Predictive Modelling of Gas Turbine Emissions based on Generalized Regression Neural Network Method Approach-Reference-Cited by-同舟云学术

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Predictive Modelling of Gas Turbine Emissions based on Generalized Regression Neural Network Method Approach

Published:2024-08-06 Issue: Volume: Page:379-385
ISSN:
Container-title:2024 International Electronics Symposium (IES)
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Author:

Winarto Rudy¹,Purnomo Mauridhi Hery²,Anggraeni Wiwik³

Affiliation:

1. Sepuluh Nopember Institute of Technology,School of Interdisciplinary Management and Technology,Surabaya,Indonesia

2. Sepuluh Nopember Institute of Technology,Department of Electrical Engineering,Surabaya,Indonesia

3. Sepuluh Nopember Institute of Technology,Department of Information System,Surabaya,Indonesia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10665754/10665755/10665804.pdf?arnumber=10665804

Reference11 articles.

1. Data Analysis and Symbolic Regression Models for Predicting CO and NOx Emissions from Gas Turbines

2. PEMS: Monitoring NOx Emissions from Gas Turbines;Hung,1995

3. Predicting CO and NOxemissions from gas turbines: novel data and abenchmark PEMS

4. Presented at the 19 th Symposium on Industrial Application of Gas Turbines (IAGT) Data from Predictive Emission Modules Implemented on GE-LM1600, GE-LM2500 and RR-RB211Gas Turbines Employed in Natural Gas Compressor Stations;Botros

5. Development of Predictive Emissions Monitoring System Using Open Source Machine Learning Library – Keras: A Case Study on a Cogeneration Unit

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