Work

Data-Driven Generative Model Aimed to Create Synthetic Data for the Long-Term Forecast of Gas Turbine Operation

Year: 2024

Type: article

Source: Journal of Engineering for Gas Turbines and Power

DOI: 10.1115/1.4066360

Authors: Enzo Losi, Lucrezia Manservigi, Pier Ruggero Spina, Mauro Venturini

Institution: University of Ferrara

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: closed

OpenAlex ID: W4401870248

FWCI: 1.279

Cites: 30

Cited by: 8

Related to: 10