Search Results - (( using estimation method algorithm ) OR ( rule detection method algorithm ))*
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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 -
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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 -
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The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms
Published 2024“…The outliers are detected by cutting the dendrogram at a specific height using the stopping rule and classifying the observations that exceed the stopping rule as potential outliers. …”
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Semi-automatic oil palm tree counting from pleiades satellite imagery and airborne LiDAR / Nurul Syafiqah Khalid
Published 2020“…There are three objectives, firstly, to produce tree height estimation by using the Canopy Height Model (CHM). Secondly, to develop the rule sets of watershed transformation segmentation and local maxima algorithm using Pleiades and LiDAR. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We classify the cluster group that exceeds the stopping rule as potential outliers. Model verification of all method and model proposed in this study are examined using the simulation study. …”
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Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking
Published 2012“…The solution consists of an algorithm for automatic collection of candidate seed points using efficient grid line searching mechanism and a validation method which uses local geometric and intensity based features as effective validation rules to discriminate between the actual seed point and false alarms. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Based on previous researches, most existing segmentation methods focused on a specific environment. Therefore, this research has developed an improved edge detection and contour segmentation algorithm that is able to correctly segment various objects from both indoor and outdoor images. …”
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Engine fault diagnosis using probabilistic neural network
Published 2021“…The proposed PNN is trained using the collected engine fault data from experiment and the probability density of PNN is determined based on the Parzen window estimation method. …”
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Proceedings -
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis
Published 2022“…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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Undergraduates Project Papers -
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Improved Malware detection model with Apriori Association rule and particle swarm optimization
Published 2019“…These rule models are used together with extraction algorithm to classify and detect malicious android application. …”
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Article -
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Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection
Published 2023Conference Paper -
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition
Published 2021“…This paper proposed the fuzzy-ID3 (FID3) algorithm, a fuzzy decision tree as the classification method in breast cancer detection. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Comparative study of clustering-based outliers detection methods in circularcircular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Article -
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The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…We classify the cluster group that exceeds the stopping rule as potential outlier. Our aim is to demonstrate the effectiveness of proposed algorithms with the similarity distances in detecting the outliers. …”
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Article -
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Optimizing the performance of mobile malware detection using the indexing rule
Published 2024journal::journal article
