Search Results - (( panel estimation using algorithm ) OR ( parameter detection method algorithm ))
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1
Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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Thesis -
2
Spacecraft sun-pointing using coplanar solar panels data and magnetic field measurements
Published 2013“…The proposed algorithm has been applied to EgyptSat-1. The satellite is switched from earth-pointing to sun-pointing mode using the estimated sun-vector. …”
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Proceeding Paper -
3
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…The simulation results indicate that the proposed method is suitable to detect a single outlier. As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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Thesis -
4
Attitude and deformation coupled estimation of flexible satellite using low-cost sensors
Published 2022“…The numerical results also demonstrate that including the flexibility model in the developed estimation equations enables the algorithm to successfully estimate the deformation at any solar panel location without the need for any conventional sensor that directly measures the strain and/or deformation.…”
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5
Application of weighted average on modal parameters for damage detection algorithms: Case study on steel beam
Published 2011“…This study verifies the use of the proposed weighting method by Fayyadh and Abdul Razak (2011a) for damage detection algorithms applied on cracked steel beam. …”
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6
Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE
Published 2014“…A fuzzy logic estimator (FLE) is used to estimate the new duty cycle used to track the PV array maximum power point. …”
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7
Weighting method for modal parameter based damage detection algorithms
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8
Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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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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Thesis -
10
Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm
Published 2014“…This study focuses on using GSA method, a new computational intelligence algorithm. …”
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Conference or Workshop Item -
11
Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm
Published 2023“…This project aims to measure the performances of various photovoltaic power plants in Malaysia based on local spectral irradiances using genetic algorithm. A Python computational model that uses genetic algorithms will be developed to estimate the optimal tilt angle and orientation angle as well as the solar power received for the solar sites. …”
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Final Year Project / Dissertation / Thesis -
12
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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Thesis -
13
Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The NTLBO was proposed in this paper as an FSS mechanism; its algorithm-specific, parameter-less concept (which requires no parameter tuning during an optimization) was explored. …”
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Article -
14
Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…The existence of outliers in a circular regression model can lead to many errors, for example in inferences and parameter estimations. Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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Conference or Workshop Item -
15
Comparison of UAV flying height parameter for crack detection applications / Wan Nurdayini Batrisyia Wan Ghazali
Published 2024“…The key concern of this thesis is to determine the influence of flying height parameters on crack detection using UAVs. Looking at the current scenario of development and the age of the structures in urban areas, there is a high significance of efficient and accurate building inspection methods. …”
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Student Project -
16
Fuzzy modelling using butterfly optimization algorithm for phishing detection
Published 2020“…To generate the fuzzy parameter automatically, an optimization method is required and Butterfly Optimization Algorithm (BOA) is one of the good methods to be applied. …”
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17
Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”
Conference Paper -
18
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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19
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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Article -
20
The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms
Published 2024“…Meanwhile, SL-Satari/Di, CL-Satari/Di, and AL-Satari/Di algorithms are recommended to be used for large sample sizes since these algorithms perform very well in detecting the outliers and have low masking and swamping effect at any percentage of outliers and concentration parameter. …”
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Conference or Workshop Item
