Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Alarms prediction and classification in industrial processes using supervised machine learning techniques: A case study in an Algerian gas plant

Creator:
SamAliRacZak
Publisher:
Elsevier BV
Host:

Visit

doi.org

Languages

Arabic, Algerian Spoken

Licenses

https://www.elsevier.com/tdm/userlicense/1.0/https://www.elsevier.com/legal/tdmrep-licensehttps://doi.org/10.15223/policy-017https://doi.org/10.15223/policy-037https://doi.org/10.15223/policy-012https://doi.org/10.15223/policy-029https://doi.org/10.15223/policy-004

Similar

Arabic Opinion Mining Using Machine Learning Techniques: Algerian Dialect as a Case of StudyCrop Yield Prediction in Nigeria Using Machine Learning Techniques: (A Case Study of Southern Part of Nigeria)Amharic Text Complexity Classification Using Supervised Machine LearningSOLAR PHOTOVOLTAIC POWER OUTPUT PREDICTION WITH MACHINE LEARNING TECHNIQUES: CASE STUDY OF RWAMAGANA SOLAR POWER PLANT- RWANDARice Plant Nutrient Deficiency Classification Using Deep Learning TechniquesAnalysis and Prediction of Soil Fertility using Machine Learning Techniques: A Case Study of North Wollo Zone in Amhara Region

Arabic Opinion Mining Using Machine Learning Techniques: Algerian Dialect as a Case of Study

Crop Yield Prediction in Nigeria Using Machine Learning Techniques: (A Case Study of Southern Part of Nigeria)

A key tool for digitalizing the agriculture sector and other industries is using big data and machin

Amharic Text Complexity Classification Using Supervised Machine Learning

SOLAR PHOTOVOLTAIC POWER OUTPUT PREDICTION WITH MACHINE LEARNING TECHNIQUES: CASE STUDY OF RWAMAGANA SOLAR POWER PLANT- RWANDA

Solar Photovoltaic has been used for long due to potential shortage of fossil fuel energy, its effec

Rice Plant Nutrient Deficiency Classification Using Deep Learning Techniques

Analysis and Prediction of Soil Fertility using Machine Learning Techniques: A Case Study of North Wollo Zone in Amhara Region

This research aimed to analyze and predict soil fertility using machine learning techniques, focusin