Search Results - (( model validation method algorithm ) OR ( pattern detection method algorithm ))
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…Finally, both algorithms are validated against the findings in various literatures. …”
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Thesis -
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…On the other hand, when we use computers to reduce uncertainty, the computer itself can become an expert in a specific field through a variety of methods. One such method is machine learning, which involves computer algorithm to capture hidden knowledge from data. …”
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Concrete surface inspection by using unmanned aerial vehicle (UAV) and deep learning algorithms YOLOv7 / Saffa Nasuha Rusdinadi
Published 2024“…These images are then processed using yolov7, a state-of-the-art object detection algorithm, to accurately identify and classify surface cracks. the study involves the collection of a comprehensive dataset of concrete surfaces with varying crack patterns, pre-processed using Roboflow and Opencv tools to enhance crack features. the annotated dataset is utilized to train and validate the yolov7 model, ensuring high precision which is 96.8% and 90.1% recall in crack detection. the performance of the model is evaluated through metrics such as precision, recall, and f1-score, demonstrating its robustness and reliability in detecting both fine and prominent cracks. …”
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Student Project -
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Concrete surface inspection by using Unmanned Aerial Vehicle (UAVs) and deep learning algorithms Yolov7
Published 2024“…The annotated dataset is utilised to train and validate the Yolov7 model, ensuring high precision which is 96.8% and 90.1% recall in crack detection. …”
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Conference or Workshop Item -
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Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim
Published 2025“…The increasing complexity of modern power systems necessitates advanced methods for detecting and classifying power quality disturbances (PQDs), which impact system reliability and equipment performance. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…This performance is validated through rigorous comparative assessments against various classification algorithms and state-of-the-art methods, revealing notable advantages in terms of predictive precision, computational efficiency, and adaptability to real-world clinical scenarios. …”
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A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection
Published 2022“…Besides, the interpretable model can help us demonstrate the complex and overlapped pattern of intrusions and analyze the pattern of various intrusions.…”
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Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain
Published 2019“…Lastly, the MFO-selected features were used as the input for a support vector machine (SVM) diagnostic model to identify fault patterns. To further demonstrate the superiority of the proposed method, other feature selection approaches were applied, including randomly selected features and complete features, and other diagnostic models, namely the multilayer perceptron neural network and k-nearest neighbour. …”
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A Design Of License Plate Recognition System Using Convolutional Neural Network
Published 2019“…This is achieved by validating the best parameters of the enhanced Stochastic Diagonal Levenberg Marquardt (SDLM) learning algorithm and network size of CNN. …”
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
Published 2022“…For volume estimation purpose, a Digital Elevation Models (DEM) were generated from photogrammetric method with flight parameters of three (3) different camera focal length and ten (10) UAV altitude. …”
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Thesis -
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Enhanced faster region-based convolutional neural network for oil palm tree detection
Published 2021“…The detection results were compared with two machine learning methods of ANN, SVM, image processing-based TM method, and the original Faster RCNN model respectively. …”
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. …”
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Conference or Workshop Item -
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…Plots of survival distribution function against failure time are used to examine the predicted survival patterns for the two types of failures. In this thesis we develop a modified Fine and Gray methods to increase the sensitivity of the models and these methods are tested and compared. …”
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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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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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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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A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Monograph -
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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