Search Results - (( java application bees algorithm ) OR ( framework _ selection algorithm ))

A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis methods by Abdulkareem, Karrar Hameed, Arbaiy, Nureize, Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., M. Salih, Mahmood

“…According to previous studies, a standardisation and selection framework for real-time image dehazing algorithms based on multi-foggy scenes is not yet available. …”
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A new multiperspective framework for standardization and benchmarking of image dehazing algorithms by Abdulkareem, Karrar Hameed

“…To evaluate the proposed framework, two main approaches were applied. On the one hand, a standard dataset was tested on the selected criteria and image dehazing algorithms to select the best algorithm. …”
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Genetic algorithm based ensemble framework for sentiment analysis by Lai, Po Hung

“…Since there are many methods involved in each task of the multilayered ensemble, genetic algorithm is added to optimize the overall framework in order to select the optimal combinations of methods in each layer that can produce satisfactory results. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

“…A new case is retained in the case base for future retrievals. A framework user is allowed to select from a list of features provided by the framework that he or she is interested in learning, and the system will give an example of application related to the selected features. …”

Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

“…In this paper, we incorporate multiview learning into semisupervised multitask feature selection framework and present a novel semisupervised multiview multitask feature selection framework. …”
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A hybrid feature selection framework for predicting students performance by Zaffar, M., Hashmani, M.A., Habib, R., Quraishi, K.S., Irfan, M., Alqhtani, S., Hamdi, M.

“…The validated results confirm that the proposed hybrid feature selection framework performs better than the existing hybrid feature selection framework, existing feature selection algorithms in terms of accuracy, f-measure, recall, and precision. …”
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A novel Multi-perspective benchmarking framework for selecting image dehazing intelligent algorithms based on BWM and group VIKOR techniques by Abdulkareem, Karrar Hameed

“…A novel Multi-perspective benchmarking framework for selecting image dehazing intelligent algorithms based on BWM and group VIKOR techniques by Abdulkareem, Karrar Hameed …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The experimental results show that the proposed feature selection framework performed better when compared to other state-of-the-art feature selection algorithms. …”
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Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

“…For the purpose of this study, ten classification algorithms have been selected. The selection aims at achieving a balance between established classification algorithms used in software defect prediction. …”
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A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis methods by Abdulkareem, Karrar Hameed

“…A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis methods by Abdulkareem, Karrar Hameed …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…In order to fill this gap, this article proposes a novel framework for comparing various variants of variable length-searching meta-heuristic algorithms in the application of feature selection. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…In order to fill this gap, this article proposes a novel framework for comparing various variants of variable length-searching meta-heuristic algorithms in the application of feature selection. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Sara, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…In order to fill this gap, this article proposes a novel framework for comparing various variants of variable length-searching meta-heuristic algorithms in the application of feature selection. …”
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A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis methods by Al-Juboori, Aos A. Z.,Ansaef

“…A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis methods by Al-Juboori, Aos A. …”
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A Simulation Framework For Performance Evaluation Of Network Selection Algorithms In Heterogeneous Wireless Networks. by Hasib, Abdul, O. Fapojuwo, Abraham

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An improved diabetes risk prediction framework : An Indonesian case study by Sutanto, Daniel Hartono

“…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification by Hossin, M., Mohd Suria, F.

“…Most previous works on Bacterial Foraging Optimization Algorithm (BFOA) for data classification were integrated BFOA as a feature selection algorithm and parameters optimizer for other classifiers. …”
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A new intelligent multilayer framework for insider threat detection by Ahmad, Rabiah, Al-Mhiqani, Mohammed Nasser Ahmed, Zainal Abidin, Zaheera, Abdulkareem, Karrar Hameed, Mohammed, Mazin Abed, Gupta, Deepak K., Shankar K.

“…The first layer of the framework is used for selecting the best insider threat detection classification model among many based on the multi-criteria decision making techniques. …”
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A novel framework for identifying twitter spam data using machine learning algorithms by Maziku, Susana Boniphace, Abdul Rahiman, Amir Rizaan, Muhammed, Abdullah, Abdullah @ Selimun, Mohd Taufik

“…This study introduces a novel framework for identifying Twitter spam data based on machine learning algorithms. …”
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Immune-based technique for undergraduate programmes recommendation / Muhammad Azrill Mohd Zamri by Mohd Zamri, Muhammad Azrill

“…The proposed technique is obtained by combining artificial immune network (aiNET) and clonal selection algorithm (CLONALG). Myers-Briggs Type Indicator is also used as a psychological assessment mechanism in the selection process to enhance the accuracy of the proposed technique. …”
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