Adaptive parameter inversion analysis method of rockfill dam based on harmony search algorithm and mixed multi-output relevance vector machine

Abstract

Purpose To improve the efficiency, accuracy and adaptivity of the parameter inversion analysis method of a rockfill dam, this study aims to establish an adaptive model based on a harmony search algorithm (HS) and a mixed multi-output relevance vector machine (MMRVM). Design/methodology/approach By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. Therefore, the finite element method with time consumption can be replaced by the MMRVM. Because of its excellent global search capability, the HS is used to optimize the kernel parameters of the MMRVM and the material parameters of a rockfill dam. Findings Because the parameters of the HS and the variation range of the MMRVM parameters are relatively fixed, the HS-MMRVM can imbue the inversion analysis with adaptivity; the number of observation points required and the robustness of the HS-MMRVM are analyzed. An application example involving a concrete-faced rockfill dam shows that the HS-MMRVM exhibits high accuracy and high speed in the parameter inversion analysis of static and creep constitutive models. Practical implications The applicability of the HS-MMRVM in hydraulic engineering is proved in this paper, which should further validate in inversion problems of other fields. Originality/value An adaptive inversion analysis model is established to avoid the parameters of traditional methods that need to be set by humans, which strongly affect the inversion analysis results. By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. To reduce the data dimensions and verify the model’s robustness, the number of observation points required for inversion analysis and the acceptable degree of noise are determined. The confidence interval is built to monitor dam settlement and provide the foundation for dam monitoring and reservoir operation management.

Optimization of Reservoir Level Scheduling Based on InSAR-LSTM Deformation Prediction Model for Rockfill Dams

“…However, they do not accurately reflect the overall deformation of a dam. Some scholars have used numerical simulations to reconstruct the deformation characteristics of an entire dam using similar methods, provided that the design and construction parameters of each part of the dam are available, and the overall deformation is calculated via computer simulations [9,10]. Currently, many rockfill dams were built and put into operation worldwide so early that some of the dam parameters are missing, and this method cannot be used.…”

Solving Multi-Objective Two-Sided Assembly Line Balancing Problems by Harmony Search Algorithm Based on Pareto Entropy

“…The Harmony Search Algorithm is a non-derivative metaheuristic algorithm, which simulates the improvisation process of a musician [49]. Although the HS algorithm is relatively simple, it has been proved to be competitive with more complex optimization algorithms and has been applied to solve many practical problems.…”