… ELM on MapReduce was inefficient for updated big data learning and proposed elastic
ELM for improvement. The most time-consuming part for big data learning of ELM is the matrix …

… In this study, extreme learning machine (ELM) was used to predict and classify rockburst
intensity, and particle swarm optimization (PSO) was used to optimize the input weight matrix …

… Sentiment Analysis (SA) of a large quantity of user reviews on e-commerce platforms. It is
still challenging to envisage the accurate sentiment … a new optimized Machine Learning (ML) …

… In the present study, a new modified version of Convolutional Neural Network (CNN) was …
based on combining it with the extreme learning machine and optimizing the network based on …

… , this paper proposes a method based on variational mode … optimization (IASO) and extreme
learning machine (ELM). VMD is first employed to decompose the original wind speed data …

… This paper proposed a framework for cloud-based breast cancer diagnosis using Extreme
Learning Machine (ELM) as a classifier. Cloud computing can provide unceasing services …

… optimization algorithms. This study focuses on the design of a big data classification model
using chaotic pigeon inspired optimization (CPIO)-based feature selection with an optimal …

… of Keras’s deep learning models with three robust optimization algorithms (stochastic gradient
descent, root mean square propagation, and adaptive moment optimization) and two-loss …

… A new short-term photovoltaic power output prediction model is proposed Based on extreme
learning machine and intelligent optimizer. Firstly, the input of the model is determined by …

… In this work, a hybrid model (SDA-GA-ELM) based on extreme learning machine (ELM),
genetic algorithm (GA) and customized similar day analysis (SDA) has been developed to …