Search Results - (( variable detection model algorithm ) OR ( java application stemming algorithm ))
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1
Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud
Published 2018“…Slope variability model is an algorithm that is being used for detecting terrain roughness. …”
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2
Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)
Published 2006“…Results showed that the developed FDD algorithm successfully detect and diagnosed the pre-designed faults. …”
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Monograph -
3
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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4
Fault diagnostic algorithm for precut fractionation column
Published 2004“…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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5
A study on advanced statistical analysis for network anomaly detection
Published 2005“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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Monograph -
6
Observer-based fault detection with fuzzy variable gains and its application to industrial servo system
Published 2020“…This work is interested in proposing an observer with fuzzy variable gains for a general nonlinear system. Furthermore, a linear model has been built to facilitate the accomplishment of the fault detection of the industrial servo system by using the proposed observer. …”
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Article -
7
Fault Detection Relevant, Neural Network and Evolutionary Algorithm based Model for a Single-shaft Industrial Gas Turbine
Published 2009“…Analytical redundancy based fault detection system generally requires an accurate model. …”
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8
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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9
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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10
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…Sure screening-based correlation methods are popular tools used to select the most significant variables in the true model in sparse and high dimensional analysis. …”
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11
An Automated Method For Model-Plant Mismatch Detection And Correction In Process Plants Employing Model Predictive Control (MPC)
Published 2012“…Since MPM has significant effect on MPC performance, the model has to be corrected and updated whenever high MPM is detected. …”
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Final Year Project -
12
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Later, we assess the performance of confidence interval for error concentration parameter for the new functional relationship model via simulation study. Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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13
Robust Estimation Methods And Outlier Detection In Mediation Models
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14
Pure intelligent monitoring system for steam economizer trips
Published 2023“…Economizers; Failure (mechanical); Fault detection; Knowledge acquisition; Learning algorithms; Learning systems; Neural networks; Plant shutdowns; Steam; Thermoelectric power plants; Extreme learning machine; Fault detection and diagnosis systems; Intelligent modeling; Intelligent monitoring systems; Network methodologies; Operational conditions; Operational variables; Thermal power plants; Steam power plants…”
Conference Paper -
15
An Optimized Semantic Segmentation Framework for Human Skin Detection
Published 2024“…Existing approaches used complex and various heuristic designs of image processing algorithms and deep models customized for skin detection problems. …”
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Article -
16
Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri
Published 2023“…Dimension reduction algorithm such as LDA and CNN were applied on the spectra to reduce the number of variables to be trained. …”
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17
ECG-based driving fatigue detection using heart rate variability analysis with mutual information
Published 2023“…The results of the experiments show that the random forest algorithm with 44 selected features produced the best model performance testing accuracy of 95.45%, with cross-validated accuracy of 98.65%.…”
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Article -
18
Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The second algorithm reduces the quantity of interest regions by using the Extremal Region Selection (ERS) algorithm. …”
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19
A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification
Published 2020“…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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20
Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory
Published 2015“…Fault related parameters thus can be considered as subsets of the abovementioned trajectories and therefore can be modelled and analysed. Mathematical models of the plants are first derived through the description of the manifest behavior by elimination of the latent variables via a systematic algorithm. …”
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