Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

A Revision of Empirical Models of Stirling Engine Performance Using Simple Artificial Neural Networks

Enrique González-Plaza, David García and Jesús-Ignacio Prieto
Inventions 8 (4) 88 (2023)
https://doi.org/10.3390/inventions8040088

Review of artificial neural networks for gasoline, diesel and homogeneous charge compression ignition engine

Ibham Veza, Asif Afzal, M.A. Mujtaba, et al.
Alexandria Engineering Journal 61 (11) 8363 (2022)
https://doi.org/10.1016/j.aej.2022.01.072

Design optimization of a heat‐to‐cool Stirling cycle using artificial neural network

Mohammad Hadi Katooli, Reza Askari Moghadam and Mehdi Mehrpooya
International Journal of Energy Research 46 (8) 10894 (2022)
https://doi.org/10.1002/er.7890

Design and optimization of Stirling engines using soft computing methods: A review

Shahryar Zare, A.R. Tavakolpour-saleh, A. Aghahosseini, M.H. Sangdani and Reza Mirshekari
Applied Energy 283 116258 (2021)
https://doi.org/10.1016/j.apenergy.2020.116258

Precise prediction of biogas thermodynamic properties by using ANN algorithm

Mahmood Farzaneh-Gord, Behnam Mohseni-Gharyehsafa, Ahmad Arabkoohsar, Mohammad Hossein Ahmadi and Mikhail A. Sheremet
Renewable Energy 147 179 (2020)
https://doi.org/10.1016/j.renene.2019.08.112

Development of Simple-to-Use Predictive Models to Determine Thermal Properties of Fe2O3/Water-Ethylene Glycol Nanofluid

Mohammad Hossein Ahmadi, Ali Ghahremannezhad, Kwok-Wing Chau, et al.
Computation 7 (1) 18 (2019)
https://doi.org/10.3390/computation7010018

A review on the applications of intelligence methods in predicting thermal conductivity of nanofluids

Mahdi Ramezanizadeh, Mohammad Alhuyi Nazari, Mohammad Hossein Ahmadi, Giulio Lorenzini and Ioan Pop
Journal of Thermal Analysis and Calorimetry (2019)
https://doi.org/10.1007/s10973-019-08154-3

A neural network-based scheme for predicting critical unmeasurable parameters of a free piston Stirling oscillator

Alireza Shourangiz-Haghighi and A.R. Tavakolpour-Saleh
Energy Conversion and Management 196 623 (2019)
https://doi.org/10.1016/j.enconman.2019.06.035

Applicability of connectionist methods to predict thermal resistance of pulsating heat pipes with ethanol by using neural networks

Mohammad Hossein Ahmadi, Afshin Tatar, Mohammad Alhuyi Nazari, et al.
International Journal of Heat and Mass Transfer 126 1079 (2018)
https://doi.org/10.1016/j.ijheatmasstransfer.2018.06.085

Determination of thermal conductivity ratio of CuO/ethylene glycol nanofluid by connectionist approach

Mohammad-Ali Ahmadi, Mohammad Hossein Ahmadi, Morteza Fahim Alavi, et al.
Journal of the Taiwan Institute of Chemical Engineers 91 383 (2018)
https://doi.org/10.1016/j.jtice.2018.06.003

Thermal conductivity and dynamic viscosity modeling of Fe2O3/water nanofluid by applying various connectionist approaches

Mohammad Hossein Ahmadi, Afshin Tatar, Parinaz Seifaddini, et al.
Numerical Heat Transfer, Part A: Applications 74 (6) 1301 (2018)
https://doi.org/10.1080/10407782.2018.1505092

ANN model to predict the performance of parabolic dish collector with tubular cavity receiver

Reyhaneh Loni, Alibakhsh Kasaeian, Kazem Shahverdi, et al.
Mechanics & Industry 18 (4) 408 (2017)
https://doi.org/10.1051/meca/2017016