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Experimental crack identification of API X70 steel pipeline using improved Artificial Neural Networks based on Whale Optimization Algorithm
Experimental crack identification of API X70 steel pipeline using improved Artificial Neural Networks based on Whale Optimization Algorithm
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Experimental crack identification of API X70 steel pipeline using improved Artificial Neural Networks based on Whale Optimization Algorithm

Ouladbrahim, A. ; Belaidi, I. ; Khatir, S. ; Magagnini, E. ; Capozucca, R. ; Abdel Wahab, M.

Mechanics of materials, 2022-03, Vol.166, p.104200, Article 104200 [Periódico revisado por pares]

Elsevier Ltd

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2
Application of a Hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) Model in Behavior Prediction of Channel Shear Connectors Embedded in Normal and High-Strength Concrete
Application of a Hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) Model in Behavior Prediction of Channel Shear Connectors Embedded in Normal and High-Strength Concrete
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Application of a Hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) Model in Behavior Prediction of Channel Shear Connectors Embedded in Normal and High-Strength Concrete

Shariati, Mahdi ; Mafipour, Mohammad Saeed ; Mehrabi, Peyman ; Bahadori, Alireza ; Zandi, Yousef ; Salih, Musab N A ; Nguyen, Hoang ; Dou, Jie ; Song, Xuan ; Poi-Ngian, Shek

Applied sciences, 2019-12, Vol.9 (24), p.5534 [Periódico revisado por pares]

Basel: MDPI AG

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3
A Novel Assisted Artificial Neural Network Modeling Approach for Improved Accuracy Using Small Datasets: Application in Residual Strength Evaluation of Panels with Multiple Site Damage Cracks
A Novel Assisted Artificial Neural Network Modeling Approach for Improved Accuracy Using Small Datasets: Application in Residual Strength Evaluation of Panels with Multiple Site Damage Cracks
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A Novel Assisted Artificial Neural Network Modeling Approach for Improved Accuracy Using Small Datasets: Application in Residual Strength Evaluation of Panels with Multiple Site Damage Cracks

Hijazi, Ala ; Al-Dahidi, Sameer ; Altarazi, Safwan

Applied sciences, 2020-11, Vol.10 (22), p.8255 [Periódico revisado por pares]

Basel: MDPI AG

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4
Development of Two Novel Hybrid Prediction Models Estimating Ultimate Bearing Capacity of the Shallow Circular Footing
Development of Two Novel Hybrid Prediction Models Estimating Ultimate Bearing Capacity of the Shallow Circular Footing
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Development of Two Novel Hybrid Prediction Models Estimating Ultimate Bearing Capacity of the Shallow Circular Footing

Moayedi, Hossein ; Kalantar, Bahareh ; Dounis, Anastasios ; Tien Bui, Dieu ; Foong, Loke Kok

Applied sciences, 2019-11, Vol.9 (21), p.4594 [Periódico revisado por pares]

Basel: MDPI AG

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5
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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6
A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm
A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm
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A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm

Adam, Abdullahi Abbas ; Soleimani, Hassan ; Shukur, Muhammad Fadhlullah Bin Abd ; Dennis, John Ojur ; Abdulkadir, Bashir Abubakar ; Hassan, Yarima Mudassir ; Yusuf, Jemilat Yetunde ; Shamsuri, Nurrul Asyiqin Bt

Journal of non-crystalline solids, 2022-07, Vol.587, p.121597, Article 121597 [Periódico revisado por pares]

Elsevier B.V

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7
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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8
Effect of machinability, microstructure and hardness of deep cryogenic treatment in hard turning of AISI D2 steel with ceramic cutting
Effect of machinability, microstructure and hardness of deep cryogenic treatment in hard turning of AISI D2 steel with ceramic cutting
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Effect of machinability, microstructure and hardness of deep cryogenic treatment in hard turning of AISI D2 steel with ceramic cutting

Kara, Fuat ; Karabatak, Mustafa ; Ayyıldız, Mustafa ; Nas, Engin

Journal of materials research and technology, 2020-01, Vol.9 (1), p.969-983 [Periódico revisado por pares]

Elsevier B.V

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9
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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10
Performance and optimization of bio-oil/Buton rock asphalt composite modified asphalt
Performance and optimization of bio-oil/Buton rock asphalt composite modified asphalt
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Performance and optimization of bio-oil/Buton rock asphalt composite modified asphalt

Lv, Songtao ; Yuan, Jiang ; Peng, Xinghai ; Borges Cabrera, Milkos ; Guo, Shuaicheng ; Luo, Xinzi ; Gao, Junfeng

Construction & building materials, 2020-12, Vol.264, p.120235, Article 120235 [Periódico revisado por pares]

Elsevier Ltd

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