Results 21 to 30 of about 602,374 (329)
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
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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
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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
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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
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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 +5 more
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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 +4 more
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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
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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
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The detection of globular clusters in galaxies as a data mining problem [PDF]
, 2011 We present an application of self-adaptive supervised learning classifiers derived from the Machine Learning paradigm, to the identification of candidate Globular Clusters in deep, wide-field, single band HST images. Several methods provided by the DAME (
Bassino +27 more
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Advances in Mechanical Engineering, 2018 To enhance the absolute position accuracy and solve complex modeling and computational complexity problems in traditional compensation methods for aviation drilling robots, a compensation method based on the extreme learning machine model was proposed in
Peijiang Yuan +5 more
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