Search Results - (( data selection methods algorithm ) OR ( parameter optimization modified algorithm ))
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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Thesis -
2
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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3
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…This paper proposes a new SGD algorithm with modified stepsize that employs function scaling strategy. …”
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4
VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…Two methods of optimization are used for CBLL. They are Cross Entropy and also Genetic Algorithm. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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7
Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…The original WOA is modified by replacing the equations designed for continuous problem domains with local search methods, enhancing its adaptability to discrete optimization problems. …”
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8
Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…Cuckoo search), and evaluator or model inducing algorithms (e.g SVM) were utilized for feature subset selection, which further compared to select the optimal conditioning factors subset. …”
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Failure detection analysis of grid-connected photovoltaic systems in tropical climate region / Nurmalessa Muhammad @ Atan
Published 2020“…A modified threshold-based technique was used to build the FD algorithm based on data from PV system installed at GERC UiTM, Malaysia. …”
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10
Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…In order to train Ridgelet probabilistic neural network, a modified differential evolution algorithm with new mutation phase, crossover process, and selection mechanism is introduced. …”
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11
Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO
Published 2017“…Due to its discriminative power, the associated optimized WKS values with each point remain extremely stable, which allows for efficient salient features extraction. To assert our method regarding its robustness against topological deformations, experiments show that the method is discriminative and robust to data perturbed by various noises. …”
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Assisted History Matching by Using Recursive Least Square and Discrete Cosine Transform
Published 2014“…Next, RLS is applied to the parameter which has been reduced to optimize the data. …”
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Final Year Project -
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Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…The findings showed that incorporating SPM with single-point crossover resulted in lower objective function (OF) values and improved error indices (EI) compared to traditional GA methods. This enhanced the GA's ability to avoid premature convergence and maintained a diverse solution set, leading to more optimal model selection. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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15
Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…This article presents a new modified cuckoo search algorithm with dynamic discovery probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological damper application. …”
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Modified Harmony Search
Published 2017“…A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in many areas. …”
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Conference or Workshop Item -
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning
Published 2019“…Many variants have been developed to cope with this problem and improve algorithm performance. In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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19
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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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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