Open Access
Issue
BIO Web Conf.
Volume 97, 2024
Fifth International Scientific Conference of Alkafeel University (ISCKU 2024)
Article Number 00078
Number of page(s) 11
DOI https://doi.org/10.1051/bioconf/20249700078
Published online 05 April 2024
  • Adebiyi, A.A., Adewumi, A.O., and Ayo, C.K., (2014). Comparison of ARIMA and Artificial Neural Networks Models. Journal of Applied Mathematics. [Google Scholar]
  • Farizawani, A.G., Puteh, M., Marina, Y., Rivaie, A., (2020). A review of artificial neural network learning rule based on multiple variants of conjugate gradient approaches. Journal of Physics: Conference Series. [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]
  • Hansen, J.V., Mcdonald, J.B., Nelson, R.D., (1999). Time series prediction with genetic-algorithm designed neural networks. Computational Intelligence. 15(3): 171–184. [CrossRef] [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]
  • Kumar, P., Sharma, P., (2014). Artificial Neural Networks-A Study. International Journal of Emerging Engineering Research and Technology. 2(2): 143–148. [Google Scholar]
  • Mahalingaraya, Rathod, S., Sinha, K., Shekhawat, R.S., Chavan, S., (2018). Statistical Modelling and Forecasting of Total Fish Production of India: A Time Series Perspective. International Journal of Current Microbiology and Applied Sciences. 7(03): 1698–1707. [CrossRef] [Google Scholar]
  • Merh, N., Saxena, P.V., Pardasani, K.R., (2010). A comparison between hybrid approaches ofANN and ARIMA for Indian stock trend forecasting. Business Intelligence Journal. 3(2): 22–43. [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]
  • Niedbala, G., (2019). Simple model based on Artificial Neural Network for early prediction and simulation of winter rapeseed yield. Journal of Integrative Agriculture. 18(1): 54–61. [CrossRef] [Google Scholar]
  • Niedbala, G., Kozlowski, R.J., (2019). Application of Artificial Neural Networks for Multi-Criteria Yield Prediction of Winter Wheat. Journal of Agricultural Science and Technology. 21: 51–61. [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]
  • Yao, J.T., Tan, C.L., Poh, H.L., (1999). Neural networks for technical analysis: a study on KLCI. International Journal of Theoretical and Applied Finance. 2(2): 221–241. [CrossRef] [Google Scholar]

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