Dr. Saeid Shabanlou – Graph Data Structures

Academician/Research Scholar

Congratulations,Dr. Saeid Shabanlou- Graph Data Structures and Algorithms , on winning the esteemed Best Researcher Award from Sfconference! Your dedication, innovative research, and scholarly contributions have truly made a significant impact in your field. Your commitment to advancing knowledge and pushing the boundaries of research is commendable. Here’s to your continued success in shaping the future of academia and making invaluable contributions to your field. Well done!

Wishing you continued success and many more milestones in your illustrious research journey. Your impact on the field is truly commendable and serves as a beacon of inspiration for aspiring researchers.

Warmest congratulations once again on this well-deserved recognition!

Professional Profiles:

• Orcid
• ResearchGate Profile
• Linkedin
• Google scholar
• scopus

Education:

• • Kermanshah Branch, Islamic Azad University
  • Saeid Shabanlou currently works at the Department of Water, Islamic Azad University Kermanshah Branch. Saeid does research in Water Resources, Environmental Engineering and Civil Engineering. Their current project is ‘WEAP 2015 Water Evaluation And Planning System.’

publication;

1. Simulation of groundwater level using MODFLOW, extreme learning machine and Wavelet-Extreme Learning Machine models
2. Combination of computational fluid dynamics, adaptive neuro-fuzzy inference system, and genetic algorithm for predicting discharge coefficient of rectangular side orifices.

3.A novel approach for prediction of monthly ground water level using a hybrid wavelet and non-tuned self-adaptive machine learning model

4.Free surface and velocity field in a circular channel along the side weir in supercritical flow conditions

5.A pareto design of evolutionary hybrid optimization of ANFIS model in prediction abutment scour depth

6.The flow pattern in triangular channels along the side weir for subcritical flow regime

7.A comparative study of artificial intelligence models and a statistical method for groundwater level prediction

8.A novel approach using CFD and neuro-fuzzy-firefly algorithm in predicting labyrinth weir discharge coefficient

9.Determining the scour dimensions around submerged vanes in a 180 bend with the gene expression programming technique

10.Modelling qualitative and quantitative parameters of groundwater using a new wavelet conjunction heuristic method: wavelet extreme learning machine versus wavelet neural networks