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1
Prairie Dog Optimization Algorithm
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Prairie Dog Optimization Algorithm

Neural computing & applications, 2022-11, Vol.34 (22), p.20017-20065 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-022-07530-9

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2
InceptionTime: Finding AlexNet for time series classification
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InceptionTime: Finding AlexNet for time series classification

Data mining and knowledge discovery, 2020-11, Vol.34 (6), p.1936-1962 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020 ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-020-00710-y

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3
Deep learning for time series classification: a review
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Deep learning for time series classification: a review

Data mining and knowledge discovery, 2019-07, Vol.33 (4), p.917-963 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2019 ;Data Mining and Knowledge Discovery is a copyright of Springer, (2019). All Rights Reserved. ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-019-00619-1

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4
A survey of transfer learning
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A survey of transfer learning

Journal of big data, 2016-05, Vol.3 (1), Article 9 [Peer Reviewed Journal]

The Author(s) 2016 ;ISSN: 2196-1115 ;EISSN: 2196-1115 ;DOI: 10.1186/s40537-016-0043-6

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5
An approach toward decision-making and medical diagnosis problems using the concept of spherical fuzzy sets
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An approach toward decision-making and medical diagnosis problems using the concept of spherical fuzzy sets

Neural computing & applications, 2019-11, Vol.31 (11), p.7041-7053 [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/s00521-018-3521-2

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6
A deep learning approach for Parkinson’s disease diagnosis from EEG signals
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A deep learning approach for Parkinson’s disease diagnosis from EEG signals

Neural computing & applications, 2020-08, Vol.32 (15), p.10927-10933 [Peer Reviewed Journal]

The Natural Computing Applications Forum 2018 ;The Natural Computing Applications Forum 2018. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-018-3689-5

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7
Federated Learning for Healthcare Informatics
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Federated Learning for Healthcare Informatics

Journal of healthcare informatics research, 2021, Vol.5 (1), p.1-19

Springer Nature Switzerland AG 2020 ;ISSN: 2509-4971 ;EISSN: 2509-498X ;DOI: 10.1007/s41666-020-00082-4 ;PMID: 33204939

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8
catch22: CAnonical Time-series CHaracteristics: Selected through highly comparative time-series analysis
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catch22: CAnonical Time-series CHaracteristics: Selected through highly comparative time-series analysis

Data mining and knowledge discovery, 2019-11, Vol.33 (6), p.1821-1852 [Peer Reviewed Journal]

The Author(s) 2019 ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-019-00647-x

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9
Monarch butterfly optimization
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Monarch butterfly optimization

Neural computing & applications, 2019-07, Vol.31 (7), p.1995-2014 [Peer Reviewed Journal]

The Natural Computing Applications Forum 2015 ;Neural Computing and Applications is a copyright of Springer, (2015). All Rights Reserved. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-015-1923-y

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10
A survey on Image Data Augmentation for Deep Learning
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A survey on Image Data Augmentation for Deep Learning

Journal of big data, 2019-07, Vol.6 (1), p.1-48, Article 60 [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/s40537-019-0197-0

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11
A dynamic ensemble learning algorithm for neural networks
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A dynamic ensemble learning algorithm for neural networks

Neural computing & applications, 2020-06, Vol.32 (12), p.8675-8690 [Peer Reviewed Journal]

The Author(s) 2019 ;The Author(s) 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: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-019-04359-7

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12
On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study
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On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study

Data mining and knowledge discovery, 2016-07, Vol.30 (4), p.891-927 [Peer Reviewed Journal]

The Author(s) 2016 ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-015-0444-8

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13
A survey of sentiment analysis in social media
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A survey of sentiment analysis in social media

Knowledge and information systems, 2019-08, Vol.60 (2), p.617-663 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2018 ;Knowledge and Information Systems is a copyright of Springer, (2018). All Rights Reserved. ;ISSN: 0219-1377 ;EISSN: 0219-3116 ;DOI: 10.1007/s10115-018-1236-4

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14
A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength
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A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength

Neural computing & applications, 2021-05, Vol.33 (9), p.4501-4532 [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/s00521-020-05244-4

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15
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
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Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

Journal of big data, 2021-03, Vol.8 (1), p.53-53, Article 53 [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/s40537-021-00444-8 ;PMID: 33816053

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16
Grey wolf optimizer: a review of recent variants and applications
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Grey wolf optimizer: a review of recent variants and applications

Neural computing & applications, 2018-07, Vol.30 (2), p.413-435 [Peer Reviewed Journal]

The Natural Computing Applications Forum 2017 ;Copyright Springer Science & Business Media 2018 ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-017-3272-5

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17
Feature selection via a novel chaotic crow search algorithm
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Feature selection via a novel chaotic crow search algorithm

Neural computing & applications, 2019-01, Vol.31 (1), p.171-188 [Peer Reviewed Journal]

The Natural Computing Applications Forum 2017 ;Copyright Springer Nature B.V. 2019 ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-017-2988-6

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18
Evolutionary algorithms and their applications to engineering problems
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Article
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Evolutionary algorithms and their applications to engineering problems

Neural computing & applications, 2020-08, Vol.32 (16), p.12363-12379 [Peer Reviewed Journal]

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: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-020-04832-8

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19
Survey on deep learning with class imbalance
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Article
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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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20
A CNN–LSTM model for gold price time-series forecasting
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Article
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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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