Search Results - (( pattern detection method algorithm ) OR ( _ validation method algorithm ))
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1
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 -
2
Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”
Conference Paper -
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…As the individual chewing pattern varies from person to person, this article uses a novel parameter search using the PSO method to find the multiplier (parameter values) according to the average peak prominence and width value within each chewing episode. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…As the individual chewing pattern varies from person to person, this article uses a novel parameter search using the PSO method to find the multiplier (parameter values) according to the average peak prominence and width value within each chewing episode. …”
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Concrete surface inspection by using unmanned aerial vehicle (UAV) and deep learning algorithms YOLOv7 / Saffa Nasuha Rusdinadi
Published 2024“…This research aims to improve the detection and analysis of cracks on concrete surfaces by utilizing UAVs and yolo algorithms. …”
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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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7
Concrete surface inspection by using Unmanned Aerial Vehicle (UAVs) and deep learning algorithms Yolov7
Published 2024“…This research aims to evaluate the detection and analysis of cracks on concrete surfaces by utilizing Uavs and Yolo algorithms. …”
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8
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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Effective mining on large databases for intrusion detection
Published 2014“…These two different mining methods are then tested and compared to find out which one produces more accurate valid patterns for the intrusion detection system. …”
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10
Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi
Published 2017“…In the implementation phase, Bubble Sort, Euclidean Distance, 10-Fold Cross validation, and K Nearest Neighbor algorithm are developed. …”
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11
A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection
Published 2022“…Using 22 attributes that highly related to the target, the performance of the proposed method achieves a 99.86% detection rate and 0.14% false alarm rate on the KDDTrain+dataset, a 77.46% detection rate on the KDDTest+dataset, which is better than many classifers. …”
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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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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
Published 2022“…Only one dynamic variable is used as a tuning parameter reducing the complexity of the algorithm. The search space skipping method has been proposed to improve the CS. …”
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14
Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain
Published 2019“…Second, the MFO algorithm was utilised to select the optimal discriminative features. …”
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A Design Of License Plate Recognition System Using Convolutional Neural Network
Published 2019“…The main contribution of this work is on the methodology to determine the best model for four-layered CNN architecture that has been used as the recognition method. 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“…Meanwhile, nine (9) classifier algorithms and forty (40) band stack combinations were deployed to classify the pothole edge. …”
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17
Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement
Published 2023“…The stereo vision algorithm computes disparity using local, global, and semiglobal optimisation methods established by the researcher. …”
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Sequential pattern mining using personalized minimum support threshold with minimum items
Published 2011“…One of the challenges of Sequential Pattern Mining is finding frequent sequential patterns in a huge click stream data (web logs) since the data has the issue of a very low support distribution.By applying a Frequent Pattern Discovery technique, a sequence is considered as frequent if it occurs more than the minimum support (min sup) threshold value.The conventional method of assuming one min sup value is valid for all levels of k-sequence, may have an impact on the overall results or pattern generation. …”
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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“…Based on the location of the lung, the liver dome is automatically detected and the liver is then extracted by random walkers method and refined using a fuzzy level set method. …”
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20
2D and 3D video scene text classification
Published 2014“…Experimental results on clasifying 2D and 3D text images are promising, and the result re further validated by text detection and recognition before clasification and after clasification with the exiting methods, respectively.…”
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