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ORCIDPanagiotis G. Asteris
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2020 – today
- 2024
[j24]Abidhan Bardhan, Nazli Tunar Ozcan
, Panagiotis G. Asteris, Candan Gokceoglu:
Hybrid ensemble paradigms for estimating tunnel boring machine penetration rate for the 10-km long Bahce-Nurdagi twin tunnels. Eng. Appl. Artif. Intell. 136: 108997 (2024)- 2023
- [j23]Wael Mahmood, Ahmed Salih Mohammed, Panagiotis G. Asteris, Hawreen Ahmed:
Soft computing technics to predict the early-age compressive strength of flowable ordinary Portland cement. Soft Comput. 27(6): 3133-3150 (2023) - 2022
- [j22]Jiandong Huang, Panagiotis G. Asteris, Siavash Manafi Khajeh Pasha, Ahmed Salih Mohammed, Mahdi Hasanipanah:
A new auto-tuning model for predicting the rock fragmentation: a cat swarm optimization algorithm. Eng. Comput. 38(3): 2209-2220 (2022) - [j21]Tien-Thinh Le, Panagiotis G. Asteris, Minas E. Lemonis:
Prediction of axial load capacity of rectangular concrete-filled steel tube columns using machine learning techniques. Eng. Comput. 38(4): 3283-3316 (2022) - [j20]Jue Zhao, Hoang Nguyen, Trung Nguyen-Thoi, Panagiotis G. Asteris, Jian Zhou:
Improved Levenberg-Marquardt backpropagation neural network by particle swarm and whale optimization algorithms to predict the deflection of RC beams. Eng. Comput. 38(5): 3847-3869 (2022) - [j19]Hong Zhang, Hoang Nguyen, Xuan-Nam Bui, Biswajeet Pradhan, Panagiotis G. Asteris, Romulus Costache, Jagannath Aryal:
A generalized artificial intelligence model for estimating the friction angle of clays in evaluating slope stability using a deep neural network and Harris Hawks optimization algorithm. Eng. Comput. 38(5): 3901-3914 (2022) - [j18]Maryam Parsajoo, Danial Jahed Armaghani, Panagiotis G. Asteris:
A precise neuro-fuzzy model enhanced by artificial bee colony techniques for assessment of rock brittleness index. Neural Comput. Appl. 34(4): 3263-3281 (2022) - 2021
- [j17]Bo Ke, Manoj Khandelwal, Panagiotis G. Asteris, Athanasia D. Skentou, Anna Mamou, Danial Jahed Armaghani:
Rock-Burst Occurrence Prediction Based on Optimized Naïve Bayes Models. IEEE Access 9: 91347-91360 (2021) - [j16]Payam Sarir, Jun Chen, Panagiotis G. Asteris, Danial Jahed Armaghani, Mahmood M. D. Tahir:
Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns. Eng. Comput. 37(1): 1-19 (2021) - [j15]Jin Duan, Panagiotis G. Asteris, Hoang Nguyen, Xuan-Nam Bui, Hossein Moayedi:
A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model. Eng. Comput. 37(4): 3329-3346 (2021) - [j14]Iman Rahimi, Amir H. Gandomi, Panagiotis G. Asteris, Fang Chen:
Analysis and Prediction of COVID-19 Using SIR, SEIQR, and Machine Learning Models: Australia, Italy, and UK Cases. Inf. 12(3): 109 (2021) - [j13]Hai-Bang Ly, Binh Thai Pham, Lu Minh Le, Tien-Thinh Le, Vuong Minh Le, Panagiotis G. Asteris:
Estimation of axial load-carrying capacity of concrete-filled steel tubes using surrogate models. Neural Comput. Appl. 33(8): 3437-3458 (2021) - [j12]Danial Jahed Armaghani, Panagiotis G. Asteris:
A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength. Neural Comput. Appl. 33(9): 4501-4532 (2021) - [j11]Panagiotis G. Asteris, Mohammadreza Koopialipoor, Danial Jahed Armaghani, Evgenios A. Kotsonis, Paulo B. Lourenço:
Prediction of cement-based mortars compressive strength using machine learning techniques. Neural Comput. Appl. 33(19): 13089-13121 (2021) - [j10]Hooman Harandizadeh, Danial Jahed Armaghani, Panagiotis G. Asteris, Amir H. Gandomi:
TBM performance prediction developing a hybrid ANFIS-PNN predictive model optimized by imperialism competitive algorithm. Neural Comput. Appl. 33(23): 16149-16179 (2021) - [j9]Panagiotis G. Asteris, Liborio Cavaleri, Hai-Bang Ly, Binh Thai Pham:
Surrogate models for the compressive strength mapping of cement mortar materials. Soft Comput. 25(8): 6347-6372 (2021) - [j8]Zimu Li, Behnam Yazdani Bejarbaneh, Panagiotis G. Asteris, Mohammadreza Koopialipoor, Danial Jahed Armaghani, Mahmood M. D. Tahir:
A hybrid GEP and WOA approach to estimate the optimal penetration rate of TBM in granitic rock mass. Soft Comput. 25(17): 11877-11895 (2021) - 2020
- [j7]Chun Bai, Hoang Nguyen, Panagiotis G. Asteris, Trung Nguyen-Thoi, Jian Zhou:
A refreshing view of soft computing models for predicting the deflection of reinforced concrete beams. Appl. Soft Comput. 97(Part B): 106831 (2020) - [j6]Panagiotis G. Asteris, Vaseilios G. Mokos:
Concrete compressive strength using artificial neural networks. Neural Comput. Appl. 32(15): 11807-11826 (2020)
2010 – 2019
- 2019
- [j5]Panagiotis G. Asteris, Mehdi Nikoo:
Artificial bee colony-based neural network for the prediction of the fundamental period of infilled frame structures. Neural Comput. Appl. 31(9): 4837-4847 (2019) - [j4]Panagiotis G. Asteris, Konstantinos G. Kolovos:
Self-compacting concrete strength prediction using surrogate models. Neural Comput. Appl. 31(S-1): 409-424 (2019) - 2018
- [c2]Panagiotis G. Asteris, Ioannis Argyropoulos, Liborio Cavaleri, Hugo Rodrigues, Humberto Varum, Job Thomas, Paulo B. Lourenço:
Masonry Compressive Strength Prediction Using Artificial Neural Networks. TMM_CH (2) 2018: 200-224 - [c1]Athanasia D. Skentou, Maria G. Douvika, Ioannis Argyropoulos, Maria Apostolopoulou, Antonia I. Moropoulou, Panagiotis G. Asteris:
Assessment of Masonry Structures Based on Analytical Damage Indices. TMM_CH (1) 2018: 513-531 - 2017
- [j3]Panagiotis G. Asteris, Vagelis Plevris:
Anisotropic masonry failure criterion using artificial neural networks. Neural Comput. Appl. 28(8): 2207-2229 (2017) - [j2]Panagiotis G. Asteris, Panayiotis C. Roussis, Maria G. Douvika:
Feed-Forward Neural Network Prediction of the Mechanical Properties of Sandcrete Materials. Sensors 17(6): 1344 (2017) - 2016
- [j1]Panagiotis G. Asteris, Athanasios K. Tsaris, Liborio Cavaleri, Constantinos C. Repapis, Angeliki Papalou, Fabio Di Trapani, Dimitrios F. Karypidis:
Prediction of the Fundamental Period of Infilled RC Frame Structures Using Artificial Neural Networks. Comput. Intell. Neurosci. 2016: 5104907:1-5104907:12 (2016)
Coauthor Index
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last updated on 2024-10-07 21:17 CEST by the dblp team
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