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Predicting the compressive strength of concrete from its compositions and age using the extreme gradient boosting method
Predicting the compressive strength of concrete from its compositions and age using the extreme gradient boosting method
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Predicting the compressive strength of concrete from its compositions and age using the extreme gradient boosting method

Nguyen-Sy, Tuan ; Wakim, Jad ; To, Quy-Dong ; Vu, Minh-Ngoc ; Nguyen, The-Duong ; Nguyen, Thoi-Trung

Construction & building materials, 2020-11, Vol.260, p.119757, Article 119757 [Periódico revisado por pares]

Elsevier Ltd

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A comparative analysis of biomass torrefaction severity index prediction from machine learning
A comparative analysis of biomass torrefaction severity index prediction from machine learning
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A comparative analysis of biomass torrefaction severity index prediction from machine learning

Chen, Wei-Hsin ; Aniza, Ria ; Arpia, Arjay A. ; Lo, Hsiu-Ju ; Hoang, Anh Tuan ; Goodarzi, Vahabodin ; Gao, Jianbing

Applied energy, 2022-10, Vol.324, p.119689, Article 119689 [Periódico revisado por pares]

Elsevier Ltd

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Machine learning algorithms to predict flow boiling pressure drop in mini/micro-channels based on universal consolidated data
Machine learning algorithms to predict flow boiling pressure drop in mini/micro-channels based on universal consolidated data
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Machine learning algorithms to predict flow boiling pressure drop in mini/micro-channels based on universal consolidated data

Qiu, Yue ; Garg, Deepak ; Kim, Sung-Min ; Mudawar, Issam ; Kharangate, Chirag R.

International journal of heat and mass transfer, 2021-10, Vol.178, p.121607, Article 121607 [Periódico revisado por pares]

Elsevier Ltd

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Wake modeling of wind turbines using machine learning
Wake modeling of wind turbines using machine learning
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Wake modeling of wind turbines using machine learning

Ti, Zilong ; Deng, Xiao Wei ; Yang, Hongxing

Applied energy, 2020-01, Vol.257, p.114025, Article 114025 [Periódico revisado por pares]

Elsevier Ltd

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5
Prediction of ultimate bearing capacity through various novel evolutionary and neural network models
Prediction of ultimate bearing capacity through various novel evolutionary and neural network models
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Prediction of ultimate bearing capacity through various novel evolutionary and neural network models

Moayedi, Hossein ; Moatamediyan, Arash ; Nguyen, Hoang ; Bui, Xuan-Nam ; Bui, Dieu Tien ; Rashid, Ahmad Safuan A.

Engineering with computers, 2020-04, Vol.36 (2), p.671-687 [Periódico revisado por pares]

London: Springer London

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Comparative study on total nitrogen prediction in wastewater treatment plant and effect of various feature selection methods on machine learning algorithms performance
Comparative study on total nitrogen prediction in wastewater treatment plant and effect of various feature selection methods on machine learning algorithms performance
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Comparative study on total nitrogen prediction in wastewater treatment plant and effect of various feature selection methods on machine learning algorithms performance

Bagherzadeh, Faramarz ; Mehrani, Mohamad-Javad ; Basirifard, Milad ; Roostaei, Javad

Journal of water process engineering, 2021-06, Vol.41, p.102033, Article 102033 [Periódico revisado por pares]

Elsevier Ltd

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Machine learning approach to predict new multiphase high entropy alloys
Machine learning approach to predict new multiphase high entropy alloys
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Machine learning approach to predict new multiphase high entropy alloys

Krishna, Yegi Vamsi ; Jaiswal, Ujjawal Kumar ; R, Rahul M

Scripta materialia, 2021-05, Vol.197, p.113804, Article 113804 [Periódico revisado por pares]

Elsevier Ltd

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8
State of the Art of Machine Learning Models in Energy Systems, a Systematic Review
State of the Art of Machine Learning Models in Energy Systems, a Systematic Review
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State of the Art of Machine Learning Models in Energy Systems, a Systematic Review

Mosavi, Amir ; Salimi, Mohsen ; Faizollahzadeh Ardabili, Sina ; Rabczuk, Timon ; Shamshirband, Shahaboddin ; Varkonyi-Koczy, Annamaria R.

Energies (Basel), 2019-04, Vol.12 (7), p.1301 [Periódico revisado por pares]

Basel: MDPI AG

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Effective modelling of hydrogen and energy recovery in microbial electrolysis cell by artificial neural network and adaptive network-based fuzzy inference system
Effective modelling of hydrogen and energy recovery in microbial electrolysis cell by artificial neural network and adaptive network-based fuzzy inference system
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Effective modelling of hydrogen and energy recovery in microbial electrolysis cell by artificial neural network and adaptive network-based fuzzy inference system

Hosseinzadeh, Ahmad ; Zhou, John L. ; Altaee, Ali ; Baziar, Mansour ; Li, Donghao

Bioresource technology, 2020-11, Vol.316, p.123967-123967, Article 123967 [Periódico revisado por pares]

Elsevier Ltd

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10
Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategy
Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategy
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Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategy

Yuan, Xiaofeng ; Zhou, Jiao ; Huang, Biao ; Wang, Yalin ; Yang, Chunhua ; Gui, Weihua

IEEE transactions on industrial informatics, 2020-06, Vol.16 (6), p.3721-3730

Piscataway: IEEE

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