Prediction of curtain grouting efficiency based on ANFIS

Li, Xiaochao; Zhong, Dexing; Ren, Bingyu; Fan, Guichao; Cui, Bo

doi:10.1007/s10064-017-1039-y

Cited by 26 publications

(5 citation statements)

References 61 publications

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“…Chen et al (2018) [31] developed a structural safety evaluation system for in-service tunnels by using ANFIS and the results demonstrated that the evaluation system had high implementation and learning capabilities. Li et al (2019) [32] designed a model based on ANFIS to predict and estimate curtain grouting efficiency, the essential process for improving dam foundations to reduce the deformability of rock masses. Moghayedi and Windapo (2019) [23] used an ANFIS, a dependable, and precise advanced machine learning technique, which has been developed based on the data acquired to analyze the influence of uncertainty events on the complete duration of highway construction projects.…”

Section: Background and Related Work A Adaptive Neuro-fuzzy Inference...mentioning

confidence: 99%

Reliable Time Contingency Estimation Based on Adaptive Neuro-Fuzzy Inference System in Construction Projects

Doungsoma,

Pawan

2023

IEEE Access

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Project scheduling is one of the most essential processes and plays a critical role in determining the success of construction projects. The reliable time contingency enables project planners to effectively address uncertainties and various types of risks that may affect the project duration. The traditional scheduling technique such as deterministic methods and probabilistic methods may not be suitable when used for planning construction projects with uncertainties and risks. This paper proposes a new framework that integrates risk management into project scheduling to establish a more reliable project schedule. The proposed model adopts the adaptive neuro-fuzzy inference system (ANFIS) called the ANFIS-TOOL to model the possibility of risk occurrences integrated with project scheduling in terms of risk lag time (ANFIS-RLT) to generate risk-integrated project duration (RPD). The learning capabilities of adaptive neural networks are utilized to adjust the parameters of the model according to the fuzzy rules, aiming to achieve the most suitable representation of the model. In a real-life case study, a sheet pile wall with a temporary bracing system (SPBS) was applied to demonstrate the application of this technique. The root mean square error (RMSE) was used to validate the accuracy of the model before being applied to real construction projects with a high degree of accuracy. This model can be used as an excellent tool to generate a more reliable schedule baseline in construction projects.INDEX TERMS Adaptive neuro-fuzzy inference system, risk management, time contingency, scheduling.

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Section: Background and Related Work A Adaptive Neuro-fuzzy Inference...mentioning

confidence: 99%

Reliable Time Contingency Estimation Based on Adaptive Neuro-Fuzzy Inference System in Construction Projects

Doungsoma,

Pawan

2023

IEEE Access

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“…So far, ANNs have been used in many areas, such as computer vision, speech recognition, machine translation, social network filtering, playing board and video games and medical diagnosis (Acharya et al 2003;Brause et al 1999;Evangelou et al 2001 Patil and Kumaraswamy 2009). In the field of civil engineering, there are also many applications, geological data was used for developing predictive model for dynamically evaluating engineering parameters, such as ground settlement, grout penetration range, where the relationship between geological data and parameters to be evaluated are highly nonlinear but the results obtained in literature were good (Li et al 2017;Suwansawat and Einstein 2006;Zhong et al 2015). The schematic diagram of ANN used in the present work is shown in Fig.…”

Section: Ann Based Modelmentioning

confidence: 99%

Evaluation of equivalent hydraulic aperture (EHA) for rough rock fractures

Xiao

Zhao

2019

Can. Geotech. J.

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Most existing models for fluid transportation within a single rock fracture tend to use a channel with two smooth parallel plates, whereas real fracture surfaces are usually rough and tortuous, which can produce a flow field significantly different from the smooth plate model. For fluid flow in a rough fracture, there are surface concave areas (SCA), where the fluid velocity is extremely low, contributing little to the fluid transportation. It is of great significance to quantitatively evaluate the impact of rough surfaces on fluid flow. Therefore, a numerical model for simulating Newtonian fluid through rough fractures is proposed, where synthetic surfaces are generated according to statistical analysis of natural rock fractures and can be quantified by several characteristic parameters. Equivalent hydraulic aperture (EHA) is proposed as one quantitative indicator for evaluating the impact of fracture roughness. Systematic studies were conducted for evaluating EHAs of rough fractures, which, combined with characteristic parameters of fractures, are used to build surrogate models for EHA prediction. It is found that the EHA is directly correlated with the fracture roughness, the mean mechanical aperture, and the standard deviation of aperture distribution. The developed surrogate models were verified to have a high accuracy for EHA prediction.

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“…Lagging grouting is an effective method to improve its stability, which improves its strength and limits its deformation [14][15][16]. At present, grouting technology has become a common reinforcement method in various geotechnical engineering applications [17][18][19][20][21]. Grouting material that matches working condition is very important in grouting engineering.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Grouting Material Mixture Ratio Based on Multi-Objective Optimization and Multi-Attribute Decision-Making

et al. 2021

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As a solid waste produced by coal combustion, fly ash will cause serious environmental pollution. However, it can be considered as a sustainable and renewable resource to replace partial cement in grouting materials. Fly ash grouting materials re-cement the broken rock mass and improve the mechanical properties of the original structure. It can reinforce the broken surrounding rock of mine roadway. The utilization of fly ash also reduces environmental pollution. Therefore, this paper establishes a new material mixture ratio optimization model to meet the requirement of material property through combining the methods of experimental design and numerical analysis. Based on the Box–Behnken design with 3 factors and 3 levels, a mathematical model is constructed to fit the nonlinear multiple regression functions between material properties and raw materials ratios. The influence of raw materials is analyzed on material properties (the material’s 7-day uniaxial compressive strength, initial setting time, and slurry viscosity). Then, 80 Pareto solutions are obtained through NASG-II algorithm which takes the regression functions as the objective functions for multi-objective optimization of the grouting material ratio. Finally, the best ratio solution of water-cement ratio—0.71, silica fume content—1.73%, and sodium silicate content—2.61% is obtained through the NNRP-TOPSIS method.

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Prediction of curtain grouting efficiency based on ANFIS

Cited by 26 publications

References 61 publications

Reliable Time Contingency Estimation Based on Adaptive Neuro-Fuzzy Inference System in Construction Projects

Reliable Time Contingency Estimation Based on Adaptive Neuro-Fuzzy Inference System in Construction Projects

Evaluation of equivalent hydraulic aperture (EHA) for rough rock fractures

Optimization of Grouting Material Mixture Ratio Based on Multi-Objective Optimization and Multi-Attribute Decision-Making

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