Search Results - (( data detection method algorithm ) OR ( global optimization method algorithm ))

Enhanced computational methods for detection and interpretation of heart disease based on ensemble learning and autoencoder framework / Abdallah Osama Hamdan Abdellatif by Abdalla Osama , Hamdan Abdellatif

“…This thesis presents two innovative methods that holistically address these challenges at algorithmic and data levels to enhance heart disease detection. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…Background Coronary heart disease (CHD) remains a prominent cause of mortality globally, necessitating early and accurate detection methods. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

“…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. …”

Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…Complementing this, the Harmony Search Algorithm (HSA) is incorporated to augment data features, facilitating better pattern recognition and enhancing overall classification accuracy through optimized feature engineering. …”
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection by Shing, Chiang Tan, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Lim, Pey, Yun Goh, Chee, Peng Lim

“…During the training and optimization process, these base learners adopt a hybrid BP and Particle Swarm Optimization algorithm to combine both local and global optimization capabilities for identifying optimal features and improving the classification performance. …”
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A buffer-based online clustering for evolving data stream by Islam, Md. Kamrul, Ahmed, Md. Manjur, Kamal Z., Zamli

“…This algorithm recursively updates the micro-cluster radius to its local optimal. …”
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Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks / Wang Jie ... [et al.] by Wang, Jie, Mohd. Shah, Mohd. Kamal, Choong, Wai Heng, Al-Azad, Nahiyan

“…The aging infrastructure of petroleum and natural gas pipelines poses a threat to national economies, necessitating precise defect detection for safety and efficiency. To enhance the accuracy of predicting pipeline defect sizes, this study introduces a magnetic leakage detection system, employing Backpropagation (BP) neural networks optimized with genetic algorithms. …”
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Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks by Wang Jie, Mohd. Kamal Mohd. Shah, Choong Wai Heng, Nahiyan Al-Azad

“…The aging infrastructure of petroleum and natural gas pipelines poses a threat to national economies, necessitating precise defect detection for safety and efficiency. To enhance the accuracy of predicting pipeline defect sizes, this study introduces a magnetic leakage detection system, employing Backpropagation (BP) neural networks optimized with genetic algorithms. …”
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Comprehensive review of drones collision avoidance schemes: challenges and open issues by Rezaee, Mohammad Reza, Abdul Hamid, Nor Asilah Wati, Hussin, Masnida, Ahmad Zukarnain, Zuriati

“…We explore collision avoidance methods for UAVs from various perspectives, categorizing them into four main groups: obstacle detection and avoidance, collision avoidance algorithms, drone swarm, and path optimization. …”
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Sim, Seera, Manjeevan, Chee, Peng Lim

“…The base learners adopt a hybrid Back-Propagation (BP) and Particle Swarm Optimization (PSO) algorithms to exploit the corresponding local and global optimization capabilities for identifying optimal features and improving FDD performance. …”
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An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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An enhancement particle-based method for dynamic object tracking by Zalili, Musa

“…The third problem to be considered is a to improve the processing time for the process of object detection and tracking. Thus, to address the accuracy of object detection, we proposed a new method of dynamic template matching using Global best Local Neighborhood in Particle Swarm Optimization (GbLN-PSO). …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

“…The temporal micro cluster data structure is proposed in CC_TRS algorithm to store the summarized information for each group of similar segments. …”
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Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning by Goh, Ching Pang

“…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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Improved Cheating Detection in Examinations using YOLOv8 with Attention Mechanism by YAN, ZUO

“…Examinations are pivotal in educational and talent-selection processes globally. Ensuring their integrity is critical, but traditional invigilation methods, combining manual oversight with video monitoring, are resource-intensive and not fully effective in detecting cheating. …”
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Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data by Sameen, Maher Ibrahim

“…Experimental results regarding road geometry extraction indicated that the proposed methods could achieve relatively high accuracy (~ 85% - User’s Accuracy) of road detection from airborne laser scanning data. …”
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Comparative study: Using machine learning techniques about rainfall prediction by Hasan R.A., Alomari M.F., Jamaluddin J.B.

“…Rainfall forecasting is a major problem because of the unreliability of existing methods for predicting rainfall. The purpose of this paper to build an accurate model for the daily prediction of the rainfall in Australia using Python In order to find the optimal model based on testing accuracy, four machine learning algorithms are utilised for training and testing (Logistic Regression, Gaussian Naive Bayes, XGboost classifier, and Random Forest). …”

A Hybrid Method Based on Cuckoo Search Algorithm for Global Optimization Problems by Shehab, Mohammad, Khader, Ahamad Tajudin, Laouchedi, Makhlouf

“…However, it undergoes the premature convergence problem for high dimensional problems because the algorithm converges rapidly. Therefore, we proposed a robust approach to solve this issue by hybridizing optimization algorithm, which is a combination of Cuckoo search algorithm and Hill climbing called CSAHC discovers many local optimum traps by using local and global searches, although the local search method is trapped at the local minimum point. …”
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Global gbest guided-artificial bee colony algorithm for numerical function optimization by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

“…The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. …”
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