Automatic modeling of a gas turbine using genetic programming: An experimental study

详细信息    查看全文

• 作者：Josué ; Enrí ; quez-Zá ; rate^a ; ^{jenriquezza@conacyt.mx} ; Leonardo Trujillo^b ; ^{leonardo.trujillo@tectijuana.edu.mx} ; Salvador de Lara^c ; ^{sdelara@iie.org.mx} ; Mauro Castelli^d ; ^{mcastelli@novaims.unl.pt} ; Emigdio Z-Flores^b ; ^{emigdioz@gmail.com} ; Luis Muñ ; oz^b ; ^{lmunoz@tectijuana.edu.mx} ; Ale&scaron ; Popovič^d ; ^e ; ^{ales.popovic@ef.uni-lj.si}
• 关键词：Gas turbine ; Data-driven modeling ; Genetic programming ; Local search
• 刊名：Applied Soft Computing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：50
• 期：Complete
• 页码：212-222
• 全文大小：1720 K
• 卷排序：50

文摘

The behavior of a real gas turbine is modeled using GP. Several state-of-the-art GP algorithms are compared. Results show that standard GP with local search outperforms recent variants.