Search Results - (( based optimization mining algorithm ) OR ( based optimization means algorithm ))

Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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Discovering optimal clusters using firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…Existing conventional clustering techniques require a pre-determined number of clusters, unluckily; missing information about real world problem makes it a hard challenge.A new orientation in data clustering is to automatically cluster a given set of items by identifying the appropriate number of clusters and the optimal centre for each cluster.In this paper, we present the WFA_selection algorithm that originates from weight-based firefly algorithm.The newly proposed WFA_selection merges selected clusters in order to produce a better quality of clusters.Experiments utilising the WFA and WFA_selection algorithms were conducted on the 20Newsgroups and Reuters-21578 benchmark dataset and the output were compared against bisect K-means and general stochastic clustering method (GSCM).Results demonstrate that the WFA_selection generates a more robust and compact clusters as compared to the WFA, bisect K-means and GSCM.…”
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Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…Hence, it is required to develop effective imbalanced LR-based methods to be widely used in data mining applications. …”
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Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

“…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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Clustering of rainfall data using k-means algorithm by Mohd Sham, Mohamad, Yuhani, Yusof, Ku Muhammad Na’im, Ku Khalif, Mohd Khairul Bazli, Mohd Aziz

“…K-Means algorithm is used to obtain optimal rainfall clusters. …”
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DEVELOPMENT OF MULTI-VERSE OPTIMIZER IN ARTIFICIAL NEURAL NETWORK FOR ENHANCING THE IMPUTATION ACCURACY OF DAILY RAINFALL OBSERVATIONS by Lai, Wai Yan, Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman

“…MVOFNN is compared against the conventional Levenberg-Marquardt Feedforward Neural Network (LMFNN) and a promising data mining-based imputation approach, the Regularized Expectation Maximization (RegEM) algorithm, to assess its reliability and feasibility in reconstructing missing daily rainfall data. …”
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Simple quantum circuit for pattern recognition based on nearest mean classifier by Mahmoud Ahmed, Gharib Subhi, Messikh Azeddine, Azeddine

“…Lett. 114, 140504 (2015)] which uses quantum matrix inverse algorithm to find optimal hyperplane that separated two different classes. …”
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Fireflyclust: an automated hierarchical text clustering approach by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…Text clustering is one of the text mining tasks that is employed in search engines. Discovering the optimal number of clusters for a dataset or repository is a challenging 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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Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach by Waidah Ismail, Ismail Ahmed Al-Qasem Al-Hadi, Crina Grosan, Rimuljo Hendradi

Evolutionary-based feature construction with substitution for data summarization using DARA by Sia, Florence, Alfred, Rayner

“…This paper proposes an evolutionary-based feature construction approach namely Fixed-Length Feature Construction with Substitution (FLFCWS) to address the problem by means of optimizing the feature construction for relational data summarization. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

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Artificial neural network approach for electric load forecasting in power distribution company / Hambali M. A ... [et al.] by M. A., Hambali, Y. K, Saheed, M. D, Gbolagade, M, Gaddafi

“…Researchers then performed data preprocessing on the data. Afterwards, data mining algorithms were applied in order to forecast electric load. …”
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Tree-based contrast subspace mining method by Florence Sia Fui Sze

“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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A dynamic eLearning prediction modelbased on incomplete activities of eLearning system by Chayanukro, Songsakda

“…Hence, this study demonstrates that using data from incomplete activities of eLearning systems provides an appropriate means for predictable learning outcomes. The prediction model contributes to an optimal number of classes and data set where two classes received the highest accuracy ratio. …”
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Role Minimization As An Optimization Metric In Role Mining Algorithms : A Literature Review by Ahmad, Rabiah, Abd Hamid, Nazirah, Selamat, Siti Rahayu

“…A recent access control model that could accommodate a dynamic structure such as cloud computing can be recognized as role based access control and the role management process of this access control can be identified as role mining.The current trend in role based access control is the role mining problem that can be described as the difficulty to uncover an optimum set of roles from the userpermission assignment.To solve this problem,the researchers have proposed role mining algorithms to produce role set and among the existing algorithms there is an intrinsic topic of the common perception to evaluate the goodness of the generated role set.Eventually,the value of the identified roles could be measured by the preferred metric of optimality namely the number of roles,sizes of userassignment and permission-assignment and Weighted Structural Complexity.Until now, there is some disagreement on the optimization metric but notably many researchers have agreed on the minimization of the number of roles as a solid metric.This paper discusses an overview of the current state-of-the-art on the recent role mining algorithms that focus on role minimization as an optimization metric to evaluate the goodness of the identified roles. …”
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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

“…Several conventional adaptive distance relay (ADR) and computational based intelligent modifications presented to solve the impending compromise by using faulted line voltage and current parameters for the various protection relay controller modification, optimizing synchronized measurement to block or limit the fault current penetration into the grid. …”
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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength by Hussain Talpur, Kashif

“…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
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Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

“…The proposed algorithm in the retrieval phase showed optimal performance as compared to the baseline algorithms. …”
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