765   Artículos

 
en línea
Marko Ðurasevic, Domagoj Jakobovic, Stjepan Picek and Luca Mariot    
The automated design of dispatching rules (DRs) with genetic programming (GP) has become an important research direction in recent years. One of the most important decisions in applying GP to generate DRs is determining the features of the scheduling pro... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Bao She, Jiating Hu, Linsheng Huang, Mengqi Zhu and Qishuo Yin    
To grasp the spatial distribution of soybean planting areas in time is the prerequisite for the work of growth monitoring, crop damage assessment and yield estimation. The research on remote sensing identification of soybean conducted in China mainly foc... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Yujuan Cao, Jianguo Dai, Guoshun Zhang, Minghui Xia and Zhitan Jiang    
This paper combines feature selection with machine learning algorithms to achieve object-oriented classification of crops in Gaofen-6 remote sensing images. The study provides technical support and methodological references for research on regional monit... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Wenfeng Li, Jiao Pan, Wenyi Peng, Yingzhi Li and Chao Li    
Garlic (Allium sativum) is an important economic crop in China. In terms of using remote sensing technology to identify it, there is still room for improvement, and the high-precision classification of garlic has become an important issue. However, to th... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Iqbal Muhammad Zubair, Yung-Seop Lee and Byunghoon Kim    
The selection of group features is a critical aspect in reducing model complexity by choosing the most essential group features, while eliminating the less significant ones. The existing group feature selection methods select a set of important group fea... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Yugen Yi, Haoming Zhang, Ningyi Zhang, Wei Zhou, Xiaomei Huang, Gengsheng Xie and Caixia Zheng    
As the feature dimension of data continues to expand, the task of selecting an optimal subset of features from a pool of limited labeled data and extensive unlabeled data becomes more and more challenging. In recent years, some semi-supervised feature se... ver más
Revista: Information    Formato: Electrónico

 
en línea
Mazen Gazzan and Frederick T. Sheldon    
Ransomware attacks have emerged as a significant threat to critical data and systems, extending beyond traditional computers to mobile and IoT/Cyber?Physical Systems. This study addresses the need to detect early ransomware behavior when only limited dat... ver más
Revista: Information    Formato: Electrónico

 
en línea
Chinyang Henry Tseng, Woei-Jiunn Tsaur and Yueh-Mao Shen    
In detecting large-scale attacks, deep neural networks (DNNs) are an effective approach based on high-quality training data samples. Feature selection and feature extraction are the primary approaches for data quality enhancement for high-accuracy intrus... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Shurong Peng, Lijuan Guo, Yuanshu Li, Haoyu Huang, Jiayi Peng and Xiaoxu Liu    
The allocation of biogas between power generation and heat supply in traditional kitchen waste power generation system is unreasonable; for this reason, a biogas prediction method based on feature selection and heterogeneous model integration learning is... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Vera Afreixo, Ana Helena Tavares, Vera Enes, Miguel Pinheiro, Leonor Rodrigues and Gabriela Moura    
In this work, we aimed to establish a stable and accurate procedure with which to perform feature selection in datasets with a much higher number of predictors than individuals, as in genome-wide association studies. Due to the instability of feature sel... ver más
Revista: Applied Sciences    Formato: Electrónico

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