt.% of ground POFA, pressed at 4 t, and sintered at 1200 °C for 300 min of soaking time. …”
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Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking
Published 2017“…Until now, there are still no perfect algorithm to track the target flawlessly. In order to improve the performance, the main idea proposed is implementing optimization technique on the selected parameters and obtain a better performance. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…Researchers have in the past few decades resorted to several methods that are inspired from complex optimization problems. …”
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10
Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks
Published 2014“…The results demonstrated that our proposed method results in significant reductions of HOF, HOPP and packet loss ratio (PLR) compared to the conventional HHO and enhanced weighted performance HO parameter optimization (EWPHPO) algorithm. …”
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11
A fast learning network with improved particle swarm optimization for intrusion detection system
Published 2019“…However, the internal power parameters (weight and basis) of FLN are initialized at random, causing the algorithm to be unstable. …”
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12
Cellular Harmony Search for Optimization Problems
Published 2013“…Structured population in evolutionary algorithms (EAs) is an important research track where an individual only interacts with its neighboring individuals in the breeding step. …”
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Optimization of process parameters for pyrolsis of waste plastics by T method-1
Published 2023text::Final Year Project -
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Model-free controller design based on simultaneous perturbation stochastic approximation
Published 2015“…In order to evaluate the effectiveness of our proposed scheme, a wind farm model with dynamic characterization of wake interaction between turbines is used and then the proposed method is applied to the Horns Rev wind farm. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. …”
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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Improving neural networks training using experiment design approach
Published 2005“…This data is selected by two methods: random and Experiment Design Approach (D-optimal and Maxmin Distance). …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The ARTMAP system is dependent on training sequence presentation to determine the effectiveness of the learning processes, as well as the strength of the biasing parameter, lambda λ. The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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An enhanced motion planning method for industrial robots based on the digital twin concept
Published 2025“…By integrating an improved Artificial potential field method, A* algorithm, and a synergistic approach combining 3-5-3 polynomial interpolation with particle swarm optimization, we effectively address the challenges of dynamic obstacle avoidance and trajectory optimization. …”
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