Technologies have driven big data collection across many fields, such as genomics and
business intelligence. This results in a significant increase in variables and data points …

Extreme learning machine (ELM) has been developed for single hidden layer feedforward
neural networks (SLFNs). In ELM algorithm, the connections between the input layer and the …

摘要极限学习机(ExtremeLearningMachine, ELM) 作为前馈神经网络学习中一种全新的训练
框架, 在行为识别, 情感识别和故障诊断等方面被广泛应用, 引起了各个领域的高度关注和深入 …

In our society, many fields have produced a large number of data streams. How to mining
the interesting knowledge and patterns from continuous data stream becomes a problem …

Deep neural networks have shown their promise in recent years with their state-of-the-art
results. Yet, backpropagation-based methods may suffer from time-consuming training …

Many daily applications are generating massive amount of data in the form of stream at an
ever higher speed, such as medical data, clicking stream, internet record and banking …

In this paper, a meta-cognitive online sequential extreme learning machine (MOS-ELM) is
proposed for class imbalance and concept drift learning. In MOS-ELM, meta-cognition is …

Stock returns are continuously generated by different data sources and depend on various
factors such as financial policies and national economic growths. Stock returns prediction …

Gas utilization ratio (GUR) is an important indicator used to measure the operating status
and energy consumption of blast furnaces (BFs). In this paper, we present a soft-sensor …

The demanding nature of construction works exposes workers to prolonged physical labor
and high-risk environments, increasing their vulnerability to mental fatigue and consequently …