Skip to Main Content
IWA Publishing Logo
header search
Search
Advanced Search
Cart
Skip Nav Destination

Automatic calibration of the groundwater simulation model with high parameter dimensionality using sequential uncertainty fitting approach

Water Supply (2020) 20 (8): 3487–3501.
This article has been cited by the following articles in journals that are participating in CrossRef Cited-by Linking.
Estimation of pile-bearing capacity of rocks via reliable hybridization techniques
  • Yangyang Ji
Multiscale and Multidisciplinary Modeling, Experiments and Design (2025) 8 (1)
Enhancing undrained shear strength prediction: a robust hybrid machine learning approach with naïve Bayes modeling
  • Chen Fang
  • Ying Li
  • Yang Shi
Journal of Engineering and Applied Science (2025) 72 (1)
A comparative study of LSSVR analysis on ground granulated blast-furnace slag-based concrete
  • Pu Zhou
  • Yin Lunyu
Multiscale and Multidisciplinary Modeling, Experiments and Design (2025) 8 (1)
Implementing a radial basis function model to anticipate the outcomes of the gasification
  • Hongfang Cui
  • Ning Su
  • Hongyan Cui
Chemical Product and Process Modeling (2025) 20 (1): 57.
Using Novel Optimization Algorithms with Support Vector Regression to Estimate Pile Settlement Rates
  • Lu Sun
  • Tinghui Li
Indian Geotechnical Journal (2025) 55 (1): 79.
Predicting the compressive strength of high-performance concrete employing multi-composed radial-based neural network
  • Honghong Wang
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 1925.
The implementation of a regularized radial basis function model for predicting California bearing capacity
  • Weiwei Zhan
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 2359.
Assessment of ultimate bearing capacity of rock-socketed piles using hybrid approaches
  • Rongjun You
  • Huijun Mao
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (4): 3673.
Investigation of mechanical properties of high-performance concrete via multi-method of regression tree approach
  • Rui Qi
  • Haiyan Wu
  • Yongjun Qi
  • HaiLin Tang
Materials Today Communications (2024) 40: 109922.
Estimating high-performance concrete compressive strength with support vector regression in hybrid method
  • Li Wang
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (1): 477.
Applying machine learning techniques in the form of ensemble and hybrid models to appraise hardness properties of high-performance concrete
  • Yue Xu
  • Mansour Afzal
Journal of Intelligent & Fuzzy Systems (2024) 46 (1): 903.
An explanatory machine learning model for forecasting compressive strength of high-performance concrete
  • Guifeng Yan
  • Xu Wu
  • Wei Zhang
  • Yuping Bao
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (1): 543.
Estimation of California Bearing Ratio of stabilized soil with lime via considering multiple optimizers coupled by RBF neural network
  • Ling Yang
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (4): 3425.
Hybrid and individual least square support vector regression methods for estimating the optimal moisture content of stabilized soil
  • Junfang Zhang
  • Peng Du
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 2757.
Accurate compressive strength prediction using machine learning algorithms and optimization techniques
  • Wenbin Lan
Journal of Engineering and Applied Science (2024) 71 (1)
The implementation of a Random Forest model utilizing meta-heuristic algorithms to forecast the undrained shear strength
  • Yunqing Xu
  • Xin Niu
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 2017.
Artificial rabbit optimization‐based ANFIS model development for predicting the compressive strength of GGBFS‐based concrete
  • Qingmei Sun
Structural Concrete (2024) 25 (1): 334.
Prediction of compressive strength of high-performance concrete via coupled meta-heuristic random forest regression techniques
  • Lei Liu
  • Du Bingxuan
  • Kan Yu
  • Wei Wei
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (2): 931.
Prediction of pile settlement by using hybrid random forest models
  • Shengnan Yu
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 2087.
Employing adaptive neural fuzzy inference system model via meta-heuristic algorithms for predicting undrained shear strength
  • Xiaoling Ding
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (2): 689.
The determination of the strongest attributes of high-performance concrete featuring innovative admixtures via optimal regression-based methodologies
  • Lianchao Zhang
  • Shizhong Guo
  • Jianwei Qi
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (2): 883.
Neuro-fuzzy system development to estimate the compressive strength of improved high-performance concrete
  • Zhiqiang Niu
  • Yan Yuan
  • Jianglan Sun
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (1): 395.
Prediction of pile settlement using hybrid support vector regressor
  • Yinan Li
  • Tianzhai Li
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 2103.
Hybrid regression analysis for simulating the rheological and mechanical properties of SCC
  • Chunyang Zhang
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (1): 491.
Applying SVR-PPSO, SVR-SSO, and SVR-BBO to estimate california bearing capacity of stabilized pond ash using admixtures
  • Wei Teng
  • Yan Li
  • Hongxing Sun
  • Haojie Chen
Journal of Intelligent & Fuzzy Systems (2024) 46 (4): 8311.
Compressive strength prediction of high-performance concrete with utilization of automated least square support vector regression-based algorithm
  • Caoli Lu
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 1941.
Predicting the Maximum Dry Density of Soil by Using the Individual and Hybrid Framework of the Decision Tree
  • Zheng Weifang
Indian Geotechnical Journal (2024) 54 (4): 1500.
Estimation of elastic modulus of recycle aggregate concrete based on hybrid and ensemble‐hybrid approaches
  • Bing Qu
Structural Concrete (2024) 25 (2): 1364.
The implementation of a least square support vector regression model utilizing meta-heuristic algorithms for predicting undrained shear strength
  • Shao Qiang
  • Ma Chenyue
  • Kong Dezhi
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 1843.
Prediction of syngas production in the gasification process of biomass employing adaptive neuro-fuzzy inference system along with meta-heuristic algorithms
  • Heng Wang
  • Shuming Cao
  • Xi Liu
Chemical Product and Process Modeling (2024) 19 (6): 933.
Prediction of compressive strength of high-performance concrete via automated machine learning models
  • Xiangcheng Meng
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 2207.
Using radial basis function for estimating the high-performance concrete compressive strength with optimizing AVOA and SSA
  • Yongcun Zhang
  • Zhe Bai
Journal of Intelligent & Fuzzy Systems (2024) 46 (3): 5695.
Predicting CBR values using gaussian process regression and meta-heuristic algorithms in geotechnical engineering
  • Xu Wu
  • Feng Yang
  • Shuchen Huang
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (4): 3799.
Tunnel boring machine performance assessment and prediction applying hybrid artificial intelligence
  • Hui Wang
  • Ensheng Liu
  • Hokai Wei
Journal of Intelligent & Fuzzy Systems (2024) 46 (2): 4511.
Prediction of compressive strength of concrete for high-performance concrete using two combined models, SVR-AVOA and SVR-SSA
  • Baorong Ding
  • Qiong Wang
  • Yue Ma
  • Hongbin Shi
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (2): 961.
RETRACTED: Hyper ensembled extreme gradient boosting techniques via novel triple algorithms to appraise the hardened properties of modern ternary admixed concrete
  • Haiyang Shen
Journal of Intelligent & Fuzzy Systems (2024) 46 (3): 5767.
Hybrid and ensemble models by coupled with automated meta-heuristic algorithms for compressive and flexural strength and slump of high-performance concrete
  • Mingming Zhang
  • Qingling Wu
Journal of Intelligent & Fuzzy Systems (2024) 46 (2): 5047.
Enhancing pile bearing capacity estimation through random forest-based hybridization approach
  • Fan Liu
  • Xiongzhi Peng
  • Pingyu Su
  • Fuzhong Yang
  • Kun Li
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (4): 3657.
Estimation of pile bearing capacity using hybrid models based on modified radial base function
  • Shaojun Chen
  • Xueli Chen
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (6): 5347.
Resolving challenges of groundwater flow modelling for improved water resources management: a narrative review
  • Saadu Umar Wali
  • Abdulqadir Abubakar Usman
  • Abdullahi Bala Usman
  • Umar Abdullahi
  • Ibrahim Umar Mohammed
  • Jamil Musa Hayatu
International Journal of Hydrology (2024) 8 (5): 175.
Prediction of California bearing ratio using hybrid regression models
  • Weiwei Wang
  • Long Zhao
  • Daoliang Dong
Signal, Image and Video Processing (2024) 18 (8-9): 6405.
Incorporation of radial basis function with Gorilla Troops Optimization and Moth-Flame Optimization to predict the compressive strength of high-performance concrete
  • Jin Zhao
  • Tingting Wu
  • Jun Li
  • Liying Shi
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (1): 69.
Compressive strength prediction of high-performance concrete using MLP model
  • Chengxiu Dong
Smart Science 1.
Settlement estimation of the piles socketed into rock employing hybrid ANFIS systems
  • Xi Chen
  • Liting Zhu
  • Lingfeng Ji
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (4): 3375.
Automated machine learning techniques for estimating of elastic modulus of recycled aggregate concrete
  • Chen Chien‐Ta
  • Tsai Shing‐Wen
  • Hsiao Liang‐Hao
Structural Concrete (2024) 25 (2): 1324.
Estimating the ultra-high-performance concrete compressive strength with a machine learning model via meta-heuristic algorithms
  • Bing Liu
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 1807.
Optimizing energy efficiency: predicting heating load with a machine learning approach and meta-heuristic algorithms
  • Yuan Feng
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (4): 3993.
Utilizing meta-heuristic algorithms for load-bearing capacity prediction in piles with support vector regression
  • Mengran Xu
  • Zhihui Zhu
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (6): 5445.
Predicting the settlement of pile based on a hybrid form of the model by considering Least Square Support Vector Regression
  • Qiang Chen
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (1): 529.
Prediction of California bearing ratio using multi-layer perceptron model based on multiple meta-heuristic optimizers
  • Jianhong Chen
Multiscale and Multidisciplinary Modeling, Experiments and Design (2024) 7 (3): 2489.
  • IWA Publishing
  • Republic – Export Building, Units 1.04 & 1.05
  • 1 Clove Crescent
  • London, E14 2BA, UK
  • Telephone: +44 208 054 8202
  • Fax: +44 207 654 5555
Close Modal
This Feature Is Available To Subscribers Only

or Create an Account

Close Modal
Close Modal
This site uses cookies. By continuing to use our website, you are agreeing to our privacy policy.
Accept