Search Results - (( java application interface algorithm ) OR ( subset detection technique algorithm ))

SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…Intrusion detection systems are developed on the bases of two different detection techniques, signature-based technique and anomaly-based technique. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…ITLBO with supervised machine learning (ML) technique was used for feature subset selection (FSS). …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Further, the shortage of efficient feature selection techniques gives rise to low accuracy in anomaly detection. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Recently, various techniques based on different algorithms have been developed. …”
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Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

“…This article presents the development of an improved intrusion detection method for binary classification. In the proposed IDS, Rao Optimization Algorithm, Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) were combined with NTLBO algorithm with supervised ML techniques (for feature subset selection (FSS). …”
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by AHMAD, IFTIKHAR

“…Therefore, accurate detection of network attack is imperative. A variety of intrusion detection approaches are available but the main problem is their performance, which can be enhanced by increasing the detection rates and reducing false positives. …”
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Algorithm of face recognition by principal component analysis by Al-Khateeb, Khalid A. Saeed, Yeop Johari, Jaiz Anuar

“…The method proved to be simple and effective. The simplified algorithm and techniques expected the process without seriously compromising the accuracy.…”
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A Naïve-Bayes classifier for damage detection in engineering materials by Addin, O., Salit, Mohd Sapuan, Mahdi Ahmad Saad, Elsadig, Othman, Mohamed

“…The Naïve-Bayes classifier and the proposed feature subset selection algorithm have been shown as efficient techniques for damage detection in engineering materials. …”
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by Iftikhar , Ahmad, Azween, Abdullah

“…Therefore, accurate detection of network attack is imperative. A variety of intrusion detection approaches are available but the main problem is their performance, which can be enhanced by increasing the detection rates and reducing false positives. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

“…Traditional intrusion detection techniques have had trouble dealing with dynamic environments. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

“…The ant colony optimisation (ACO) algorithm have been used to select feature subset. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.

A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS by Thayaaleni, Rajandran

“…The project proposed a dynamic analysis technique in Android malware detection. The objectives of the project are to investigate the Android malware using dynamic analysis technique and to enhance the accuracy of malware detection. …”
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Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

“…In addition, the system also utilises JavaFx and jFugue for its graphical user interface and music programming respectively. …”
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Adaptive feature selection for denial of services (DoS) attack by Yusof, Ahmad Riza'ain, Udzir, Nur Izura, Selamat, Ali, Hamdan, Hazlina, Abdullah @ Selimun, Mohd Taufik

“…In this paper, we propose combining two techniques in feature selection algorithm, namely consistency subset evaluation (CSE) and DDoS characteristic features (DCF) to identify and select the most important and relevant features related DDoS attacks. …”
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A new hybrid ensemble feature selection framework for machine learning-based phishing detection system by Chiew, Kang Leng, Tan, Choon Lin, Wong, KokSheik, Yong, Kelvin S.C., Tiong, Wei King

“…In the first phase of HEFS, a novel Cumulative Distribution Function gradient (CDF-g) algorithm is exploited to produce primary feature subsets, which are then fed into a data perturbation ensemble to yield secondary feature subsets. …”
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Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

“…In addition the implementation is done by algorithm using Java’s programming language, executed through an application developed in the Android operating system. …”

Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification by Saw, Yee Ching

“…The proposed feature selection approach has a simple algorithmic framework and makes use of the existing feature selection techniques to cater different variety of data issues, namely Ensemble Filter-Embedded Feature Ranking Approach (FEFR). …”
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Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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