Feedback analysis of tunnel construction using a hybrid arithmetic based on Support Vector Machine and Particle Swarm Optimisation

Jiang, Anyan; Wang, Shanyong; Tang, Shi Bin

doi:10.1016/j.autcon.2010.11.016

Cited by 51 publications

(20 citation statements)

References 20 publications

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“…Moreover, determination of the network architecture is complex when using ANNs because trial-and-error is always needed, and ANNs have the problem of over fitting in many cases [10]. Support vector machines (SVMs) [11], as a machine learning technique, are also used in geomechanical back analysis [12], prediction of settlement of shallow foundation [13], tunnel deformation control [14] and other geotechnical areas.…”

Section: Introductionmentioning

confidence: 99%

Modeling of shield-ground interaction using an adaptive relevance vector machine

Wang

Gou

et al. 2016

Applied Mathematical Modelling

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Highlights  The developed model considers soil behavior in response to tunnel excavation.  Adaptive feature scaling factors are adopted to improve model performance. The relative importance of features related to ground settlement is prioritized. The model parameters can be determined automatically in the training process. ABSTRACTShield tunneling method is widely adopted in tunneling projects. Analysis of ground settlement is required as an effective way for minimizing the potential damage caused by tunneling. Many efforts have been devoted for this purpose using various methods such as empirical approaches and numerical modeling. However, there are multiple factors that may influence the ground settlement, and the shield-ground relationship is highly non-linear and complex. To understand the complex soil Moreover, the implementation of the adaptive RVM model is relatively simple. There is no need to set model parameters because they can be automatically optimized during model training, which makes the method a practical tool for geotechnical engineers to evaluate ground reactions during tunnel excavation.

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Section: Introductionmentioning

confidence: 99%

Modeling of shield-ground interaction using an adaptive relevance vector machine

Wang

Gou

et al. 2016

Applied Mathematical Modelling

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“…Several computational approaches have been used in previous studies, e.g. Arai, Ohta, and Yasui (1983), Gioda and Sakurai (1987), Ichikawa and Ohkami (1992), Honjo, Tsung, and Guha (1994), Ohkami and Swoboda (1995), Swoboda et al (1999), Xiang, Swoboda, and Cen (2003), Chaparro et al (2008), Jiang, Wang, and Tang (2010), etc. Only static analysis is considered in *Corresponding author.…”

Section: Introductionmentioning

confidence: 99%

Second-order adjoint equation method for parameter identification of rock based on blast waves in tunnel excavation

Motoyama

Mikame

Nojima

et al. 2013

Engineering Optimization

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The objective of this study is to present a method for identifying the elastic moduli of ground rock via the first-and second-order adjoint methods using blast vibration measurements during tunnel excavation. For identifying these parameters, the magnitudes of the blast force should be identified beforehand. Parameter identification is a minimization problem of the square sum of the discrepancy between the computed and observed velocities. The magnitudes of the three components of borehole pressure are assumed to be independent in each direction. The propagation of an elastic wave is assumed because the amplitude of such a wave is infinitesimal. The three-dimensional finite element method and the linear acceleration method are used effectively. The extended performance function can be expanded into a series of small constants to derive the necessary condition of minimization. The adjoint equation and the dynamic equation of motion can be used to obtain the gradient and the Hessian product of the extended performance function with respect to the parameters. The weighted gradient method and Broyden-Flecher-Goldfarb-Shanno method are successfully employed for the minimization. By applying the present identification technique at the Ohyorogi tunnel site, the fact that the computed and observed velocities are well in agreement is verified. The present method can be shown to be useful for tunnel excavation.

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“…They base their learning on statistics in order to solve multidimensional functions whose domain is previously delimited as explained in Jiang et al (2011). However, its working procedure is "hidden" from user in the same way it was in ANN, so it is not suitable in developing a tool aimed to aid new professionals and to help them in their formation.…”

Section: Why An Expert System?mentioning

confidence: 99%

“…However, recent investigations on genetic algorithms like Cheng et al (2002) and particle swarm method presented in Zhang and Xing (2010) or Jiang et al (2011) among many others, suggest them to be widely used in the development of the future most complex decision-making tools.…”

Section: Review On Artificial Intelligence In Construction and Aim Ofmentioning

confidence: 99%

“…OLSC (On-Line System for Construction) for multi-criteria analysis presented by Kaklauskas (2007); CoSPES (Construction Site Preparation Expert System) for construction tasks written by Albert and Wu (1997); CONBPS by Poon (2004); for construction project supplies there are many example like Kumaraswamy and Dissanayaka (2001); for determining the rippability of rocks in Tiryaki (2007); for adapting tunnel construction in base of its displacements using Support Vector Machine (SVM) together with a particle swarm as shown in Jiang et al (2011); or a fuzzy multi-objective particle swarm to optimise timecost-quality in construction presented in Zhang and Xing (2010).…”

Section: Review On Artificial Intelligence In Construction and Aim Ofmentioning

confidence: 99%

See 1 more Smart Citation

Aided Diagnosis of Structural Pathologies with an Expert System

Bernat

Gil

2013

Advances in Structural Engineering

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Sustainability and safety are social demands for long-life buildings. Suitable inspection and maintenance tasks on structural elements are needed for keeping buildings safely in service. Any malfunction that causes structural damage could be called pathology by analogy between structural engineering and medicine.Even the easiest evaluation tasks require expensive training periods that may be shortened with a suitable tool. This work presents an expert system (called Doctor House or DH) for diagnosing pathologies of structural elements in buildings. DH differs from other expert systems when it deals with uncertainty in a far easier but still useful way and it is capable of aiding during the initial survey 'in situ', when damage should be detected at a glance. DH is a powerful tool that represents complex knowledge gathered from bibliography and experts.Knowledge codification and uncertainty treatment are the main achievements presented. Finally, DH was tested and validated during real surveys.

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Feedback analysis of tunnel construction using a hybrid arithmetic based on Support Vector Machine and Particle Swarm Optimisation

Cited by 51 publications

References 20 publications

Modeling of shield-ground interaction using an adaptive relevance vector machine

Modeling of shield-ground interaction using an adaptive relevance vector machine

Second-order adjoint equation method for parameter identification of rock based on blast waves in tunnel excavation

Aided Diagnosis of Structural Pathologies with an Expert System

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