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

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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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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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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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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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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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

“…Data reduction is an essential task in the data preparation phase of knowledge discovery and data mining (KDD). The reduction method contains two techniques, namely features reduction and data reduction which are commonly applied to a classification problem. …”
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Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Analysis of traffic accidents using association rules mining technique / Abdullah Murshid Abdul Rahim by Abdul Rahim, Abdullah Murshid

“…Analysis of traffic accidents using data mining techniques is a project to identify the traffic accident pattern analysis using data mining techniques. …”
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COVID-19 and global supply chain risks mitigation: Systematic review using a scientometric technique by Fernando, Yudi, Mohammed Hammam, Mohammed Al-Madani, Muhammad Shabir, Shaharudin

“…Multiple scientometric techniques (e.g. bibliometric, machine learning and social network analysis) were used to analyse the Lens.org, Web of Science and Scopus databases’ global supply chain risk mitigation data. …”
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Analyzing course affecting the results of inferential statistics students in UiTM Seremban Campus using association rule mining / Dayang Mas Rafisha Awang Raffi, Nur Asyikin Mohd M... by Awang Raffi, Dayang Mas Rafisha, Mohd Mustafa, Nur Asyikin, Sazali, Nursyaza Nisa

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A review on optimization of least squares support vector machine for time series forecasting by Yusof, Yuhanis, Mustaffa, Zuriani

“…This paper presents a review on techniques used to optimize the parameters based on two main classes; Evolutionary Computation and Cross Validation.…”
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