System Identification of a Soil Tunnel Based on a Hybrid Artificial Neural Network–Numerical Model Approach

Jafari, Marzieh

doi:10.1007/s40996-020-00405-w

Cited by 4 publications

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Due to the nature of high-speed parallel, distributed processing and the convenience of hardware implementation, neural networks have been used to replace the numerical algorithm of serial processing, and widely used in the fields of scientific and engineering (Jin et al, 2017 ; Xu et al, 2019 ; Jafari, 2020 ; Liu et al, 2020 ). Scholars have deeply studied many recurrent neural networks and parallel computing schemes for computing scientific problems including matrix pseudoinverse in real time (Li et al, 2021 ; Kornilova et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Harmonic Noise-Tolerant ZNN for Dynamic Matrix Pseudoinversion and Its Application to Robot Manipulator

Liao

Wang

et al. 2022

Front. Neurorobot.

View full text Add to dashboard Cite

As we know, harmonic noises widely exist in industrial fields and have a crucial impact on the computational accuracy of the zeroing neural network (ZNN) model. For tackling this issue, by combining the dynamics of harmonic signals, two harmonic noise-tolerant ZNN (HNTZNN) models are designed for the dynamic matrix pseudoinversion. In the design of HNTZNN models, an adaptive compensation term is adopted to eliminate the influence of harmonic noises, and a Li activation function is introduced to further improve the convergence rate. The convergence and robustness to harmonic noises of the proposed HNTZNN models are proved through theoretical analyses. Besides, compared with the ZNN model without adaptive compensation term, the HNTZNN models are more effective for tacking the problem of dynamic matrix pseudoinverse under harmonic noises environments. Moreover, HNTZNN models are further applied to the kinematic control of a four-link planar robot manipulator under harmonic noises. In general, the experimental results verify the effectiveness, superiority, and broad application prospect of the models.

show abstract

Section: Introductionmentioning

confidence: 99%

Harmonic Noise-Tolerant ZNN for Dynamic Matrix Pseudoinversion and Its Application to Robot Manipulator

Liao

Wang

et al. 2022

Front. Neurorobot.

View full text Add to dashboard Cite

show abstract

“…Demands for the construction of new metro routes, tracks, and rail transit are also rising accordingly. With the development of urban rail transit, it is unavoidable to cross the old and new metro tracks [1]. Due to congestion in urban areas and the shortage of space, the construction of more than one tunnel at one site is becoming the ultimate option.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation Algorithm Design of Influence on Existing Tunnel by Underpass Construction of New Tunnel

2021

Scientific Programming

View full text Add to dashboard Cite

Simulation is a powerful tool that can be used for systematic planning, analysis, and decision-making. Proper designing is preliminary required to construct a new tunnel over an existing tunnel to ensure safety and durability. Once an underpass tunnel completes, the interaction between the tunnel structure and the nearby soil gains a stable state and the stress of the tunnel is balanced. However, the stability of an existing tunnel is affected if the construction in the nearby area is not properly analyzed. This article proposes a numerical simulation model to empirically analyze lining force and surface settlement in order to ensure safety in engineering practice. The existing tunnel structure working condition is simulated under the new tunnel. The artificial honeybee colony algorithm is used to extract the parameter fusion characteristic value of tunnel influence and the model of estimating the bending moment of group piles. The structural mechanics of existing tunnels under new tunnels are analyzed using the triple bend model to improve the bearing capacity of existing tunnels under new tunnels. Based on the above analysis, numerical simulation experiments are designed. The proposed method has high accuracy and strong fitting ability and can effectively reduce the displacement of existing tunnels. Moreover, the method can improve the bearing capacity of tunnels. For tunneling operation, the results of the simulation may be used as a recommendation.

show abstract

Machine Learning in Computer Aided Engineering

Montáns,

Cueto,

Bathe

2023

Computational Methods in Engineering &Amp; The Sciences

View full text Add to dashboard Cite

The extraordinary success of Machine Learning (ML) in many complex heuristic fields has promoted its introduction in more analytical engineering fields, improving or substituting many established approaches in Computer Aided Engineering (CAE), and also solving long-standing problems. In this chapter, we first review the ideas behind the most used ML approaches in CAE, and then discuss a variety of different applications which have been traditionally addressed using classical approaches and that now are increasingly the focus of ML methods.

show abstract

System Identification of a Soil Tunnel Based on a Hybrid Artificial Neural Network–Numerical Model Approach

Cited by 4 publications

References 13 publications

Harmonic Noise-Tolerant ZNN for Dynamic Matrix Pseudoinversion and Its Application to Robot Manipulator

Harmonic Noise-Tolerant ZNN for Dynamic Matrix Pseudoinversion and Its Application to Robot Manipulator

Numerical Simulation Algorithm Design of Influence on Existing Tunnel by Underpass Construction of New Tunnel

Machine Learning in Computer Aided Engineering

Contact Info

Product

Resources

About