Engineering Data Analysis Applications Research Group

This group was created for the purpose of activating the research mobility in the College of Engineering. The group, which consists of a number of teachers in different specializations, aims to manage some research lines related to the analysis of engineering data and some of its applications such as: –

  • Fault diagnosis in rotating machines.
  • Wear detection with cutting tools.
  • Materials Acoustic properties Researches.
  • Damage assessment in structures.
  • Forecasting of water demand.
  1. Farouk O. Hamdoon*, Hussein R. Al-Bugharbee, and Azzam S. Hameed (2019). “Transient response of rotor system under different startup speed profiles”. Journal of Mechanical Engineering Research and Developments (JMERD). Vol(42), No.(5). PP 163-167.
  2. H. Al-Bugharbee; A. Jubear (2020).“An Experimental Investigation of Enclosure’s Effect on Noise Reduction in Portable Generators (Technical Note)”. IJE TRANSACTIONS B: Applications. Vol. (33), (No). 2, 350-356
  3. Zubaidi, S. L., Ortega-Martorell, S., Al-Bugharbee, H., Olier, I., Hashim, K. S., Gharghan, S. K., … & Al-Khaddar, R. (2020). Urban water demand prediction for a city that suffers from climate change and population growth: gauteng province case study. Water12(7), 1885.
  4. Zubaidi, S. L., Dooley, J., Alkhaddar, R. M., Abdellatif, M., Al-Bugharbee, H., & Ortega-Martorell, S. (2018). A Novel approach for predicting monthly water demand by combining singular spectrum analysis with neural networks. Journal of hydrology561, 136-145.
  5. Zubaidi, S. L., Abdulkareem, I. H., Hashim, K. S., Al-Bugharbee, H., Ridha, H. M., Gharghan, S. K., … & Al-Khaddar, R. (2020). Hybridised Artificial Neural Network Model with Slime Mould Algorithm: A Novel Methodology for Prediction of Urban Stochastic Water Demand. Water12(10), 2692.
  6. Zubaidi, S. L., Kot, P., Alkhaddar, R. M., Abdellatif, M., & Al-Bugharbee, H. (2018, September). Short-term water demand prediction in residential complexes: Case study in Columbia city, USA. In 2018 11th International Conference on Developments in eSystems Engineering (DeSE) (pp. 31-35). IEEE.
  7. Zubaidi, S. L., Al-Bugharbee, H., Muhsin, Y. R., Hashim, K., & Alkhaddar, R. (2020, July). Forecasting of monthly stochastic signal of urban water demand: Baghdad as a case study. In IOP Conference Series: Materials Science and Engineering (Vol. 888, No. 1, p. 012018). IOP Publishing.
  8. Zubaidi, S. L., Al-Bugharbee, H., Ortega-Martorell, S., Gharghan, S. K., Olier, I., Hashim, K. S., … & Kot, P. (2020). A Novel Methodology for Prediction Urban Water Demand by Wavelet Denoising and Adaptive Neuro-Fuzzy Inference System Approach. Water12(6), 1628.
  9. Al-Bugharbee, H., & Jubear, A. (2020). An Experimental Investigation of Enclosure’s Effect on Noise Reduction in Portable Generators. International Journal of Engineering33(2), 350-356.
  10. Samaka, H., Al-Bugharbee, H., & Al-Azawy, M. (2020). Redesign the Front Shape of the Sedan Car for Pedestrian Safety and Mitigating Leg Injuries at Accidents Redesign the Front Shape of the Sedan Car for Pedestrian Safety and Mitigating Leg Injuries at Accidents.