Open Access
| Issue |
BIO Web Conf.
Volume 97, 2024
Fifth International Scientific Conference of Alkafeel University (ISCKU 2024)
|
|
|---|---|---|
| Article Number | 00142 | |
| Number of page(s) | 9 | |
| DOI | https://doi.org/10.1051/bioconf/20249700142 | |
| Published online | 05 April 2024 | |
- Afrifa-Yamoah, E., Saeed, B. I., & Karim, A. (2016). Sarima modelling and forecasting of monthly rainfall in the BrongAhafo Region of Ghana. World Environment, 6(1), 1–9. [Google Scholar]
- Cong, J., Ren, M., Xie, S., & Wang, P. (2019). Predicting seasonal influenza based on SARIMA model, in mainland China from 2005 to 2018. International journal of environmental research and public health, 16(23), 4760. [CrossRef] [PubMed] [Google Scholar]
- Al-Mahdawi, H. K., Albadran, Z., Alkattan, H., Abotaleb, M., Alakkari, K., & Ramadhan, A. J. (2023, December). Using the inverse Cauchy problem of the Laplace equation for wave propagation to implement a numerical regularization homotopy method. AIP Conference Proceedings (Vol. 2977, No. 1). AIP Publishing. [Google Scholar]
- Divisekara, R. W., Jayasinghe, G. J. M. S. R., & Kumari, K.W.S.N. (2020). Forecasting the red lentils commodity market price using SARIMA models. SN Business & Economics, 1(1), 20. [Google Scholar]
- Dubey, A. K., Kumar, A., García-Díaz, V., Sharma, A. K., & Kanhaiya, K. (2021). Study and analysis of SARIMA and LSTM in forecasting time series data. Sustainable Energy Technologies and Assessments, 47, 101474. [CrossRef] [Google Scholar]
- Kamal, Mustafa, et al. “A new updated version of the Weibull model with an application to re-injury rate data.” Alexandria Engineering Journal 83 (2023): 92–101. [CrossRef] [Google Scholar]
- Ma, S., Liu, Q., & Zhang, Y. (2021). A prediction method of fire frequency: Based on the optimization of SARIMA model. PLoS one, 16(8), e0255857. [CrossRef] [PubMed] [Google Scholar]
- Al-Nuaimi, B. T., Al-Mahdawi, H. K., Albadran, Z., Alkattan, H., Abotaleb, M., & El-Kenawy, E.S.M. (2023). Solving of the inverse boundary value problem for the heat conduction equation in two intervals of time. Algorithms, 16(1), 33. [CrossRef] [Google Scholar]
- Akbari, E., Mollajafari, M., Al-Khafaji, H. M. R., Alkattan, H., Abotaleb, M., Eslami, M., & Palani, S. (2022). Improved salp swarm optimization algorithm for damping controller design for multimachine power system. IEEE Access, 10, 82910–82922. [CrossRef] [Google Scholar]
- Nai, W., Liu, L., Wang, S., & Dong, D. (2017). An EMD-SARIMA-based modeling approach for air traffic forecasting. Algorithms, 10(4), 139. [CrossRef] [Google Scholar]
- Nasiru, S., Luguterah, A., & Anzagra, L. (2013). The efficacy of ARIMAX and SARIMA models in predicting monthly currency in circulation in Ghana. Mathematical Theory and Modeling, 3(5), 73–81. [Google Scholar]
- Qiu, H., Zhao, H., Xiang, H., Ou, R., Yi, J., Hu, L., …& Ye, M. (2021). Forecasting the incidence of mumps in Chongqing based on a SARIMA model. BMC Public Health, 21(1), 1–12. [CrossRef] [PubMed] [Google Scholar]
- Ehsan Khodadadi, S.K. Towfek, Hussein Alkattan. (2023). Brain Tumor Classification Using Convolutional Neural Network and Feature Extraction. Fusion: Practice and Applications, 13(2), 34–41. [CrossRef] [Google Scholar]
- Xu, F., Du, Y. A., Chen, H., & Zhu, J. M. (2021). Prediction of fish migration caused by ocean warming based on SARIMA model. Complexity, 2021, 1–9. [Google Scholar]
- Yang, Y., Zheng, H., & Zhang, R. (2017, September). Prediction and analysis of aircraft failure rate based on SARIMA model. In 2017 2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA) (pp. 567–571). IEEE. [CrossRef] [Google Scholar]
- Yang, Y., Zheng, H., & Zhang, R. (2017, September). Prediction and analysis of aircraft failure rate based on SARIMA model. In 2017 2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA) (pp. 567–571). IEEE. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.