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3D silhouette rendering algorithms using vectorisation technique from Kedah topography map by Che Mat, Ruzinoor, Nordin, Norani

“…The vectorisation software has been used for producing these data. …”
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A DNA-dynamic permutation-diffusion algorithm for image encryption using scaling chaotification models and advanced DNA operations by Alkawsi, Gamal, Khairullah, Mustafa Kamil, Baharuddin, Mohd Zafri, Thabit, Reema, Alomari, Mohammad Ahmed, A. Saif, Faten

“…To evaluate the proposed algorithm, extensive experiments have been conducted, and results have been compared with the latest encryption algorithms. …”
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Data driven hybrid evolutionary analytical approach for multi objective location allocation decisions: Automotive green supply chain empirical evidence by Doolun, Ian Shivraj, Ponnambalam, S. G., Subramanian, Nachiappan, Kanagaraj, G.

“…Five variants of the hybrid algorithm are evaluated in addition to comparing the performance with the existing Multi-Objective Hybrid Particle Swarm Optimization (MOHPSO) algorithm. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

“…Advancing multi-objective optimization techniques for cancer treatment strategies, the study strategically incorporates Swarm Intelligence (SI) and Evolutionary Algorithms (EA). …”
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An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

“…The Knowledge Discovery in Databases (KDD) process was followed as a formal data mining methodology where 1000 AI conference papers were carefully collected, pre-processed and transformed to numerical representations through TF-IDF vectorisation. A randomised stratified 5- fold cross validation was then applied on several data mining algorithms and evaluated using the F-measure as a metric. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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