Search Results - (evolution OR solution) ((mining techniques) OR (learning techniques))

Global Trends of Educational Data Mining in Online Learning by Chen, Chwen Jen, Teh, Chee Siong, Dexter Sigan, John

“…Educational data mining (EDM) in online learning involves data mining techniques to analyze data from online environments to gain insights into student behavior, performance, and engagement. …”
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A New Hybrid K-Means Evolving Spiking Neural Network Model Based on Differential Evolution by Abdulrazak Yahya, Saleh, Haza Nuzly, Abdull Hamed, Siti Mariyam, Shamsuddin, Ashraf, Osman Ibrahim

“…Clustering is one of the essential unsupervised learning techniques in Data Mining. In this paper, a new hybrid (K-DESNN) approach to combine differential evolution and K-means evolving spiking neural network model (K-means ESNN) for clustering problems has been proposed. …”
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Review of firewall optimization techniques by Shakirah, Saidin, Mohamad Fadli, Zolkipli

“…Minimizing firewall rules by removing anomalies in the policy proven to be one of the solutions. Firewall performance can also be optimized using data mining technique and optimization based on traffic awareness. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

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Accelerated mine blast algorithm for ANFIS training for solving classification problems by Mohd Salleh, Mohd Najib, Hussain, Kashif

“…Mine Blast Algorithm (MBA) is newly developed metaheuristic technique. …”
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Global trends of educational data mining in online learning by Nie Hui Ling, Chwen Jen Chen, Chee Siong Teh, Dexter Sigan John, Looi Chin Ch’ng, Yoon Fah Lay

“…Educational data mining (EDM) in online learning involves data mining techniques to analyze data from online environments to gain insights into student behavior, performance, and engagement. …”
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Cyberbullying in e-Learning platform: a text mining analytics by Kartiwi, Mira, Gunawan, Teddy Surya

“…This paper also aimed to propose a practical solution to combat cyberbullying in an educational platform, and shed some lights on the potential applications of text mining techniques in educational research.…”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…Many statistical and data mining techniques have been used to predict time series stock market. …”
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Applied data mining approach in ubiquitous world of air transportation by Reza, S.M., Wah, T.Y., Lahsasna, A.

“…This paper is going to use one of successfully used data mining techniques, namely neural network, which is capable of recognizing patterns. …”
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Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

Modeling of Remora Optimization with Deep Learning Enabled Heavy Metal Sorption Efficiency Prediction onto Biochar by Almalawi, A., Khan, A.I., Alqurashi, F., Abushark, Y.B., Alam, M.M., Qaiyum, S.

“…Besides, deep belief network (DBN) model was employed for prediction and the efficiency of the DBN model is optimally adjusted with utilize of RO technique. The experimental validation of the RODL-HMSEP technique ensured the promising performance of the RODL-HMSEP technique on the prediction of sorption efficiency onto biochar over other methods The experimental validation of the RODL-HMSEP technique ensured the promising performance of the RODL-HMSEP technique on the prediction of sorption efficiency onto biochar over other methods. …”
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Modeling of Remora Optimization with Deep Learning Enabled Heavy Metal Sorption Efficiency Prediction onto Biochar by Almalawi, A., Khan, A.I., Alqurashi, F., Abushark, Y.B., Alam, M.M., Qaiyum, S.

“…Besides, deep belief network (DBN) model was employed for prediction and the efficiency of the DBN model is optimally adjusted with utilize of RO technique. The experimental validation of the RODL-HMSEP technique ensured the promising performance of the RODL-HMSEP technique on the prediction of sorption efficiency onto biochar over other methods The experimental validation of the RODL-HMSEP technique ensured the promising performance of the RODL-HMSEP technique on the prediction of sorption efficiency onto biochar over other methods. …”
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Cyberbullying in e-learning platform: an exploratory study through text mining analytics by Kartiwi, Mira, Gunawan, Teddy Surya

“…This paper also aimed to propose a practical solution to combat cyberbullying in an educational platform, and shed some lights on the potential applications of text mining techniques in educational research.…”
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Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman by Hamdan, Muhammad Halim, Abdul-Rahman, Shuzlina

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Accelerator-based human activity recognition using voting technique with NBTree and MLP classifiers by Azmi M.S.M., Sulaiman M.N.

“…In this study, an accelerator-based activity recognition model using voting technique was proposed. Two machine learning classifiers, Naive Bayes Tree (NBTree) and Multilayer Perceptron (MLP), were used as ensemble classifiers in the voting technique. …”

Predictive crime mapping model using association rule mining for crime analysis by Asmai, S. A., Rosmiza Wahida, Abdullah, Sabrina, Ahmad

“…After training the data, the rules of relationship between attributes were generated. Here, the technique of association rule mining is being used. …”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif by Sa’dan, Siti ‘Aisyah, Jantan, Hamidah, Abdul Latif, Mohd Hanapi

“…Recently, among the challenges of Human Resource professionals has been managing an organization talent which involves a lot of managerial or human decisions, which sometimes are very uncertain and difficult. Prediction in data mining is among the popular machine learning techniques as a part of intelligent techniques, for example, Bayesian methods, neural network, support vector machine, association rule mining, k-nearest-neighbor, rough sets and fuzzy logic. …”
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Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability by Romli, Nurul Atiqah, Zulkepli, Nur Fariha Syaqina, Kasihmuddin, Mohd Shareduwan Mohd, Zamri, Nur Ezlin, Rusdi, Nur 'Afifah, Manoharam, Gaeithry, Mansor, Mohd. Asyraf, Jamaludin, Siti Zulaikha Mohd, Malik, Amierah Abdul

“…Additionally, unsupervised learning techniques such as Topological Data Analysis were proposed to ensure the reliability of the selected attributes in the model. …”
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Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. The evolution of authoritative immunofingerprint mining technology is exerting a growing influence on comprehensive cancer diagnosis biology. …”
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Approaches to Multi-Objective Feature Selection: A Systematic Literature Review by Al-Tashi, Q., Abdulkadir, S.J., Rais, H.M., Mirjalili, S., Alhussian, H.

“…Feature selection has gained much consideration from scholars working in the domain of machine learning and data mining in recent years. Feature selection is a popular problem in Machine learning with the goal of finding optimal features with increase accuracy. …”
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