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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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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.

“…This paper presents an intelligent system to reduce Non Technical Loss (NTL) using hybrid Support Vector Machine (SVM) and Genetic Algorithm (GA). The main motivation for this research is to assist Sabah Electricity Sdn. …”

Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

“…IP-PBX face challenges in detecting and mitigating malicious traffic. In this research, Support Vector Machine (SVM) machine learning detection & prevention algorithm were developed to detect this type of attacks Two other techniques were benchmarked decision tree and Naïve Bayes. …”
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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. This paper proposes a detection model, ant system with support vector machine, which uses ant system, a variation of ant colony optimization, to filter out the redundant and irrelevant features for support vector machine classification algorithm. …”
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Shot boundary detection based on orthogonal polynomial by Abdulhussain, Sadiq H., Ramli, Abd Rahman, Mahmmod, Basheera M., Saripan, Mohd Iqbal, Al-Haddad, Syed Abdul Rahman, Jassim, Wissam A.

“…These moments (smoothed and gradients) are fused to form a feature vector. Finally, the support vector machine is utilized to detect hard transitions. …”
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Dual-tone multifrequency signal detection using support vector machines by Nagi J., Tiong S.K., Yap K.S., Ahmed S.K.

“…The need for efficient detection of Dual-tone Multifrequency (DTMF) tones for developing telecommunication equipment is justifiable. …”

Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine by Fathi Mahdi Elsiddig Haroun, Mr.

“…The SVM algorithm has been used to detect high- and low-density vegetation regions from the extracted ROI. …”

AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm by Salim, Nur Saadah, Saad, Shahadan

“…This research introduces a new approach to enhancing cybersecurity by integrating Support Vector Machine (SVM) algorithms with penetration testing to develop a recommendation system focused on Cross-Site Scripting (XSS) attack detection. …”
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Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve hig... by Harum, Norharyati, Khalil, Mohamad Kchouri, Obeid, Ali, Hazimeh, Hussein

“…Therefore, it is critical to develop a smart fall detection system. Many approaches have been proposed in wearable-based systems. …”
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An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

“…Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. …”
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An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

“…Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. …”
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Vader lexicon and support vector machine algorithm to detect customer sentiment orientation by Vivine Nurcahyawati, ., Zuriani, Mustaffa

“…To accomplish this, a dataset from the Amazon website will be analyzed and classified using the Support Vector Machine algorithm. The objective of this method is to determine the level of customer orientation present within the dataset. …”
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Micro-Crack Detection Of Solar Cells Featuring Adaptive Anisotropic Diffusion Filter And Semi-Supervised Support Vector Learning by Majid, Said Amirul Anwar B Ab Hamid @ Ab

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Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms by Murti M.A., Junior R., Ahmed A.N., Elshafie A.

Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain by Mohamad Zain, Muhammad Asyraf

“…To counter this problem, a system has been proposed to detect the hand gesture using one of the machine learning technique which is Support Vector Machine (SVM) Algorithm. …”
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Improved abnormal detection using self-adaptive social force model for visual surveillance by Wan Nur Azhani, W. Samsudin

“…So, Self-Adaptive SFM is developed in order to estimate a good quality of interaction forces since it is crucial to achieve better abnormal detection, which represents the behavior of the crowd. …”
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Data forensics analysis on biometric images using Benford's law and support vector machine algorithm by Hamid, Alsaadi Hussam Hussein

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Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines by Nagi J., Yap K.S., Tiong S.K., Ahmed S.K., Nagi F.

“…Efficient methods for DTMF signal detection are important for developing telecommunication equipment. …”

Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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