Authors: Pijush Samui; Aditi Palsapure; Sanjiban Sekhar Roy
Addresses: Department of Civil Engineering, National Institute of Technology, Patna, Bihar, India ' Department of Civil and Environmental Engineering, Stanford University, USA ' School of Computer Science and Engineering, VIT University, Vellore-632014, India
Abstract: Foundation settlement is an important design criterion as it affects the durability of a structure. Conventional methodologies calculate only a global factor of safety to determine the safety of the structure. However this does not account for the uncertainties due to soil variability and measurement errors. Therefore reliability based design principles must be incorporated to determine the performance and reliability of a structure. The first order second moment method (FOSM) is generally used for this analysis but it is time consuming. On the other hand, relevance vector machine (RVM) achieves very good generalisation performance. Thus in our study we have used RVM-based FOSM and ELM and compared the results obtained from both. For this, a dataset of 480 readings was developed for cohesive frictional soil taking Poissons ratio and elastic modulus parameters as random variables. Readings used for training was 70% and 30% were used for testing. Normalised data was used. Additionally, several error and correlation functions were also calculated to assess the performance of the models.
Keywords: settlement; reliability analysis; first order second moment method; FOSM; relevance vector machine; RVM; extreme learning machine; ELM.
International Journal of Advanced Intelligence Paradigms, 2023 Vol.24 No.3/4, pp.369 - 379
Received: 28 Nov 2016
Accepted: 01 Dec 2017
Published online: 01 Mar 2023 *