Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …

对近年来聚类算法的研究现状与新进展进行归纳总结. 一方面对近年来提出的较有代表性的聚类
算法, 从算法思想, 关键技术和优缺点等方面进行分析概括; 另一方面选择一些典型的聚类算法和 …

K-均值(K-Means) 算法是聚类分析中一种基于划分的算法, 同时也是无监督学习算法.
其具有思想简单, 效果好和容易实现的优点, 广泛应用于机器学习等领域. 但是K-Means …

In deep learning research, self-supervised learning (SSL) has received great attention,
triggering interest within both the computer vision and remote sensing communities. While …

The k-means clustering algorithm is considered one of the most powerful and popular data
mining algorithms in the research community. However, despite its popularity, the algorithm …

Recently, with the emergence of Industry 4.0 (I4. 0), smart systems, machine learning (ML)
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …

Multi-objective evolutionary algorithms (MOEAs) have shown promising performance in
solving various optimization problems, but their performance may deteriorate drastically …

Abstract Machine learning (ML) pervades an increasing number of academic disciplines and
industries. Its impact is profound, and several fields have been fundamentally altered by it …

Large-scale labeled data are generally required to train deep neural networks in order to
obtain better performance in visual feature learning from images or videos for computer …