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141
UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…To overcome these challenges, a new FS algorithm named Uniform-solution-driven Binary Feature Selection (UniBFS) has been developed in this study. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
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doctoralThesis -
145
Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
Published 2003“…A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. …”
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146
A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…Design/methodology/approach In the proposed approach, the parameter tuning process is performed on all parameters of genetic algorithm (GA), and the finest coefficients with minimum errors are identified. …”
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149
Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN)
Published 2020“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”
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KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…The proposed technique called K-Nearest Neighbor OveRsampling approach (KNNOR) performs a three step process to identify the critical and safe areas for augmentation and generate synthetic data points of the minority class. …”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…The challenge now is to develop fast and accurate computational methods to analyze this huge amount of data. …”
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155
Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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A novel encryption algorithm using multiple semifield S-boxes based on permutation of symmetric group
Published 2023“…The presented algorithm is mainly based on the Shannon idea of substitution–permutation network where the process of substitution is performed by the proposed S<sub>8</sub> semifield substitution boxes and permutation operation is performed by the binary cyclic shift of substitution box transformed data. …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
Published 2022“…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. However, these schemes have limitations like slow convergence and longer training time. …”
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Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare
Published 2007“…With all the preventive methods, malicious users still find new methods that overcome the system security, and access and modify the sensitive information. To make the process of damage assessment and recovery fast and efficient and in order not to scan the whole log, researchers have proposed different methods for segmenting the log, and accordingly presented different damage assessment and recovery algorithms. …”
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