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1
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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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…An efficient IDS uses computational methods as techniques of machine learning (ML) to enhance the rates of detection to obtain the lowest false positive rate, although such rates tend to be reduced by the big amount of irrelevant features as an optimization issue. …”
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Thesis -
3
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. 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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4
Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…In this paper we propose an intrusion detection method that combines Fuzzy Clustering and Genetic Algorithms. …”
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5
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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Optimizing high-density aquaculture rotifer Detection using deep learning algorithm
Published 2022“…In this paper, we present the method and performance to detect rotifer Brachionus plicatilis in 1ml sample automatically using deep learning algorithm YOLOv3. …”
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7
Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection
Published 2024“…HBA as metahueristic algorithm is used to optimize the network training process of ANN to improve their performances. …”
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Enhanced computational methods for detection and interpretation of heart disease based on ensemble learning and autoencoder framework / Abdallah Osama Hamdan Abdellatif
Published 2024“…However, the challenge of class imbalance and high dimensionality in clinical data significantly impedes the efficacy of Machine Learning (ML) models in this domain. 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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9
A hybrid deep learning-based unsupervised anomaly detection in high dimensional data
Published 2022“…However, Adamax optimization algorithm showed the best results when employed to train the DANN model. …”
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A fast learning network with improved particle swarm optimization for intrusion detection system
Published 2019“…In current days the intrusion detection systems (IDS) have several shortcomings such as high rates of false positive alerts, low detection rates of rare but dangerous attacks, and the need for a constant human intervention and tuning. …”
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11
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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12
An efficient anomaly intrusion detection method with evolutionary neural network
Published 2020“…The third proposed method is a new Evolutionary Neural Network (ENN) algorithm with a combination of Genetic Algorithm and Multiverse Optimizer (GAMVO) as a training part of ANN to create efficient anomaly-based detection with low false alarm rate. …”
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13
Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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14
Early detection of dengue disease using extreme learning machine
Published 2018“…Therefore, the proposed ELM model can be considered as an alternative algorithm to apply for early detection of Dengue disease.…”
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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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Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption
Published 2024“…Our quantitative tests show that the improved model has the best coverage (95.3%, 84.3% and 65.8%, respectively) compared to two other methods Levy Flight (LF) algorithm and Particle Swarm Optimization (PSO), which use the same initial parameter values. …”
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Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture
Published 2010“…It is shown that the computational complexity of proposed FAST-QR detection algorithm is approximately 48 % lower than the conventional QR decomposition detection algorithm. …”
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
Published 2022“…This study extracted pothole area and volume information from fusion of Digital Elevation Model (DEM) and classified MS image. The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. …”
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19
Color image enhancement of acute leukemia cells in blood microscopic image for leukemia detection sample
Published 2020“…The segmentation algorithm uses saturation S-component based on Hue, Saturation, Intensity (HSI) color model. …”
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A Cryptojacking Detection System With Product Moment Correlation Coefficient (Pmcc) Heatmap Intelligent
Published 2023“…Hence, a feature selection method is necessary to pick the right features. Aside from that, the objective of this project is to investigate cryptojacking in cryptocurrency users' devices, develop a machine learning model to detect cryptojacking, and evaluate the machine learning model's accuracy, true positive rate (TPR), false positive rate (FPR), and precision in detecting cryptojacking. …”
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Undergraduates Project Papers
