Search Results - (( pattern detection method algorithm ) OR ( _ integration method algorithm ))

Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…This creates the jamming detection and classification parameters. The second stage is detecting jammers by integrating both lower layers by developing Integrated Combined Layer Algorithm (ICLA). …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…However, these algorithms often fall short in consistently detecting and classifying network intrusions, particularly when distinctions between classes are subtle or when facing evolving attack patterns. …”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

“…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification by Kamaruddin, B., Zabiri, H., Mohd Amiruddin, A.A.A., Teh, W.K., Ramasamy, M., Jeremiah, S.S.

“…In this paper, a â��butterflyâ�� shape derived from the manipulation of the standard PV and OP data, which is more robust towards different loop dynamics, is developed for stiction detection. This simple model-free butterfly shape-based detection (BSD) method uses Stenman's one parameter stiction model, which results in a distinctive â��butterflyâ�� pattern in the presence of stiction. …”
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Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm by Mohamed, M. E, Samir, B. B., Azween, Abdullah

“…The growth of intelligent intrusion and diverse attack techniques in network systems stimulate computer scientists and mathematical researchers to challenge the dangers of intelligent attacks. In this work, we integrate artificial immune algorithm with non-linear classification of pattern recognition and machine learning methods to solve the problem of intrusion detection in network systems. …”
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Can recognition using LABVIEW / Jamilah Othman by Othman, Jamilah

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Concrete surface inspection by using unmanned aerial vehicle (UAV) and deep learning algorithms YOLOv7 / Saffa Nasuha Rusdinadi by Rusdinadi, Saffa Nasuha

“…This research aims to improve the detection and analysis of cracks on concrete surfaces by utilizing UAVs and yolo algorithms. …”
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Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim by Mohamad Kasim, Adibah I’zzah

“…The increasing complexity of modern power systems necessitates advanced methods for detecting and classifying power quality disturbances (PQDs), which impact system reliability and equipment performance. …”
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Analysis of banana plant health using machine learning techniques by Thiagarajan, Joshva Devadas, Kulkarni, Siddharaj Vitthal, Jadhav, Shreyas Anil, Waghe, Ayush Ashish, Raja, S.P., Rajagopal, Sivakumar, Poddar, Harshit, Subramaniam, Shamala

“…Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. …”
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Seismic attribute feasibility study for fault and fracture analysis and integration with spectral decomposition: Application in Sarawak basin by Hamidi, R., Ghosh, D.

“…Next, spectral analysis, as a tool to identify events with different frequency content is used which can detect the patterns related to faulting and fracturing of the subsurface layers. …”
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Concrete surface inspection by using Unmanned Aerial Vehicle (UAVs) and deep learning algorithms Yolov7 by Rusdinaidi, Saffa Nasuha, Hashim, Khairil Afendy, Ahmad Dahlan, Zaki

“…This research aims to evaluate the detection and analysis of cracks on concrete surfaces by utilizing Uavs and Yolo algorithms. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

“…A statistical test was used to demonstrate the efficiency of the proposed algorithm over the compared methods. The GLS is 7.8 and 5.5 times faster than A* and LS, respectively, generating a path 1.2 and 1.5 times shorter than A* and LS. …”
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Scrutinized System Calls Information Using J48 And Jrip For Malware Behaviour Detection by Abdollah, Mohd Faizal, S. M. M Yassin, S. M. Warusia Mohamed, Mohd Saudi, Nur Hidayah

“…This integrated classifier algorithm applied to analyse, classify and generate rules of the pattern and program behaviour of system call information in which, the legal and illegal behaviours could identify. …”
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Accelerating FPGA-surf feature detection module by memory access reduction by Mohd. Yamani Idna, Idris, Nor Bakiah, Abd. Warif, Hamzah, Arof, Noorzaily, Mohamed Noor, Ainuddin Wahid, Abdul Wahab, Zaidi, Razak

“…We also found that the SURF algorithm memory access has redundant repeating pattern that can be reduced. …”
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Coordinated Malware Eradication And Remediation Project (CMERP) by Abdollah, Mohd Faizal, S.M.M Yassin, S.M.Warusia Mohamed, Mas’ud, Mohd Zaki, Selamat, Siti Rahayu, Yusof, Robiah, Ahmad, Rabiah, Shahrin @ Sahibuddin, Shahrin

“…This integrated classifier algorithm applied to analyse, classify and generate rules of the pattern and program behaviour of system call information in which the legal and illegal behaviours could identified. …”
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An Analysis Of System Calls Using J48 And JRip For Malware Detection by Abdollah, Mohd Faizal, Abdullah, Raihana Syahirah, S. M. M Yassin, S. M. Warusia Mohamed, Selamat, Siti Rahayu, Mohd Saudi, Nur Hidayah

“…The evolution of malware possesses serious threat ever since the concept of malware took root in the technology industry.The malicious software which is specifically designed to disrupt,damage,or gain authorized access to a computer system has made a lot of researchers try to develop a new and better technique to detect malware but it is still inaccurate in distinguishing the malware activities and ineffective.To solve the problem,this paper proposed the integrated machine learning methods consist of J48 and JRip in detecting the malware accurately.The integrated classifier algorithm applied to examine,classify and generate rules of the pattern and program behaviour of system call information.The outcome then revealed the integrated classifier of J48 and JRip outperforming the other classifier with 100% detection of attack rate. …”
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An Analysis Of System Calls Using J48 And JRip For Malware Detection by Abdollah, Mohd Faizal, Abdullah, Raihana Syahirah, S.M.M Yassin, S.M. Warusia Mohamed, Selamat, Siti Rahayu, Mohd Saudi, Nur Hidayah

“…To solve the problem, this paper proposed the integrated machine learning methods consist of J48 and JRip in detecting the malware accurately. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…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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Application of terrain analysis to the mapping and spatial pattern analysis of subsurface geological fractures of Kuala Lumpur limestone bedrock, Malaysia. by Mansor, Shattri, Mahmud, Ahmad Rodzi, Kim Huat, Bujang, Elmahdy, Samy Ismail

“…The second is an automatic detection method using a topographical fabric algorithm that uses a DEM to create a map of ridges, which represent the footwalls of geological fractures, and valleys (channels), which reflect geological fracture zones. …”
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Neuro fuzzy classification and detection technique for bioinformatics problems by Othman, Mohd. Fauzi, Moh, Thomas Shan Yau

“…It is very important to identify new integration of classification or clustering algorithm especially in neuro fuzzy domain as compared to conventional or traditional method. …”
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