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21
Survey on deep learning with class imbalance
Survey on deep learning with class imbalance
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Survey on deep learning with class imbalance

Journal of big data, 2019-03, Vol.6 (1), p.1-54, Article 27 [Peer Reviewed Journal]

The Author(s) 2019 ;Journal of Big Data is a copyright of Springer, (2019). All Rights Reserved. © 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2196-1115 ;EISSN: 2196-1115 ;DOI: 10.1186/s40537-019-0192-5

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22
A CNN–LSTM model for gold price time-series forecasting
A CNN–LSTM model for gold price time-series forecasting
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A CNN–LSTM model for gold price time-series forecasting

Neural computing & applications, 2020-12, Vol.32 (23), p.17351-17360 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2020 ;Springer-Verlag London Ltd., part of Springer Nature 2020. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-020-04867-x

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23
Concrete compressive strength using artificial neural networks
Concrete compressive strength using artificial neural networks
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Concrete compressive strength using artificial neural networks

Neural computing & applications, 2020-08, Vol.32 (15), p.11807-11826 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2019 ;Springer-Verlag London Ltd., part of Springer Nature 2019. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-019-04663-2

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24
Accurate photovoltaic power forecasting models using deep LSTM-RNN
Accurate photovoltaic power forecasting models using deep LSTM-RNN
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Accurate photovoltaic power forecasting models using deep LSTM-RNN

Neural computing & applications, 2019-07, Vol.31 (7), p.2727-2740 [Peer Reviewed Journal]

The Natural Computing Applications Forum 2017 ;Neural Computing and Applications is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-017-3225-z

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25
A transfer convolutional neural network for fault diagnosis based on ResNet-50
A transfer convolutional neural network for fault diagnosis based on ResNet-50
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A transfer convolutional neural network for fault diagnosis based on ResNet-50

Neural computing & applications, 2020-05, Vol.32 (10), p.6111-6124 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2019 ;Springer-Verlag London Ltd., part of Springer Nature 2019. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-019-04097-w

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26
A survey of methods for time series change point detection
A survey of methods for time series change point detection
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A survey of methods for time series change point detection

Knowledge and information systems, 2017-05, Vol.51 (2), p.339-367 [Peer Reviewed Journal]

Springer-Verlag London 2016 ;Knowledge and Information Systems is a copyright of Springer, 2017. ;ISSN: 0219-1377 ;EISSN: 0219-3116 ;DOI: 10.1007/s10115-016-0987-z ;PMID: 28603327 ;CODEN: KISNCR

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27
Characterizing concept drift
Characterizing concept drift
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Characterizing concept drift

Data mining and knowledge discovery, 2016-07, Vol.30 (4), p.964-994 [Peer Reviewed Journal]

The Author(s) 2016 ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-015-0448-4

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28
FEMa: a finite element machine for fast learning
FEMa: a finite element machine for fast learning
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FEMa: a finite element machine for fast learning

Neural computing & applications, 2020-05, Vol.32 (10), p.6393-6404 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2019 ;Springer-Verlag London Ltd., part of Springer Nature 2019. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-019-04146-4

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29
A survey on missing data in machine learning
A survey on missing data in machine learning
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A survey on missing data in machine learning

Journal of big data, 2021-10, Vol.8 (1), p.140-140, Article 140 [Peer Reviewed Journal]

The Author(s) 2021 ;The Author(s) 2021. ;The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2196-1115 ;EISSN: 2196-1115 ;DOI: 10.1186/s40537-021-00516-9 ;PMID: 34722113

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30
Coronavirus herd immunity optimizer (CHIO)
Coronavirus herd immunity optimizer (CHIO)
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Coronavirus herd immunity optimizer (CHIO)

Neural computing & applications, 2021-05, Vol.33 (10), p.5011-5042 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2020 ;Springer-Verlag London Ltd., part of Springer Nature 2020. ;COPYRIGHT 2021 Springer ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-020-05296-6 ;PMID: 32874019

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31
Efficient deep learning approach for augmented detection of Coronavirus disease
Efficient deep learning approach for augmented detection of Coronavirus disease
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Efficient deep learning approach for augmented detection of Coronavirus disease

Neural computing & applications, 2022-07, Vol.34 (14), p.11423-11440 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2021 ;Springer-Verlag London Ltd., part of Springer Nature 2021. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-020-05410-8 ;PMID: 33487885

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32
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances
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The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances

Data mining and knowledge discovery, 2021-03, Vol.35 (2), p.401-449 [Peer Reviewed Journal]

The Author(s) 2020 ;The Author(s) 2020. ;The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-020-00727-3 ;PMID: 33679210

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33
Deep convolutional neural network based medical image classification for disease diagnosis
Deep convolutional neural network based medical image classification for disease diagnosis
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Deep convolutional neural network based medical image classification for disease diagnosis

Journal of big data, 2019-12, Vol.6 (1), p.1-18, Article 113 [Peer Reviewed Journal]

The Author(s) 2019 ;Journal of Big Data is a copyright of Springer, (2019). All Rights Reserved. © 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2196-1115 ;EISSN: 2196-1115 ;DOI: 10.1186/s40537-019-0276-2

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34
CatBoost for big data: an interdisciplinary review
CatBoost for big data: an interdisciplinary review
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CatBoost for big data: an interdisciplinary review

Journal of big data, 2020-11, Vol.7 (1), p.94-94, Article 94 [Peer Reviewed Journal]

The Author(s) 2020 ;The Author(s) 2020. ;The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2196-1115 ;EISSN: 2196-1115 ;DOI: 10.1186/s40537-020-00369-8 ;PMID: 33169094

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35
A survey on addressing high-class imbalance in big data
A survey on addressing high-class imbalance in big data
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Article 		Add to My Research

A survey on addressing high-class imbalance in big data

Journal of big data, 2018-11, Vol.5 (1), p.1-30, Article 42 [Peer Reviewed Journal]

The Author(s) 2018 ;Journal of Big Data is a copyright of Springer, (2018). All Rights Reserved. © 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2196-1115 ;EISSN: 2196-1115 ;DOI: 10.1186/s40537-018-0151-6

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36
Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm
Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm
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Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm

Neural computing & applications, 2020-07, Vol.32 (13), p.9383-9425 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2019 ;Springer-Verlag London Ltd., part of Springer Nature 2019. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-019-04452-x

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37
A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications
A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications
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Article 		Add to My Research

A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications

Neural computing & applications, 2020-10, Vol.32 (19), p.15533-15556 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2020 ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-020-04789-8

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38
Recent advances in feature selection and its applications
Recent advances in feature selection and its applications
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Recent advances in feature selection and its applications

Knowledge and information systems, 2017-12, Vol.53 (3), p.551-577 [Peer Reviewed Journal]

Springer-Verlag London 2017 ;Knowledge and Information Systems is a copyright of Springer, 2017. ;ISSN: 0219-1377 ;EISSN: 0219-3116 ;DOI: 10.1007/s10115-017-1059-8

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39
Adversarial frontier stitching for remote neural network watermarking
Adversarial frontier stitching for remote neural network watermarking
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Article 		Add to My Research

Adversarial frontier stitching for remote neural network watermarking

Neural computing & applications, 2020-07, Vol.32 (13), p.9233-9244 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2019 ;Springer-Verlag London Ltd., part of Springer Nature 2019. ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-019-04434-z

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40
Chaotic grasshopper optimization algorithm for global optimization
Chaotic grasshopper optimization algorithm for global optimization
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Chaotic grasshopper optimization algorithm for global optimization

Neural computing & applications, 2019-08, Vol.31 (8), p.4385-4405 [Peer Reviewed Journal]

The Natural Computing Applications Forum 2018 ;Neural Computing and Applications is a copyright of Springer, (2018). All Rights Reserved. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-018-3343-2

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