Extreme learning machine (ELM) has received considerable attention due to its rapid
learning speed and powerful fitting capabilities. One of its important variants, the elastic-net …

In this paper, we proposed a novel regularization and variable selection algorithm called Liu–
Lasso extreme learning machine (LL-ELM) in order to deal with the ELM's drawbacks like …

Extreme learning machine (ELM) is one of the most notable machine learning algorithms
with many advantages, especially its training speed. However, ELM has some drawbacks …

Purpose This paper aims to develop a novel method and apply it to solve multiple definite
integrals. The proposed method is constructed based on multiple sets of correlation extreme …

Extreme learning machine (ELM) as a type of feedforward neural network has been widely
used to obtain beneficial insights from various disciplines and real-world applications …

The aim of this study is to present a new regularized extreme learning machine (ELM)
algorithm that can perform variable selection based on the simultaneous use of both ridge …

The multicollinearity problem is a common phenomenon in data-driven studies, significantly
affecting the performance of machine learning algorithms during the process of extracting …

To predict the trend of stock prices, a belief rule base (BRB) assessment model based on
different technical indicators is proposed in this paper. The proposed BRB-based model …

The existing randomized autoencoders are generally designed for vectorization data
resulting in destroying the original structure information inevitably when dealing with multi …

情绪是人类重要的生理属性， 情绪识别技术可以更好地辅助人类进行自我认识。
本文针对不同受试者之间的脑电信号（ EEG） 存在巨大差异的难点， 在传统鲸鱼优化算法 …