This application utilizes machine learning models to validate air conditioner energy efficiency tests conducted in compliance with ISO 5151. The models analyze key performance metrics, including input power, electrical current, total cooling capacity, and the energy efficiency ratio. By leveraging advanced data-driven techniques, the application enhances accuracy in assessing AC performance, ensuring reliable validation of test results.
Amr Sadek (2026). ANNS_AC_1 (https://it.mathworks.com/matlabcentral/fileexchange/181225-anns_ac_1), MATLAB Central File Exchange.
Recuperato .
Sadek, A. M., et al. “Machine Learning Models for Validating the Self-Declaration Conformity Assessment: Risk Evaluation.” Machine Learning and Soft Computing, Springer Nature Singapore, 2025, pp. 231–42, https://doi.org/10.1007/978-981-96-6400-9_17.
Sadek, A. M., et al. “Machine Learning Models for Validating the Self-Declaration Conformity Assessment: Risk Evaluation.” Machine Learning and Soft Computing, Springer Nature Singapore, 2025, pp. 231–42, https://doi.org/10.1007/978-981-96-6400-9_17.
APA
Sadek, A. M., AlRashidi, M. S., AlMutiri, Y. M., AlQahtani, A. R. M., & AlQahtani, T. S. (2025). Machine Learning Models for Validating the Self-declaration Conformity Assessment: Risk Evaluation. In Machine Learning and Soft Computing (pp. 231–242). Springer Nature Singapore. Retrieved from http://dx.doi.org/10.1007/978-981-96-6400-9_17
BibTeX
@inbook{Sadek_2025, title={Machine Learning Models for Validating the Self-declaration Conformity Assessment: Risk Evaluation}, ISBN={9789819664009}, ISSN={1865-0937}, url={http://dx.doi.org/10.1007/978-981-96-6400-9_17}, DOI={10.1007/978-981-96-6400-9_17}, booktitle={Machine Learning and Soft Computing}, publisher={Springer Nature Singapore}, author={Sadek, A. M. and AlRashidi, Mohammed S. and AlMutiri, Yousef M. and AlQahtani, AbdulRahman M. and AlQahtani, Turki S.}, year={2025}, pages={231–242} }
AlMutiri, Yousef M., et al. “Modeling the Air Conditioner Performance Tests Using Artificial Neural Network Simulator (ANNS-AC).” Artificial Intelligence Applications and Innovations, Springer Nature Switzerland, 2024, pp. 125–38, https://doi.org/10.1007/978-3-031-63223-5_10.
AlMutiri, Yousef M., et al. “Modeling the Air Conditioner Performance Tests Using Artificial Neural Network Simulator (ANNS-AC).” Artificial Intelligence Applications and Innovations, Springer Nature Switzerland, 2024, pp. 125–38, https://doi.org/10.1007/978-3-031-63223-5_10.
APA
AlMutiri, Y. M., AlRashidi, M. S., AlQahtani, A. R. M., Alqahtani, T. S., & Sadek, A. M. (2024). Modeling the Air Conditioner Performance Tests Using Artificial Neural Network Simulator (ANNS-AC). In Artificial Intelligence Applications and Innovations (pp. 125–138). Springer Nature Switzerland. Retrieved from http://dx.doi.org/10.1007/978-3-031-63223-5_10
BibTeX
@inbook{AlMutiri_2024, title={Modeling the Air Conditioner Performance Tests Using Artificial Neural Network Simulator (ANNS-AC)}, ISBN={9783031632235}, ISSN={1868-422X}, url={http://dx.doi.org/10.1007/978-3-031-63223-5_10}, DOI={10.1007/978-3-031-63223-5_10}, booktitle={Artificial Intelligence Applications and Innovations}, publisher={Springer Nature Switzerland}, author={AlMutiri, Yousef M. and AlRashidi, Mohammed S. and AlQahtani, AbdulRahman M. and Alqahtani, Turki S. and Sadek, A. M.}, year={2024}, pages={125–138} }
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