Search Results - (( evolution optimisation based algorithm ) OR ( pattern detection using algorithm ))

Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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A competitive co-evolutionary approach for the nurse scheduling problem by Mohamad Nazri, Maizatul Farhana, Mohd Yusoh, Zeratul Izzah, Basiron, Halizah, Daud, Azlina

“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis by Siti Nur Hidayah, Mazelan

“…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis by Kabir Ahmad, Farzana, Kamaruddin, Siti Sakira, Yusof, Yuhanis, Yusoff, Nooraini

“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff by Mohd Yusoff, Mohd Izhan

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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Moiré Method Based Tilt Sensing System For Landslides Monitoring Using Raspberry PI by Toh, Han Yaung

“…An algorithm to detect the centroid of the moiré fringe pattern was developed. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory by Rusli, Julie Roslita

“…Moreover, most of the memory test algorithm does not have the capability to detect and diagnose NPSF. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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High impedance fault detection and identification based on pattern recognition of phase displacement computation by Ali, Mohd Syukri, Bakar, Ab Halim Abu, Tan, Chia Kwang, Arof, Hamzah, Mokhlis, Hazlie

“…There are two stages in this algorithm. In the first stage, the pattern of the PDC is analyzed to detect the occurrence of an event. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm by Ahmad Fakhri, Ab. Nasir, Ahmad Shahrizan, Abdul Ghani, Muhammad Aizzat, Zakaria, Anwar, P. P. Abdul Majeed, Ahmad Najmuddin, Ibrahim

“…In the empirical experiment by using this algorithm, some region in the image which is supposed to be non-face region is detected as face due to the similarity of human face features. …”
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Animal voice recognition for identification (ID) detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

“…While the voice pattern classification will be done by using DTW algorithm. …”
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Dog voice identification (ID) for detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

“…While the voice pattern classification will be done by using DTW algorithm. …”
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Evaluation of fall detection classification approaches by Kerdegari, Hamideh, Samsudin, Khairulmizam, Ramli, Abdul Rahman, Ghotoorlar, Saeid Mokaram

“…This paper presents the comparison of different machine learning classification algorithms using Waikato Environment for Knowledge Analysis (WEKA) platform for classifying falling patterns from ADL patterns. …”
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Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column by Othman, M. R., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

“…Through the proposed algorithm, various faults could be simulated and detected using the system. …”
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A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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