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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm
Published 2022“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The SVGPM performance is compared against current methods in developing a prediction model for IDS. In the third experiment, SVGPM is evaluated on wilt disease data set from remote sensing study, to identify wilt diseased trees in high-resolution image. …”
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An intelligent DDoS attack detection tree-based model using Gini index feature selection method
Published 2023“…Our system achieved an overall accuracy of 98, outperforming baseline models that used more advanced algorithms such as Random Forest and XGBoost. …”
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A Stacked Ensemble Deep Learning Approach For Imbalanced Multi-class Water Quality Index Prediction
Published 2024journal::journal article -
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A stylometry approach for blind linguistic steganalysis model against translation-based steganography
Published 2023“…However, accuracy of blind steganalysis algorithms highly depend on the features selected from the input data especially when attacking embedding techniques in TBS. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The locations of landslides were detected accurately by employing two Machine learning classifiers, namely, SVM and RF, decision rule and hierarchal rules sets were developed by applying decision tree (DT) algorithm to provide improved landslide inventory. …”
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Efficient flow-based channel assignment schemes for congestion avoidance in wireless mesh networks
Published 2016“…Several simulation scenarios and analytical model have been presented in order to evaluate and compare the proposed schemes with the existing channel assignment. …”
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Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks
Published 2015“…Simulation results show that the proposed algorithm converges and outperforms a source based tree algorithm. …”
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Proceeding Paper -
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Nano-scale VLSI clock routing module based on useful-skew tree algorithm
Published 2006“…We implemented Useful-Skew Tree (UST) algorithm which is based on the deferred-merge embedding (DME) paradigm, as the clock layout synthesis engine. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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Improved tree routing protocol in zigbee networks
Published 2010“…ImpTR protocol uses an approach to select next hope depending on new algorithm and uses the same tree topology construction for distributing address to all sensor nodes in the network. …”
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15
Delineating mangrove forest zone using spectral reflectance
Published 2020“…By using geospatial techniques and remotely sensed imagery data, the distribution of mangrove tree species associating with anthropogenic matrix can clearly be identified and mapped. …”
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White root disease auto-detection system for rubber trees based on dynamic electro-biochemical latex properties / Mohd Suhaimi Sulaiman
Published 2019“…All of the measurement inputs from the experiment were tested for the data distribution and discrimination between the conditions of the latex using statistical analysis. …”
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Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data
Published 2018“…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. The model is implemented and tested on the CICDDoS2019 dataset using different data dimensionality reduction test scenarios. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. The model is implemented and tested on the CICDDoS2019 dataset using different data dimensionality reduction test scenarios. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. The model is implemented and tested on the CICDDoS2019 dataset using different data dimensionality reduction test scenarios. …”
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