Search Results - (( model evaluation method algorithm ) OR ( evolution optimisation based algorithm ))
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1
Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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Thesis -
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Article -
4
A competitive co-evolutionary approach for the nurse scheduling problem
Published 2026“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Book Section -
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Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting
Published 2013“…These algorithms include equal�weights combination of Best NN models, combination of trimmed forecasts, combination through Variance-Covariance method and Bayesian Model Averaging. …”
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9
B-spline curve fitting with different parameterization methods
Published 2020“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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Final Year Project / Dissertation / Thesis -
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method
Published 2021“…Thus, unify a set of most suitable evaluation criteria of the MaOO is needed. This study proposed a distinct unifying model for the MaOO evaluation criteria using the fuzzy Delphi method. …”
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Evaluating the effectiveness of integrated benders decomposition algorithm and epsilon constraint method for multi-objective facility location problem under demand uncertainty
Published 2017“…For this aim, a multi-objective facility location allocation model is proposed. In this case, an integrated BDA and epsilon constraint method are proposed and it is shown that how Pareto points in multi-objective facility location model can be found. …”
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Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods
Published 2021“…The evaluation criteria of Many Objective Optimization algorithm (MaOO) play a critical role in evaluating the competition MaOO algorithms. …”
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Incorporating the range-based method into GridSim for modeling task and resource heterogeneity
Published 2017“…In this paper, we propose a new simulation model that incorporates the range-based method into GridSim for modeling and simulating heterogeneous tasks and resources in order to capture the inherent heterogeneity of Grid environments that later can be used by other researchers to test their algorithms.…”
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Evaluation of Lightning Current Using Inverse Procedure Algorithm.
Published 2013“…The proposed method considers on all electromagnetic fields components and can evaluate full shape of current, velocity and constant parameters of current models in contrast with previous studies. …”
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Hybrid performance measures and mixed evaluation method for data classification problems
Published 2012“…In fact, no previous studies employ mixed evaluation method in evaluating and comparing the performance measures. …”
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Thesis -
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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market
Published 2024“…By setting the ML algorithms and their parameter along with using Walk-Forward Analysis (WFA) method, the algorithm design of trading signal was evaluated based on two groups of evaluation indicators, namely directional and performance. …”
thesis::master thesis -
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
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Development of an Automated Technique for Reconstructing Jawi Characters in Historical Documents
Published 2007“…A noise model has been developed to test the reliability of the proposed algorithm. …”
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Thesis -
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Visualisasi pohon sintaksis berasaskan model dan algoritma sintaks ayat bahasa Melayu
Published 2018“…To achieve these objectives (the algorithm, the model and the X-bar rules), five phases of research methods involved namely identifying the research gap, the sentence and rules categorization, model and algorithm design phase, prototype development evaluation and conclusion phase. …”
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