Prediction of CBR Value of Fine Grained Soils of Bengal Basin by Genetic Expression Programming, Artificial Neural Network and Krigging Method

Alam, Sk Kamrul; Mondal, Abhijit; Shiuly, Amit

doi:10.1007/s12594-020-1409-0

Cited by 36 publications

(18 citation statements)

References 23 publications

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“…Coastal surveys are concluded. Since the 21st century, network information technology has developed rapidly worldwide (Alam et al 2020). The proximity of education and the integration of modern network information technology have contributed to the smart teaching reform of Chinese universities (Johari and Nejad 2015).…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Coastline climate environment and coastal city English smart teaching simulation based on GIS system

2021

Arab J Geosci

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This paper makes full use of the advantages of open source software, enhances the advantages of SWMMM model and MapWindow model, and provides ideas and solutions that integrate open source GIS system and professional model software.The basic concepts of SWMMM model and open source GIS system (MapW Indo) are outlined. The GIS platform is the parameter input platform, display platform, and statistical analysis platform of the SWMM model. The SWMM model provides hydropower and water quality modeling modules for the platform. Both data are stored in MongoD B. In addition, the document established a coastline climate environment and ecological environment remote sensing evaluation system as a basis for evaluation based on land use data and 17 types of land use and combined each evaluation result with expert advice and weighted analysis and classification. Each indicator is used to calculate the overall score of each area, as well as the weight and ratio of each factor in each field. With the implementation of Educational Information Action Plan 2.0, the city's modern education and training reforms are gaining momentum. Smart teaching has become the main focus of reform and innovation in universities and cities in the new century. The proficient smart teaching ability of university teachers is the basic condition necessary to create the professional development of English teachers, create smart classrooms and improve the smart city English education evaluation system, develop smart practical teaching, strengthen inter-school exchanges and cooperation, and widely promote smart teaching of urban English.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Coastline climate environment and coastal city English smart teaching simulation based on GIS system

2021

Arab J Geosci

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“…Therefore, for smaller LL, higher CBR was obtained. The mathematical relation between the two parameters is shown in Equation (1). Similarly, the mentioned relation are also reported in several studies, however current study's results are higher than the results of developed relations by Talukdar [28], Saklecha et al [25], Roy [23], Farias et al [10], Bassey et al [7], and Torgano et al [30].…”

Section: Linear Regression Analysis (Simple)supporting

confidence: 75%

“…However, good correlations for prediction of CBR value from LL, PL, PI, OMC, and MDD with as a single variable equation were achieved by Kumar et al [13], Prashanth et al [21], Gudeta and Patel [11], Mishra and Tegar [16], Priya et al [31], and Katte et al [12]. Moreover, various indx parameters such as specific gravity (G), coefficient of uniformity (Cu), coefficient of curvature (Cc), liquid limit (LL), plastic limit (PL), plasticity index (PI), optimum moisture content (OMC) and maximum dry density (MDD) for alluvial soil were correlated with CBR in the study of Alam et al [1]. The study considered both soaked and unsoaked CBR values as a function of those index properties by utilizing Genetic Expression Programming (GEP), artificial neural network (ANN), and kriging methods.…”

Section: Introductionmentioning

confidence: 99%

Prediction of California Bearing Ratio from Consistency and Compaction Characteristics of Fine-grained Soils

Rashed

Salih²,

Abdalla

2021

NJES

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Soil’s characteristics are essential for the successful design of projects such as airports runway and flexible pavement. CBR (California Bering Ratio) is one of the significant soil characteristics for highways and airports projects. Thus, the CBR property can be used to determine the subgrade reaction of soil through correlations. Many of the soil geotechnical parameters such as compaction characteristics (Maximum Dry Density, MDD; Optimum Moisture Content, OMC), and consistency parameters (Liquid Limit, LL; Plastic Limit, PL; Plasticity Index, PI) can be in charge of changes that happen in soil CBR value. Soaked and/or non-soaked conditions of soils also affect CBR value. Hence, testing soils in a laboratory for CBR calculation is time-consuming that needs notable effort. Therefore, this study aims to generate some useful correlations for soil’s CBR with compaction and consistency parameters for 85 samples of fine-grained soils. The study trials were applied on natural soil samples of various places in Sulaimani Governorate, Northern Iraq. Statistical analysis has been carried out by using SPSS software (Version 28). Soaked CBR is counted, which is important for conditions such as rural roads that remain prone to water for few days. Based on the statistical analysis, there is a significant correlation between LL, PL, PI, MDD, and OMC with CBR as the dependent variable as a single variable equation with R2 of 0.7673, 0.5423, 0.5192, 0.6489, and 0.51, respectively. In addition, the highest value of R2 correlation was obtained between CBR value with consistency and compaction properties as a multiple regression equation with R2 of 0.82. The obtained equations for correlation purposes are successfully achieved and can be used, notably, to estimate CBR value.

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“…Yildirim and Gunaydin (2011) [41], Kumar et al (2013) [42], Varghese et al (2013) [43], Bhatt and Jain (2014) [34], Sabat (2015) [44], Ghorbani and Hasanzadehshooiili (2018) [45], Suthar and Aggarwal (2018) [33], Alam et al (2020) [46], and Islam and Roy (2020) [47] developed further models relying on limited data sets (in the range of 20 to 158 observations). Their findings suggested accuracies of 0.81 R 2 < 1.00.…”

Section: Short Literature Review On Soft Computing Techniques For Estimation Of the California Bearing Ratiomentioning

confidence: 99%

On Random Subspace Optimization-Based Hybrid Computing Models Predicting the California Bearing Ratio of Soils

et al. 2021

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The California Bearing Ratio (CBR) is an important index for evaluating the bearing capacity of pavement subgrade materials. In this research, random subspace optimization-based hybrid computing models were trained and developed for the prediction of the CBR of soil. Three models were developed, namely reduced error pruning trees (REPTs), random subsurface-based REPT (RSS-REPT), and RSS-based extra tree (RSS-ET). An experimental database was compiled from a total of 214 soil samples, which were classified according to AASHTO M 145, and included 26 samples of A-2-6 (clayey gravel and sand soil), 3 samples of A-4 (silty soil), 89 samples of A-6 (clayey soil), and 96 samples of A-7-6 (clayey soil). All CBR tests were performed in soaked conditions. The input parameters of the models included the particle size distribution, gravel content (G), coarse sand content (CS), fine sand content (FS), silt clay content (SC), organic content (O), liquid limit (LL), plastic limit (PL), plasticity index (PI), optimum moisture content (OMC), and maximum dry density (MDD). The accuracy of the developed models was assessed using numerous performance indexes, such as the coefficient of determination, relative error, MAE, and RMSE. The results show that the highest prediction accuracy was obtained using the RSS-based extra tree optimization technique.

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Prediction of CBR Value of Fine Grained Soils of Bengal Basin by Genetic Expression Programming, Artificial Neural Network and Krigging Method

Cited by 36 publications

References 23 publications

RETRACTED ARTICLE: Coastline climate environment and coastal city English smart teaching simulation based on GIS system

RETRACTED ARTICLE: Coastline climate environment and coastal city English smart teaching simulation based on GIS system

Prediction of California Bearing Ratio from Consistency and Compaction Characteristics of Fine-grained Soils

On Random Subspace Optimization-Based Hybrid Computing Models Predicting the California Bearing Ratio of Soils

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