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1
Using Genetic Algorithm and Particle Swarm Optimization BP Neural Network Algorithm to Improve Marine Oil Spill Prediction
Using Genetic Algorithm and Particle Swarm Optimization BP Neural Network Algorithm to Improve Marine Oil Spill Prediction
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Using Genetic Algorithm and Particle Swarm Optimization BP Neural Network Algorithm to Improve Marine Oil Spill Prediction

Water, air, and soil pollution, 2022-08, Vol.233 (8), Article 354 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. ;COPYRIGHT 2022 Springer ;ISSN: 0049-6979 ;EISSN: 1573-2932 ;DOI: 10.1007/s11270-022-05771-x

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2
Ethnomathematics batik design Bali island
Ethnomathematics batik design Bali island
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Ethnomathematics batik design Bali island

Journal of physics. Conference series, 2019-10, Vol.1338 (1), p.12045 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1338/1/012045

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3
Deep physical neural networks trained with backpropagation
Deep physical neural networks trained with backpropagation
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Deep physical neural networks trained with backpropagation

Nature (London), 2022-01, Vol.601 (7894), p.549-555 [Peer Reviewed Journal]

2022. The Author(s). ;Copyright Nature Publishing Group Jan 27, 2022 ;The Author(s) 2022 ;ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/s41586-021-04223-6 ;PMID: 35082422

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4
Learning Explanatory Rules from Noisy Data
Learning Explanatory Rules from Noisy Data
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Learning Explanatory Rules from Noisy Data

The Journal of artificial intelligence research, , Vol.61, p.1-64 [Peer Reviewed Journal]

2018. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.jair.org/index.php/jair/about ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.5714

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5
A solution to the learning dilemma for recurrent networks of spiking neurons
A solution to the learning dilemma for recurrent networks of spiking neurons
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A solution to the learning dilemma for recurrent networks of spiking neurons

Nature communications, 2020-07, Vol.11 (1), p.3625-3625, Article 3625 [Peer Reviewed Journal]

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. ;The Author(s) 2020 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-020-17236-y ;PMID: 32681001

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6
Large-Scale Optical Neural Networks Based on Photoelectric Multiplication
Large-Scale Optical Neural Networks Based on Photoelectric Multiplication
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Large-Scale Optical Neural Networks Based on Photoelectric Multiplication

Physical review. X, 2019-05, Vol.9 (2), p.021032, Article 021032 [Peer Reviewed Journal]

2019. This work is licensed under https://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: 2160-3308 ;EISSN: 2160-3308 ;DOI: 10.1103/PhysRevX.9.021032

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7
Differentiable Programming Tensor Networks
Differentiable Programming Tensor Networks
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Differentiable Programming Tensor Networks

Physical review. X, 2019-09, Vol.9 (3), p.031041, Article 031041 [Peer Reviewed Journal]

2019. This work is licensed under https://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: 2160-3308 ;EISSN: 2160-3308 ;DOI: 10.1103/PhysRevX.9.031041

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8
Back-Propagation Neural Network Optimized by K-Fold Cross-Validation for Prediction of Torsional Strength of Reinforced Concrete Beam
Back-Propagation Neural Network Optimized by K-Fold Cross-Validation for Prediction of Torsional Strength of Reinforced Concrete Beam
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Back-Propagation Neural Network Optimized by K-Fold Cross-Validation for Prediction of Torsional Strength of Reinforced Concrete Beam

Materials, 2022-02, Vol.15 (4), p.1477 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 by the authors. 2022 ;ISSN: 1996-1944 ;EISSN: 1996-1944 ;DOI: 10.3390/ma15041477 ;PMID: 35208015

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9
An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox
An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox
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An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

Sensors (Basel, Switzerland), 2017-02, Vol.17 (2), p.414-414 [Peer Reviewed Journal]

2017. This work is licensed under https://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. ;2017 by the authors. 2017 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s17020414 ;PMID: 28230767

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10
A Levy flight-based grey wolf optimizer combined with back-propagation algorithm for neural network training
A Levy flight-based grey wolf optimizer combined with back-propagation algorithm for neural network training
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A Levy flight-based grey wolf optimizer combined with back-propagation algorithm for neural network training

Neural computing & applications, 2018-12, Vol.30 (12), p.3707-3720 [Peer Reviewed Journal]

The Natural Computing Applications Forum 2017 ;Copyright Springer Science & Business Media 2018 ;ISSN: 0941-0643 ;ISSN: 1433-3058 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-017-2952-5

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11
Equalization enhanced phase noise in Nyquist-spaced superchannel transmission systems using multi-channel digital back-propagation
Equalization enhanced phase noise in Nyquist-spaced superchannel transmission systems using multi-channel digital back-propagation
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Equalization enhanced phase noise in Nyquist-spaced superchannel transmission systems using multi-channel digital back-propagation

Scientific reports, 2015-09, Vol.5 (1), p.13990-13990, Article 13990 [Peer Reviewed Journal]

Copyright Nature Publishing Group Sep 2015 ;Copyright © 2015, Macmillan Publishers Limited 2015 Macmillan Publishers Limited ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/srep13990 ;PMID: 26365422

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12
Designing neural networks through neuroevolution
Designing neural networks through neuroevolution
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Designing neural networks through neuroevolution

Nature machine intelligence, 2019-01, Vol.1 (1), p.24-35 [Peer Reviewed Journal]

Springer Nature Limited 2019. ;ISSN: 2522-5839 ;EISSN: 2522-5839 ;DOI: 10.1038/s42256-018-0006-z

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13
Low-dimensional dynamics for working memory and time encoding
Low-dimensional dynamics for working memory and time encoding
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Low-dimensional dynamics for working memory and time encoding

Proceedings of the National Academy of Sciences - PNAS, 2020-09, Vol.117 (37), p.23021-23032 [Peer Reviewed Journal]

Copyright National Academy of Sciences Sep 15, 2020 ;2020 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.1915984117 ;PMID: 32859756

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14
Convolutional Neural Network Based on Extreme Learning Machine for Maritime Ships Recognition in Infrared Images
Convolutional Neural Network Based on Extreme Learning Machine for Maritime Ships Recognition in Infrared Images
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Convolutional Neural Network Based on Extreme Learning Machine for Maritime Ships Recognition in Infrared Images

Sensors (Basel, Switzerland), 2018-05, Vol.18 (5), p.1490 [Peer Reviewed Journal]

2018. This work is licensed under https://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. ;2018 by the authors. 2018 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s18051490 ;PMID: 29747439

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15
Advancing theoretical understanding and practical performance of signal processing for nonlinear optical communications through machine learning
Advancing theoretical understanding and practical performance of signal processing for nonlinear optical communications through machine learning
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Advancing theoretical understanding and practical performance of signal processing for nonlinear optical communications through machine learning

Nature communications, 2020-07, Vol.11 (1), p.3694-3694, Article 3694 [Peer Reviewed Journal]

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. ;The Author(s) 2020 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-020-17516-7 ;PMID: 32703945

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16
Toward a theory of evolution as multilevel learning
Toward a theory of evolution as multilevel learning
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Toward a theory of evolution as multilevel learning

Proceedings of the National Academy of Sciences - PNAS, 2022-02, Vol.119 (6), p.1 [Peer Reviewed Journal]

Copyright © 2022 the Author(s). Published by PNAS. ;Copyright National Academy of Sciences Feb 8, 2022 ;Copyright © 2022 the Author(s). Published by PNAS. 2022 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.2120037119 ;PMID: 35121666

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17
Learning hidden elasticity with deep neural networks
Learning hidden elasticity with deep neural networks
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Learning hidden elasticity with deep neural networks

Proceedings of the National Academy of Sciences - PNAS, 2021-08, Vol.118 (31), p.1 [Peer Reviewed Journal]

Copyright National Academy of Sciences Aug 3, 2021 ;2021 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.2102721118 ;PMID: 34326258

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18
Investigation and back-propagation modeling of base pressure at sonic and supersonic Mach numbers
Investigation and back-propagation modeling of base pressure at sonic and supersonic Mach numbers
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Investigation and back-propagation modeling of base pressure at sonic and supersonic Mach numbers

Physics of fluids (1994), 2020-09, Vol.32 (9) [Peer Reviewed Journal]

Author(s) ;2020 Author(s). Published under license by AIP Publishing. ;ISSN: 1070-6631 ;EISSN: 1089-7666 ;DOI: 10.1063/5.0022015 ;CODEN: PHFLE6

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19
Mold breakout prediction in slab continuous casting based on combined method of GA-BP neural network and logic rules
Mold breakout prediction in slab continuous casting based on combined method of GA-BP neural network and logic rules
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Mold breakout prediction in slab continuous casting based on combined method of GA-BP neural network and logic rules

International journal of advanced manufacturing technology, 2018-04, Vol.95 (9-12), p.4081-4089 [Peer Reviewed Journal]

Springer-Verlag London Ltd., part of Springer Nature 2018 ;Copyright Springer Science & Business Media 2018 ;The International Journal of Advanced Manufacturing Technology is a copyright of Springer, (2018). All Rights Reserved. ;Springer-Verlag London Ltd., part of Springer Nature 2018. ;ISSN: 0268-3768 ;EISSN: 1433-3015 ;DOI: 10.1007/s00170-017-1517-1

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20
A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks
A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks
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A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks

Neural computing & applications, 2018, Vol.29 (11), p.991-1004 [Peer Reviewed Journal]

The Author(s) 2016 ;Copyright Springer Science & Business Media 2018 ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-016-2564-5 ;PMID: 29769759

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