Nasrin Fathollahzadeh AttarUrmia University
Nasrin Fathollahzadeh Attar
Founder of R-ladiesUrmia. Interested in extremes and stochastic models in environmental sciences.
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
I am interested in Hydrological Modelling and Prediction. I am the coordinator of online education in data science using R software. Furthermore, I was awarded as a visiting scholar by the Iranian Ministry of Foreign Affairs to the University of Adelaide, Australia. The quality of publication is my first priority. For your questions about any of my papers or projects please Contact: https://linktr.ee/nasrinattar Email: email@example.com
I want to model river flow by self threshold autoregressive model, but I don't know how should I consider these three (p,r,d)?
please help me.
I have 30 years,daily river flow data.
I want to model these time series with data driven methods like GEP.
My question is how to select my lags with discharge data
Is there any method for this purpose?
Working with these wonderful people (Vahid Naghshin, Ph. D. Marya Alizadeh Homayoon Khadivi) was my best experience as teamwork. We are fortune teller team and we participated in Global AI Innovation Challenge Series 2021 Intelligent Weather Forecast for Better Life. We are forecasting the Drought Level by using the open data offered by the NASA POWER Project and the authors of the US Drought Monitor. We have already used Alibaba Cloud services for implementing our AI Architecture on DSW Development Environment. We have developed an AI Architecture which forecasts the Drought Level with high-level accuracy. Our system is capable of Monitoring the environment, specifying the drought areas, forecasting the drought level, and alarming the authorities for the extreme events. More information Can be found at: https://lnkd.in/eCpZnRbR
This project is about optimizing cropping pattern of selected crops in Urmia lake basin with considering climate change effects and virtual water.
Developing of time series modeling (linear and nonlinear) and also new artificial intelligence techniques in Water Resources Engineering.