A hybrid computational approach for seismic energy demand prediction

作者：

Highlights：

• An evolutionary method is proposed to formulate the energy-based engineering demand parameters.

• A multi-objective genetic programming is combined with linear regression in this framework.

• Both structural and earthquake characteristics are included in the proposed prediction models.

• For each problem, one model with four different coefficient sets is proposed for various soil types.

• A comparative study is performed to compare the model performance with other well-known models.

摘要

•An evolutionary method is proposed to formulate the energy-based engineering demand parameters.•A multi-objective genetic programming is combined with linear regression in this framework.•Both structural and earthquake characteristics are included in the proposed prediction models.•For each problem, one model with four different coefficient sets is proposed for various soil types.•A comparative study is performed to compare the model performance with other well-known models.

论文关键词：Evolutionary computation,Genetic programming,Regression analysis,Input energy,Hysteretic energy,Seismic energy spectra

论文评审过程：Received 30 November 2017, Revised 29 April 2018, Accepted 3 June 2018, Available online 4 June 2018, Version of Record 18 June 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.06.009