Prediction of CO and NOx Emission from Gas Turbine Using Machine Learning

Title

Prediction of CO and NOx Emission from Gas Turbine Using Machine Learning

Creator

Karthick, K.; Aruna, S.K.; Ravivarman, S.

Description

In gas-turbine-based power plants, predictive emission monitoring systems (PEMS) are used to validate and back up the expensive continuous emission monitoring systems. Increasing energy consumption increased deforestation and carbon and flue gas emissions, harming the environment. The availability of relevant and ecologically sound data is crucial to their successful deployment. In this article, we adopted the Gas Turbine CO and NOx Emission Data Set Data Set from UCI machine learning repository to predict the CO And NOx emission from gas turbine using machine learning (ML). We developed the model using random forest and support vector algorithms. The random forest algorithm performs better for the data. 2025 Author(s).

Source

AIP Conference Proceedings;Volume;3137;Issue;1;Article No.;20037;

Date

01-01-2025

Publisher

American Institute of Physics

Subject

Machine Learning; Prediction Model; Prediction of CO and NOx Emission

Coverage

Karthick K., Department of Electrical and Electronics Engineering, GMR Institute of Technology, Andhra Pradesh, Rajam, India; Aruna S.K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Ravivarman S., Department of Electrical and Electronics Engineering, Vardhaman College of Engineering, Shamshabad, Telangana, Hyderabad, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 0094243X;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1063/5.0262087

https://www.scopus.com/pages/publications/105001959194?origin=resultslist