Search Results - (( java evolution optimization algorithm ) OR ( opening classification mining algorithm ))

Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…The aim of this evolution is to reflect the unseen time overhead incurred by optimal real-time algorithm, represented by LRE-TL, which might hinder the claimed optimality of such algorithms when they are practically implemented. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…This research opens a wide range of future work to be considered, which includes applying the proposed method in other areas such as web mining, text mining or multimedia mining; and extending the proposed approach to work in parallel computing in data mining.…”
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Framework for mining XML format business process log data by Ang, Jin Sheng

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Data mining and analysis for predicting electrical energy consumption by Khudhair I.Y., Dhahi S.H., Alwan O.F., Jaaz Z.A.

Data mining of protein sequences with amino acid position-based feature encoding technique by Iqbal, M.J., Faye, I., Md Said, A., Samir, B.B.

“…The accurate classification of protein sequences into family/superfamily based on the primary sequence is a very complex and open problem. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

Activity recognition based on accelerometer sensor using combinational classifiers by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran

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Activity Recognition Based On Accelerometer Sensor Using Combinational Classifiers by Muhammad Noorazlan Shah, Zainuddin, Md Nasir, Sulaiman, Norwati, Mustapha, Thinagaran, Perumal

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A Rough Set-Based Approach for Identifying and Replacing Missing Concepts in Incomplete Sentences in Computer Domain Texts by Nur Faiqah ‘Aqilah binti Fuaad

An enhanced android botnet detection approach using feature refinement by Anwar, Shahid

“…The experimental and statistical tests show that 97.28% accuracy achieved by Random Forest machine classifier, it performs well as compared to other classification algorithms. Based on the test results, various open research issues which need to be addressed in future studies are highlighted.…”
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