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Classification of students' performance in computer programming course according to learning style
Published 2024Conference Paper -
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Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin
Published 2006“…The methods that wilt be applied are conventional statistical methods Markowitz Optimization as well as evolutionary programming (EP) utilizing genetic algorithms. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Uncovering patterns in online database usage at UiTM Negeri Sembilan: a data mining approach/ Mohd Aizat Abd Halim and Safawi Abdul Rahman
Published 2024“…This study investigates online database usage patterns at Universiti Teknologi MARA (UiTM) Negeri Sembilan through a data mining approach, specifically utilizing association rule mining and the Apriori algorithm. …”
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Classification of Students' Performance in Computer Programming Course According to Learning Style
Published 2024Proceedings Paper -
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Towards a better feature subset selection approach
Published 2010“…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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Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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Thesis -
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