Farah Rania

Specialty: 
Informatique
Department: 
Faculty: 
Campus: Ancien Campus
Doctoral advisor: 
Google Scholar Link: 
Rersearchgate Link: 
ORCID: 

Thesis title

Doctoral thesis title: 
Prediction of electric charge with deep learning models

Thesis title (Ar)

Doctoral thesis title (Ar): 
التنبؤ بالطاقة الكهربائية باستخدام نماذج التعلّم العميق

Thesis title (Fr)

Doctoral thesis title (Fr): 
prédiction de charge électrique avec des modèles Deep Learning

keywords

Keywords: 
artificielle intelligence, deep learning, load forecasting

keywords (Ar)

Key words (Ar): 
الذكاء الاصطناعي ، التعلم العميق

keywords (Fr)

Key words (Fr): 
intelligence artificial, modeles deep learning, prédiction, charge électrique

Abstract

Abstract: 

<p>enterprises have started to use information on a large scale. this use made it possible to generate a large quantity of data to be exploited and studied. this is the case of sonalgaz which provided us with dozens of electrical load data to try to predict future consumption with deepleqrning models Research interest</p>

Abstract (Ar)

Abstract (Ar): 

<p> بدأت المؤسسات في استخدام المعلومات على نطاق واسع. جعل هذا الاستخدام من الممكن توليد كمية كبيرة من البيانات لاستغلالها ودراستها. هذه هي حالة Sonalgaz التي زودتنا بالعشرات من بيانات الحمل الكهربائي لمحاولة التنبؤ بالاستهلاك المستقبلي من خلال نماذج التعلم العميق. </ p>

Abstract (Fr)

Abstract (Fr): 

les entreprises ont commencé à utiliser l'informatique à grande échelle. cette utilisation a permis de générer une grande quantité de données à exploiter et à étudier. c'est le cas de sonalgaz qui nous a fourni des dizaines de données de charge électrique pour tenter de prédire les consommations futures avec des modèles de deep learning

Scientific publications

Scientific publications : 

Farah, R., Farou, B., Kouahla, Z., & Seridi, H. (2024). Data driven models on load forecasting: Case study Algeria. Data in Brief, 52, 109854.

Scientific conferences

Scientific conferences: 
  1. Rania, F., Brahim, F., Zineddine, K., & Hamid, S. (2023, September). A Comparison of the Finest Electrical Energy Forecast Models. In 2023 International Conference on Decision Aid Sciences and Applications (DASA) (pp. 570-575). IEEE.
  2. Rania, F., Brahim, F., Zineddine, K., & Hamid, S. (2021, December).  Load Short-Term Forecast by Linear Regression and Artificial Neural Network. In 2021 the 4th conference on informatics and applied mathematics IAM’21 held in Guelma University.
  3. Rania, F., Brahim, F., Zineddine, K., & Hamid, S. (2022, December). The Use Of Machine Learning For Load Charge Forecasting. In 2022 the 5th conference on informatics and applied mathematics IAM’21 held in Guelma University.
  4. Rania, F., Brahim, F., Zineddine, K., & Hamid, S. (2023, December).  Precision Forecasting of Electricity Consumption for Proactive Pollution Control. In 2023 the 6th conference on informatics and applied mathematics IAM’23 held in Guelma University.