Results 21 to 30 of about 8,140,064 (302)

Augmented Quaternion Extreme Learning Machine

IEEE Access, 2019
As an efficient training strategy for single hidden layer neural networks, extreme learning machine, and its variants have been widely used due to its fast learning speed and superior generalization performance.
Huisheng Zhang, Hui Lv
doaj   +1 more source

Unsupervised feature learning with sparse Bayesian auto-encoding based extreme learning machine

, 2020
Extreme learning machine (ELM) is a popular method in machine learning with extremely few parameters, fast learning speed and model efficiency. Unsupervised feature learning based ELM receives rising research focus. Recently the ELM auto-encoder (ELM-AE)
Zhang, Guanghao, Cui, Dongshun, Huang, Guang-Bin, Mao, Shangbo   +3 more
core   +1 more source

Extreme Minimal Learning Machine [PDF]

, 2019
Extreme Learning Machine (ELM) and Minimal Learning Machine (MLM) are nonlinear and scalable machine learning techniques with randomly generated basis.
Kärkkäinen, Tommi
core   +1 more source

Multifault Diagnosis for Rolling Element Bearings Based on Intrinsic Mode Permutation Entropy and Ensemble Optimal Extreme Learning Machine

Advances in Mechanical Engineering, 2014
This paper presented a novel procedure based on the ensemble empirical mode decomposition and extreme learning machine. Firstly, EEMD was utilized to decompose the vibration signals into a number of IMFs adaptively and the permutation entropy of each IMF
Jianzhong Zhou, Jian Xiao, Han Xiao, Weibo Zhang, Wenlong Zhu, Chaoshun Li   +5 more
doaj   +1 more source

Research into Financial Position of Listed Companies following Classification via Extreme Learning Machine Based upon DE Optimization

MATEC Web of Conferences, 2016
By means of the model of extreme learning machine based upon DE optimization, this article particularly centers on the optimization thinking of such a model as well as its application effect in the field of listed company’s financial position ...
Fu Yu, Mu Jiong, Duan Xu Liang
doaj   +1 more source

An online deep extreme learning machine based on forgetting mechanism

Dianzi Jishu Yingyong, 2018
The development of deep learning promotes the development of deep online learning, and online learning tends to have strong effectiveness. Based on the principle of online extreme learning machine and the principle of autoencoder of deep extreme learning
Liu Buzhong
doaj   +1 more source

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach

Sensors, 2017
A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic
Yulin Jian, Daoyu Huang, Jia Yan, Kun Lu, Ying Huang, Tailai Wen, Tanyue Zeng, Shijie Zhong, Qilong Xie   +8 more
doaj   +1 more source

Binary/ternary extreme learning machines [PDF]

Neurocomputing, 2015
In this paper, a new hidden layer construction method for Extreme Learning Machines (ELMs) is investigated, aimed at generating a diverse set of weights. The paper proposes two new ELM variants: Binary ELM, with a weight initialization scheme based on { 0 , 1 } -weights; and Ternary ELM, with a weight initialization scheme based on { - 1 , 0 , 1 ...
van Heeswijk, Mark, Miche, Yoan
openaire   +2 more sources

Extreme Learning Machine.

, 2019
Extreme Learning Machine.
Sabih Ahmad Khan (7853771), Hsien-Tsung Chang (146098)   +1 more
core   +1 more source

Groundwater Prediction Using Machine-Learning Tools

, 2020
Predicting groundwater availability is important to water sustainability and drought mitigation. Machine-learning tools have the potential to improve groundwater prediction, thus enabling resource planners to: (1) anticipate water quality in unsampled ...
Christopher Thron, Mattia Vaccari, Eslam A. Hussein, Antoine Bagula, Mehrdad Ghaziasgar   +4 more
core   +1 more source