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Optimizing an ANN model with ICA for estimating bearing capacity of driven pile in cohesionless soil
Optimizing an ANN model with ICA for estimating bearing capacity of driven pile in cohesionless soil
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Optimizing an ANN model with ICA for estimating bearing capacity of driven pile in cohesionless soil

Moayedi, Hossein ; Jahed Armaghani, Danial

Engineering with computers, 2018-04, Vol.34 (2), p.347-356 [Periódico revisado por pares]

London: Springer London

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12
The impact of the ANN’s choice on PV systems diagnosis quality
The impact of the ANN’s choice on PV systems diagnosis quality
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The impact of the ANN’s choice on PV systems diagnosis quality

Kara Mostefa Khelil, Chérifa ; Amrouche, Badia ; Kara, Kamel ; Chouder, Aissa

Energy conversion and management, 2021-07, Vol.240, p.114278, Article 114278 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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13
Progress of artificial neural networks applications in hydrogen production
Progress of artificial neural networks applications in hydrogen production
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Progress of artificial neural networks applications in hydrogen production

Abdelkareem, Mohammad A. ; Soudan, Bassel ; Mahmoud, Mohamed S. ; Sayed, Enas T. ; AlMallahi, Maryam N. ; Inayat, Abrar ; Radi, Muaz Al ; Olabi, Abdul G.

Chemical engineering research & design, 2022-06, Vol.182, p.66-86 [Periódico revisado por pares]

Rugby: Elsevier Ltd

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14
Airblast prediction through a hybrid genetic algorithm-ANN model
Airblast prediction through a hybrid genetic algorithm-ANN model
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Airblast prediction through a hybrid genetic algorithm-ANN model

Jahed Armaghani, Danial ; Hasanipanah, Mahdi ; Mahdiyar, Amir ; Abd Majid, Muhd Zaimi ; Bakhshandeh Amnieh, Hassan ; Tahir, Mahmood M. D.

Neural computing & applications, 2018-05, Vol.29 (9), p.619-629 [Periódico revisado por pares]

London: Springer London

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15
Modeling and simulation of co-digestion performance with artificial neural network for prediction of methane production from tea factory waste with co-substrate of spent tea waste
Modeling and simulation of co-digestion performance with artificial neural network for prediction of methane production from tea factory waste with co-substrate of spent tea waste
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Modeling and simulation of co-digestion performance with artificial neural network for prediction of methane production from tea factory waste with co-substrate of spent tea waste

Özarslan, Saliha ; Abut, Serdar ; Atelge, M.R. ; Kaya, M. ; Unalan, S.

Fuel (Guildford), 2021-12, Vol.306, p.121715, Article 121715 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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16
An integrated design of particle swarm optimization (PSO) with fusion of features for detection of brain tumor
An integrated design of particle swarm optimization (PSO) with fusion of features for detection of brain tumor
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An integrated design of particle swarm optimization (PSO) with fusion of features for detection of brain tumor

Sharif, Muhammad ; Amin, Javaria ; Raza, Mudassar ; Yasmin, Mussarat ; Satapathy, Suresh Chandra

Pattern recognition letters, 2020-01, Vol.129, p.150-157 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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17
An optimized ANN model based on genetic algorithm for predicting ripping production
An optimized ANN model based on genetic algorithm for predicting ripping production
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An optimized ANN model based on genetic algorithm for predicting ripping production

Mohamad, Edy Tonnizam ; Faradonbeh, Roohollah Shirani ; Armaghani, Danial Jahed ; Monjezi, Masoud ; Majid, Muhd Zaimi Abd

Neural computing & applications, 2017-12, Vol.28 (Suppl 1), p.393-406 [Periódico revisado por pares]

London: Springer London

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18
A hybrid artificial bee colony algorithm-artificial neural network for forecasting the blast-produced ground vibration
A hybrid artificial bee colony algorithm-artificial neural network for forecasting the blast-produced ground vibration
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A hybrid artificial bee colony algorithm-artificial neural network for forecasting the blast-produced ground vibration

Taheri, Khalil ; Hasanipanah, Mahdi ; Golzar, Saeid Bagheri ; Majid, Muhd Zaimi Abd

Engineering with computers, 2017-07, Vol.33 (3), p.689-700 [Periódico revisado por pares]

London: Springer London

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19
Prediction on the viscosity and thermal conductivity of hfc/hfo refrigerants with artificial neural network models
Prediction on the viscosity and thermal conductivity of hfc/hfo refrigerants with artificial neural network models
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Prediction on the viscosity and thermal conductivity of hfc/hfo refrigerants with artificial neural network models

Wang, Xuehui ; Li, Ying ; Yan, Yuying ; Wright, Edward ; Gao, Neng ; Chen, Guangming

International journal of refrigeration, 2020-11, Vol.119, p.316-325 [Periódico revisado por pares]

Paris: Elsevier Ltd

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20
Assessing Dynamic Conditions of the Retaining Wall: Developing Two Hybrid Intelligent Models
Assessing Dynamic Conditions of the Retaining Wall: Developing Two Hybrid Intelligent Models
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Assessing Dynamic Conditions of the Retaining Wall: Developing Two Hybrid Intelligent Models

Chen, Hui ; Asteris, Panagiotis G. ; Jahed Armaghani, Danial ; Gordan, Behrouz ; Pham, Binh Thai

Applied sciences, 2019, Vol.9 (6), p.1042 [Periódico revisado por pares]

Basel: MDPI AG

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