بدائل البحث:
dose optimization » dog optimization (توسيع البحث), whale optimization (توسيع البحث), level optimization (توسيع البحث)
samples » sample (توسيع البحث)
dose optimization » dog optimization (توسيع البحث), whale optimization (توسيع البحث), level optimization (توسيع البحث)
samples » sample (توسيع البحث)
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1
Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
منشور في 2021"…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …"
احصل على النص الكامل
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2
Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
منشور في 2022"…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …"
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3
Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems
منشور في 2023"…First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …"
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4
Opportunistic Throughput Optimization in Energy Harvesting Dynamic Spectrum Sharing Wireless Networks
منشور في 2024"…Furthermore, we propose two algorithms designed to achieve optimal throughput for each scenario. …"
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5
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6
An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization
منشور في 2022"…First, an efficient feature selection algorithm based on particle swarm optimization (PSO) is proposed. …"
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7
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
منشور في 2022"…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …"
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8
Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks
منشور في 2024"…In a postfault scenario, a copula of processing blocks is implemented to ensure the reliability of the proposed method where high-importance features are incorporated into the TCN-GWO model. The proposed algorithm unlocks scalability and system adaptability to operational variability by adopting numeric imputation and missing-data-tolerant techniques. …"
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9
Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
منشور في 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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10
Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
منشور في 2019احصل على النص الكامل
doctoralThesis -
11
Shuffled Linear Regression with Erroneous Observations
منشور في 2019"…We propose an optimal recursive algorithm that updates the estimate from the underdetermined function that is based on that permutation-invariant constraint. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
conferenceObject -
12
Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging
منشور في 2023احصل على النص الكامل
doctoralThesis -
13
LDSVM: Leukemia Cancer Classification Using Machine Learning
منشور في 2022"…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …"
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14
Just-in-time defect prediction for mobile applications: using shallow or deep learning?
منشور في 2023"…In this research, we evaluate the performance of traditional machine learning algorithms and data sampling techniques for JITDP problems and compare the model performance with the performance of a DL-based prediction model. …"