Search Results - (( parameters detection method algorithm ) OR ( variable simulation based algorithm ))
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1
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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2
DEVELOPMENT OF OE-BASED BROWN-FORSYTHE TEST ALGORITHM FOR CONTROL VALVE STICTION DETECTION
Published 2018“…Therefore, the main objective of the project is to develop an OE-based Brown-Forsythe test algorithm to effectively detect the presence of control valve stiction.In this study, the proposed OE model is developed using System Identification in MATLAB, where it is used to simulate the process output (PV). …”
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3
A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification
Published 2020“…Control valve stiction is a long-standing problem within process industries. In most methods for shape-based stiction detection, they rely heavily on the traditional controller output (OP) and process variable (PV) plot (i.e. …”
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4
Fault detection and diagnosis using rule-based support system on fatty acid fractionation column
Published 2003“…Process history based methods (rule-based feature extraction) is used to implement the FDD rule-based support system. …”
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5
Numerical Analysis of structural batteries response with the presence of uncertainty
Published 2023“…The proposed research is devoted to the uncertainty analysis of structural battery behavior under various parameters. To help with the analysis, a dedicated algorithm based on an elimination approach to solve numerical problems with uncertain parameters is successfully developed using Visual Basic. …”
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6
Robust Estimation Methods And Outlier Detection In Mediation Models
Published 2010“…Mediation models refer to the relationships among three variables: an independent variables (IV), a potential mediating variable (M), and a dependent variable (DV). …”
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7
Numerical Analysis of Structural Batteries Response with the Presence of Uncertainty
Published 2023“…The proposed research is devoted to the uncertainty analysis of structural battery behavior under various parameters. To help with the analysis, a dedicated algorithm based on an elimination approach to solve numerical problems with uncertain parameters is successfully developed using Visual Basic. …”
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Speed sensorless control for PMSM drives using Extended Kalman Filter
Published 2021“…Therefore, this project proposes sensorless control using an EKF. This method provides an optional estimation algorithm for the non-linear system that can produce a fast and accurate estimation of state variables. …”
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9
Development of new code for optical code division multiple access systems
Published 2011“…This work proposed algorithms for designing a new code with variable cross-correlation properties for the SAC-OCDMA system, namely, Random Diagonal (RD) code. …”
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10
Adaptive Control of Weld Penetration and Trajectory for Robotic GTAW
Published 1996“…Weld process parameters such as base current and time, pulse current and time, electrode tip to workpiece distance, filler traveling speed, torch speed and workpiece thickness were used for finding the equations which describe the interrelationship between the aforementioned variables and penetration depth as well as bead width. …”
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11
Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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12
Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu
Published 2018“…The proposed control algorithm takes advantage of a predefined Lyapunov control law which minimizes the required calculation time by the Lyapunov model equations just once in each control loop to predict future variables. …”
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13
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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14
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. © 2017, UK Simulation Society. …”
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15
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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Weighting method for modal parameter based damage detection algorithms
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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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19
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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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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