Results 11 to 20 of about 7,810,973 (301)

Local Coupled Extreme Learning Machine Based on Particle Swarm Optimization

Algorithms, 2018
We developed a new method of intelligent optimum strategy for a local coupled extreme learning machine (LC-ELM). In this method, both the weights and biases between the input layer and the hidden layer, as well as the addresses and radiuses in the local ...
Hongli Guo, Bin Li, Wei Li, Fengjuan Qiao, Xuewen Rong, Yibin Li   +5 more
doaj   +2 more sources

Hierarchical Information-Extreme Machine Learning of Hand Prosthesis Control System Based on Decursive Data Structure

Журнал інженерних наук
The article considers the machine learning method for a hand prosthesis control system that recognizes electromyographic signals with a non-invasive recording system.
Anatolii Dovbysh, Vladyslav Piatachenko, Mykyta Myronenko, Mykyta Suprunenko, Julius Simonovskiy   +4 more
doaj   +2 more sources

Fault diagnosis method based on wavelet packet-energy entropy and fuzzy kernel extreme learning machine

Advances in Mechanical Engineering, 2018
Aiming at connatural limitations of extreme learning machine in practice, a new fault diagnosis method based on wavelet packet-energy entropy and fuzzy kernel extreme learning machine is proposed.
Jun Ma, Jiande Wu, Xiaodong Wang
doaj   +1 more source

Research on an improved lp-RWMKE-ELM fault diagnosis model

工程科学学报, 2022
As the service time of military equipment increases, equipment failure data is continuously accumulated during events such as routine maintenance, training, and combat readiness exercises, and the data presented is often imbalanced to varying degrees and
Xing LIU, Jian-yin ZHAO, Min ZHU, Wei ZHANG   +3 more
doaj   +1 more source

A Novel Fault Diagnosis Method for Motor Bearing Based on DTCWT and AFSO-KELM

Shock and Vibration, 2021
Aiming at the defects of wavelet transform-based feature extraction and extreme learning machine-based classification, a novel fault diagnosis method for motor bearing, based on dual tree complex wavelet transform and artificial fish swarm optimization ...
Yan Lu, Peijiang Li
doaj   +1 more source

FORECASTING OF CURRENCY CIRCULATION IN INDONESIA USING HYBRID EXTREME LEARNING MACHINE

Barekeng, 2022
Forecasting currency circulation, including inflow and outflow, is one of Bank Indonesia's strategies to maintain the Rupiah value's stability. The characteristic of inflow and outflow data is that they have seasonal variations.
Mujiati Dwi Kartikasari
doaj   +1 more source

Sparse Extreme Learning Machine for Classification [PDF]

IEEE Transactions on Cybernetics, 2014
Extreme learning machine (ELM) was initially proposed for single-hidden-layer feedforward neural networks (SLFNs). In the hidden layer (feature mapping), nodes are randomly generated independently of training data. Furthermore, a unified ELM was proposed, providing a single framework to simplify and unify different learning methods, such as SLFNs ...
Zuo Bai, Guang-Bin Huang, Danwei Wang, Han Wang 0001, M. Brandon Westover   +4 more
openaire   +3 more sources

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

Extreme Rainfall Event Classification Using Machine Learning for Kikuletwa River Floods [PDF]

, 2023
Advancements in machine learning techniques, availability of more data sets, and increased computing power have enabled a significant growth in a number of research areas.
Edith Luhanga, Leo, Judith, Mdegela, Lawrence, Erik Mannens, Mdegela, Lawrence Nehemiah, Mannens, Erik, De Bock, Yorick, Lawrence Mdegela, Yorick De Bock, Esteban Municio, Municio, Esteban, Judith Leo, Luhanga, Edith, Bock, Yorick   +13 more
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