Search Results - (( parameters evaluation methods algorithm ) OR ( parameter detection method algorithm ))
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…This creates the jamming detection and classification parameters. The second stage is detecting jammers by integrating both lower layers by developing Integrated Combined Layer Algorithm (ICLA). …”
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Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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4
Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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An analysis of low complexity of 5G-MIMO communication system based CR using hybrid filter detection
Published 2022“…Thus, a 5G-MIMO based CR communication system has been developed to enhance the spectrum by employing a spectrum sensing (SS) algorithm. This recommended SS algorithm, based on the hybrid filter detection (HFD) method, employs the Cosine law for filtering the traffic signal, and then enables segmentation by applying the Welch algorithm. …”
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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…Thus, an Extremal Region Detection (ERD) algorithm in MSER is improved by finding optimum configuration of MSER parameters, allowing the quantity of interest points for certain food images to be increased appropriately. …”
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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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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…The objective is to establish the best transfer learning algorithms with a known baseline parameter for Wafer Defect Detection. …”
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A pothole boundary detection algorithm using image segmentation technique in urban road
Published 2025“…Employing Otsu's method and Canny edge detection, the algorithm seeks to accurately identify and contour the edges of potholes in urban road imagery. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Finally, the effectiveness of the algorithm is evaluated based on the accuracy performance. …”
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Identifying and detecting unlawful behavior in video images using genetic algorithm / Shahirah Mohamed Hatim
Published 2016“…GA is used as the method of unlawful behavior detection. Previous research on GA components impact evaluation has identified selection parameter as high potential of increasing GA performance for unlawful behavior detection. …”
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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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Forward-Backward Time Stepping with Automated Edge-preserving Regularization Technique for Wood Defects Detection
Published 2019“…Therefore, the microwave imaging technique is proposed to detect the wood defects. In this thesis, Forward-Backward Time-Stepping (FBTS) method is applied to microwave imaging wood defect detection application. …”
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
Published 2022“…For volume estimation purpose, a Digital Elevation Models (DEM) were generated from photogrammetric method with flight parameters of three (3) different camera focal length and ten (10) UAV altitude. …”
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Mental stress classification based on selected EEG channels using Correlation Coefficient of Hjorth Parameters
Published 2023“…Furthermore, CCHP outperformed existing channel selection methods by an impressive 8%. These findings strongly indicate that the CCHP algorithm shows great promise in the design of a wearable application for mental stress detection, utilizing a minimal number of EEG channels.…”
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Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach
Published 2023“…Biomass; Coal; Complex networks; Errors; Forecasting; Gasification; Hydrogen production; Learning algorithms; Mean square error; Neural networks; Regression analysis; Sensitivity analysis; Support vector machines; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Machine-learning; Neural-networks; Process parameters; Regression model; Support vectors machine; Syn gas; Synthesis gas; coal; hydrogen; synfuel; biomass; chemical reaction; detection method; hydrogen; machine learning; multicriteria analysis; algorithm; Article; artificial neural network; biomass; controlled study; gasification; Gaussian processing regression; linear regression analysis; machine learning; mean absolute error; mean square error; parameters; prediction; root mean square error; sensitivity analysis; support vector machine; temperature; Bayes theorem; biomass; Bayes Theorem; Biomass; Coal; Hydrogen; Temperature…”
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Lung cancer medical images classification using hybrid CNN-SVM
Published 2021“…This paper presents an image classification method based on the hybrid Convolutional Neural Network (CNN) algorithm and Support Vector Machine (SVM). …”
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Numerical Analysis of structural batteries response with the presence of uncertainty
Published 2023“…Uncertainty of the material properties and loading are modeled as Fuzzy Random Variables. In evaluating the influence of the uncertainty parameters, Interval Monte Carlo Simulation and the interval finite element method are used to compute the bounds of the structure behavior. …”
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Application of neural networks in early detection and diagnosis of parkinson's disease
Published 2014“…Hence, this study proposes a method in early detection and diagnosis of PD by using the Multilayer Feedforward Neural Network (MLFNN) with Back-propagation (BP) algorithm. …”
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Proceeding Paper
