Detecting faults in hydraulic valves are of great significance to improve the reliability and
security of the whole hydraulic system. However, it is difficult to detect multiple faults in …

In recent years, there has been an immense research interest in applying Machine Learning
for defending networked systems from cyber threats. A particular challenge in this domain is …

Feature selection has gained its importance due to the voluminous nature of the data. Owing
to the computational complexity of wrapper approaches, the poor performance of filtering …

Ensemble classifiers methods are considered as one of the strongest classification
approaches in different applications. A key factor in creating a successful ensemble is to …

In recent years, hand-based multimodal biometrics has received a lot of attention in the field
of pattern recognition due to its convenience, stability and inclusion of a wider range of …

A computer-implemented method and system including a recommendation engine receiving
a first user behavior data, the first user behavior data associated with a user action taken by …

With the development of intelligence technology, high-dimensional multi-label data exist in
practical applications, which makes multi-label learning a significant challenge. Feature …

在特征选择问题中, 近似马尔科夫毯常用于判断冗余特征, 但所得到的冗余特征并不完全相同,
因此, 在直接使用近似马尔科夫毯删除冗余特征时, 存在可能导致信息丢失的情况 …

Abstract Addressing uncertainty in Deep Learning (DL) is essential, as it enables the
development of models that can make reliable predictions and informed decisions in …

The process of creating and selecting features from raw data to enhance the accuracy of
machine learning models is referred to as feature engineering. In the context of real-time …