Search Results - (( time optimization based algorithm ) OR ( parameter detection method algorithm ))
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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Thesis -
3
Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm
Published 2014“…The main intention of this study is to find the significant peak features in time domain approach and this can be done using feature selection methods such as gravitational search algorithm (GSA) and particle swarm optimization (PSO). …”
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4
Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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5
Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
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Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
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7
Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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8
Exploration and Exploitation Mechanism in Pairwise Test Case Generation: A Systematic Literature Review
Published 2025“…Covering research from 2014 to 2024, the review evaluates hybrid and metaheuristic strategies, including Pairwise Migrating Birds Optimization-Based Strategies (PMBOS), Pairwise Gravitational Search Algorithm Strategy (PGSAS), Pairwise hybrid Artificial Bee Colony (PhABC), Genetic and Particle Swarm Optimization (GAPSO) algorithm, Hybrid Optimization Algorithm (HOA), and Parameter Free Choice Function based Hyper-Heuristic (PCFHH), among others. …”
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Road damage detection for autonomous driving vehicles using YOLOv8 and salp swarm algorithm
Published 2025“…Finding suitable sets of hyperparameters for this task is time-consuming. Consequently, this paper proposes a method to improve the detection accuracy of You Only Look Once version 8 (YOLOv8) using Salp Swarm Algorithm (SSA) for hyperparameter optimization, focusing on eight key parameters. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…As such, its training can reach stability in a shorter time compared to the gradient-descent based methods. …”
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11
Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel
Published 2016“…Results show that the defect detection algorithm able to detect defect only on the scratch area and able to read the Ga value at detected scratch line and transform it to surface roughness measurement at considerably good level of accuracy compared with manual method. …”
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12
Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. …”
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13
Observer-based fault detection approach using fuzzy adaptive poles placement system with real-time implementation
Published 2021“…This paper validated the system simulation by implementing fault detection algorithms by using a real-time embedded observer-based system. …”
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14
Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications
Published 2025“…On the other hand, artificial intelligence had been ways to enhances embedded system by enabling real-time, accurate detection and management of PCB defects through advanced pattern recognition and automated inspection methods. …”
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Final Year Project / Dissertation / Thesis -
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SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique
Published 2023Conference Paper -
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Mental stress classification based on selected electroencephalography channels using correlation coefficient of Hjorth parameters
Published 2023“…Leveraging features from the time, frequency, and time–frequency domains of these channels, and employing machine learning algorithms, notably RLDA, SVM, and KNN, our approach achieved a remarkable accuracy of 81.56% with the SVM algorithm outperforming existing methodologies. …”
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Power System State Estimation In Large-Scale Networks
Published 2010“…Also the WLS algorithm is modified to include Unified Power Flow Controller (UPFC) parameters. …”
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19
Color image enhancement of acute leukemia cells in blood microscopic image for leukemia detection sample
Published 2020“…This report introduces a new enhancement method which is a combination of Particle swarm optimization (PSO) algorithm and contrast stretching, known as Hybrid PSO-Contrast stretching (HPSO-CS). …”
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Conference or Workshop Item -
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Results show that the proposed method is able to detect islanding conditions with 100% accuracy, 100% detection rate and 0% false alarm with detection time of less than 0.19s. …”
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Thesis
