Search Results - (( gene selection methods algorithm ) OR ( based optimization steam algorithm ))*

Neuro-Fuzzy and Particle Swarm Optimization based Model for the Steam and Cooling sections of a Cogeneration and Cooling Plant by Alemu Lemma, Tamiru, Rangkuti, Chalillullah, Mohd Hashim, Fakhruldin

“…Neuro-fuzzy approach trained by a sequence of optimization algorithms-Particle Swarm Optimization (PSO) followed by Back-Propagation (BP)-is used to develop models for the steam drum pressure, steam drum water level, steam flow rate and chilled water supply temperature. …”
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A combinatory algorithm of univariate and multivariate gene selection by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

“…Gene selection is usually based on univariate or multivariate methods. …”
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Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

“…This leads to the classification accuracy and genes subset size problem. Hence, this study proposed to modify the Firefly Algorithm (FA) along with the Correlation-based Feature Selection (CFS) filter for the gene selection task. …”
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New entropy-based method for gene selection by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

“…Gene selection, based on top ranked genes which individually have high power to discriminate objects, is a traditional method that doesn’t consider the redundancy among the genes. …”
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Gene Selection For Cancer Classification Based On Xgboost Classifier by Teo, Voon Chuan

“…Gene selection is the technique that applied to the gene selection dataset, such as DNA microarray, which is develop to reduce the less informative gene, so that the selected gene is related to the disease diagnosis. …”
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Gene selection for high dimensional data using k-means clustering algorithm and statistical approach by Ahmad, Farzana Kabir, Yusof, Yuhanis, Othman, Nor Hayati

“…Thus, selection of relevant genes is a challenging issue in microarray data analysis and has been a central research focus.This study proposed kmeans clustering algorithm to groups the relevant genes. …”
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Filter-Wrapper Methods For Gene Selection In Cancer Classification by Alomari, Osama Ahmad Suleiman

“…Several hybrid filter-wrapper methods have been proposed to select informative genes. …”
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Using fuzzy association rule mining in cancer classification by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

“…In addition, creating a fuzzy classifier with high performance in classification that uses a subset of significant genes which have been selected by different types of gene selection methods is another goal of this study. …”
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Integrated framework with association analysis for gene selection in microarray data classification by Ong, Huey Fang

“…The proposed gene selection method combined the strength of both filter method and association analysis to identify a set of discriminative and informative genes. …”
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An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes by Mohd Saberi, Mohamad, Sigeru, Omatu, Safaai, Deris, Yoshioka, Michifumi, Afnizanfaizal, Abdullah, Zuwairie, Ibrahim

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Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

“…This reproduction is established in terms of selection, crossover and mutation of reproducing genes. …”
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SYSTEMATIC DESIGN ALGORITHM FOR ENERGY EFFICIENT AND COST EFFECTIVE HYDROGEN PRODUCTION FROM PALM WASTE by INAYAT, ABRAR

“…In the current study, a systematic autonomous algorithm incorporating reaction kinetics model, flowsheet calculations, heat integration analysis and economic evaluation, has been developed to calculate optimum parameters giving minimum hydrogen production cost using optimization strategies. …”
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The importance of data classification using machine learning methods in microarray data by Jaber, Aws Naser, Moorthy, Kohbalan, Machap, Logenthiran, Safaai, Deris

“…One of them is microarrays, which is a type of representation for gene expression that is helpful in diagnosis. To unleash the full potential of microarrays, machine-learning algorithms and gene selection methods can be implemented to facilitate processing on microarrays and to overcome other potential challenges. …”
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Selecting informative genes from leukemia gene expression data using a hybrid approach for cancer classification by Mohamad, Mohd. Saberi, Deris, Safaai, Hashim, Siti Zaiton Mohd.

“…We introduce an improved version of hybrid of genetic algorithm and support vector machine for genes selection and classification. …”
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Pathway-based analysis with Support Vector Machine (SVM-LASSO) for gene selection and classification by Nasrudin, Nurul Athirah, Chan, Weng Howe, Mohamad, Mohd Saberi, Deris, Safaai, Napis, Suhaimi, Kasim, Shahreen

“…Secondly, Support Vector Machine with Least Absolute Shrinkage and Selection Operator algorithm (SVM-LASSO) is proposed, which to find informative genes for each pathway to ensure efficient gene selection and classification in every pathway. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Optimization of stiffened panel fatigue life by using finite element analysis by Mazlan, Shahan

“…The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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Pathway-based analysis with support vector machine (SVM-LASSO) for gene selection and classification by Nurul Athirah, Nasrudin, Chan, Weng Howe, Mohd Saberi, Mohamad, Safaai, Deris, Suhaimi, Napis, Shahreen, Kasim

“…Secondly, Support Vector Machine with Least Absolute Shrinkage and Selection Operator algorithm (SVM-LASSO) is proposed, which to find informative genes for each pathway to ensure efficient gene selection and classification in every pathway. …”
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Reference gene validation for gene expression normalization in canine osteosarcoma: a geNorm algorithm approach by Selvarajah, Gayathri Thevi, Bonestroo, Floor A. S., Timmermans Sprang, Elpetra P. M., Kirpensteijn, Jolle, Mol, Jan A.

“…RESULTS: Tumors with a variety of clinical and pathological characteristics were selected. Gene expression stability and the optimal number of reference genes for gene expression normalization were calculated. …”
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Gene Selection for Cancer Classification Based on XGBoost by Chuan, Teo Voon, Tomal, Md Raihanul Islam, Moorthy, Kohbalan, Howe, Chan Weng

“…This research focuses on improving gene selection for cancer classification using the XGBoost classifier, an efficient open-source implementation of the gradient boosted trees algorithm. …”
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