Search Results - (( java implication based algorithm ) OR ( learning operation mining algorithm ))

Rough-Set-and-Genetic-Algorithm based data mining and Rule Quality Measure to hypothesize distance protective relay operation characteristics from relay event report by Othman, Mohammad Lutfi, Aris, Ishak, Othman, Mohammad Ridzal, Osman, Harussaleh

“…Firstly, the data mining approach of the integrated-Rough-Set-and-Genetic-Algorithm is used to discover the relay CD-decision algorithm. …”
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Algorithm comparison for data mining classification: assessing bank customer credit scoring default risk by Elaf Adel Abbas, Nisreen Abbas Hussein

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Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure by Othman, Mohamad Lutfi

“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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Knowledge discovery in distance relay event report: a comparative data-mining strategy of rough set theory with decision tree by Othman, Mohammad Lutfi, Aris, Ishak, Abdullah, Senan Mahmood, Ali, Md. Liakot, Othman, Mohammad Ridzal

“…This paper addresses these issues by intelligently divulging the knowledge hidden in the relay recorded event report using a data-mining strategy based on rough set theory and a rule-quality measure under supervised learning to discover the relay decision algorithm and association rule. …”
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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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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

“…This analysis' performance was evaluated using overall accuracy, F1, precision and the receiver operating characteristic curve metric. All of these steps were conducted using Orange data mining software. …”
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A Machine Learning Classification Application to Identify Inefficient Novice Programmers by Khan I., Al-Mamari A., Al-Abdulsalam B., Al-Abdulsalam F., Al-Khansuri M., Iqbal Malik S., Ahmad A.R.

An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

“…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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Data Mining On Machine Breakdowns And Effectiveness Of Scheduled Maintenance by Tan, Su Sze

“…Last but not least, some of the complex data mining tasks are not able to perform because of the limited algorithms and machine learning in Orange software.…”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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A dynamic eLearning prediction modelbased on incomplete activities of eLearning system by Chayanukro, Songsakda

“…Six data mining algorithms were used in evaluating the model. …”
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Evolving fuzzy grammar for crime texts categorization by Mohd Sharef, Nurfadhlina, Martin, Trevor

“…The fuzzy notion is used because the grammar matching, parsing and derivation involve uncertainty. Fuzzy union operator is also used to combine and transform individual text fragment grammars into more general representations of the learned text fragments. …”
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman by Muhammad Habib , Ur Rehman

“…The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

“…Preventing ACL injury is challenging due to their multifactorial nature. Machine learning-based data mining techniques have shown significant potential in identifying risk factors associated with ACL injury. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

“…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…Results have shown that integrated Cuckoo search and induced SVM learning algorithm produced the best-selected feature subset with 99% coefficient of determination, lowest RMSE and MAE of 0.081 and 0.0132 respectively.…”
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Forecasting utility management in UiTMCTKKT using predictive analytics / Nur Sufiah Muhammad Taufik by Muhammad Taufik, Nur Sufiah

“…Future iterations could also improve the system using real-time monitoring and machine-learning based predictive algorithms.…”
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An enhanced android botnet detection approach using feature refinement by Anwar, Shahid

“…That adopts machine learning techniques to classify botware and benign applications. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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