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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…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 by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

“…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 by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…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 by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…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 by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…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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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…Two different models for learning in data sets were proposed based on two different reduction algorithms. The split-condition-merge-reduct algorithm ( SCMR) was performed on three different modules: partitioning the data set vertically into subsets, applying rough set concepts of reduction to each subset, and merging the reducts of all subsets to form the best reduct. …”
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Redesign the 4:2 compressor for partial product reduction by Hussin, R., Ali Yeon, Md Shakaff, Idris, N., Zaliman, Sauli, Ismail, R.C., Kamarudin, A.

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Algorithm for the legal regulation of internet financial crime by Ambaras Khan, Hanna, Ab. Rahman, Suhaimi, Xinxin, Mao

“…Data processing for criminal acts on Internet finance platforms is crucial, with the utilization of random forest algorithms, including Decision tree and Bagging integration algorithms. …”
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Detecting Malware with Classification Machine Learning Techniques by Mohd Yusof, Mohd Azahari, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Shaker Hussain, Hanizan

“…The study assesses the effectiveness of several algorithms, including Naïve Bayes, Support Vector Machine (SVM), KNearest Neighbor (KNN), Decision Tree, Random Forest, and Logistic Regression, through an examination of a publicly accessible dataset featuring both benign files and malware. …”
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Detecting Malware with Classification Machine Learning Techniques by Mohd Yusof, Mohd Azahari, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Shaker Hussain, Hanizan

“…The study assesses the effectiveness of several algorithms, including Naïve Bayes, Support Vector Machine (SVM), KNearest Neighbor (KNN), Decision Tree, Random Forest, and Logistic Regression, through an examination of a publicly accessible dataset featuring both benign files and malware. …”
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Drone-based surveillance of palm tress ecosystems by Mansor, Ya’akob, Baki, Sharudin Omar, Sahwee, Zulhilmy, Mengyue, Cheng, Wu, Yuanyuan

“…Overall, this research contributes to the advancement of oil palm tree health detection systems, providing valuable insights for future developments in agricultural surveillance and monitoring technologies.…”
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Prospects for basal stem rot disease based on soil apparent electrical conductivity in oil palm plantation by Mohd Husin, Ezrin

“…Furthermore, the software was developed by using MATLAB to produce a predicted BSR map in oil palm plantation based on the developed algorithm. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…It ensures that plants receive the necessary nutrients for optimal growth and development.…”
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A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data by Rana, M.M., Rahman, A., Uddin, M., Sarkar, M.R., Shezan, S.A., Ishraque, M.F., Rafin, S.M.S.H., Atef, M.

“…This paper presents a comparative analysis of a categorical variable decision tree algorithm (CVDTA) with the most common peak shaving technique, namely, the general capacity addition technique, to evaluate the peak shaving performance for an IMG system. …”
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Efficient flow-based channel assignment schemes for congestion avoidance in wireless mesh networks by Abdulla Mogaibel, Hassen Abd-Almotaleb

“…In addition, a hybrid interface assignment strategy is developed based on the spanning tree structure of the gateway traffic. …”
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Predicting open space parking vacancies using machine learning by Lee, Wei Jun

“…A custom object detector developed using the YOLOv4 algorithm was used to collect the data for training the machine learning model. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

“…For BrC detection, an efficient and reliable model namely Ensemble BrC Detection Network (EBrC-Net) and three misclassification reduction (McR) algorithms are developed. The proposed EBrC-Net model is based on deep learning (DL) based approach. …”
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