Search Results - (( variable extraction based algorithm ) OR ( data evaluation method algorithm ))
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. …”
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The framework of weighted subset-hood Mamdani fuzzy rule based system rule extraction (MFRBS-WSBA) for forecasting electricity load demand
Published 2016“…Fuzzy rules are very important elements that should be taken consideration seriously when applying any fuzzy system.This paper proposes the framework of Mamdani Fuzzy Rule-based System with Weighted Subset-hood Based Algorithm (MFRBS-WSBA) in the fuzzy rule extraction for electricity load demand forecasting.The framework consist of six main steps: (1) Data Collection and Selection; (2) Preprocessing Data; (3) Variables Selection; (4) Fuzzy Model; (5) Comparison with Other FIS and (6) Performance Evaluation. …”
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Conference or Workshop Item -
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The framework of weighted subset-hood Mamdani fuzzy rule based system rule extraction (MFRBS-WSBA) for forecasting electricity load demand
Published 2016“…This paper proposes the framework of Mamdani Fuzzy Rule-based System with Weighted Subset-hood Based Algorithm (MFRBS-WSBA) in the fuzzy rule extraction for electricity load demand forecasting. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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Thesis -
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The motor features are extracted through the proposed Discrete Wavelet Transform (DWT) based analysis method, while the wavelet inlet acts as an expert tool to adapt the right controller in accordance with the fault type. …”
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9
Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah
Published 2022“…The SMU method based on the improved model was used to predict the variability of the dynamic behaviour of the structure. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…In an imbalanced dataset, one of the two classes contains fewer total samples than the other class. The sampling-based method, also known as the data level method, is used to deal with this problem. …”
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Classification for large number of variables with two imbalanced groups
Published 2020“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach
Published 2015“…Intrusion detection systems (IDSs) effectively balance additional security in a computer system by identifying intrusive activities on a computer system, and their enhancements are developing at a surprising rate. Detection methods based on statistical and data mining techniques are widely deployed as anomaly-based detection system (ADS). …”
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13
Development Of Fall Risk Clustering Algorithm In Older People
Published 2020“…Therefore, the aim of this study is to develop a clustering-based fall risk algorithm which can provide assistances for clinician in management of falls. …”
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Final Year Project / Dissertation / Thesis -
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Optimized clustering with modified K-means algorithm
Published 2021“…In dealing with correlated variables, PCA was embedded in the proposed algorithm. …”
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An Enhanced Hybrid Method Using AES Algorithm And Arabic Text Steganography
Published 2024thesis::master thesis -
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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Case Slicing Technique for Feature Selection
Published 2004“…Since the 1960s, many algorithms for data classification have been proposed. …”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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