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Wyświetlanie 1-2 z 2
Tytuł:
Investigation of the settlement prediction in soft soil by Richards Model: based on a linear least squares-iteration method
Autorzy:
Nadeem, Muhammad
Akbar, Muhammad
Huali, Pan
Xiaoqing, Li
Guoqiang, Ou
Amin, Azka
Powiązania:
https://bibliotekanauki.pl/articles/1852538.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
metoda iteracji liniowej
metoda najmniejszych kwadratów
prognoza
grunt słaby
podłoże gruntowe
błąd porównawczy
osiadanie gruntu
model obliczeniowy
linear iterative method
least square method
prediction
soft soil
comparative error
settlement
calculation model
Opis:
Prediction of soft soil sub-grades settlement has been a big challenge for geotechnical engineers that are responsible for the design of roadbed embankment. The characteristics of low strength, poor permeability, high water contents, and high compressibility are dominant in soft soils, which result in a huge settlement in the case of long-term loading. The settlement prediction in soft soil subgrades of Jiehui Expressway A1, Guangdong, China, is the focus of this study. For this purpose, the necessary data of settlement is collected throughout the project execution. The numerical analysis is conducted by using the Richards model based on Linear Least Squares Iteration (LLS-I) method to calculate and predict the expected settlement. The traditional settlement prediction methods, including the hyperbolic method, exponential curve method, and pearl curve method, are applied on field settlement data of soft soil subgrades of Jiehui Expressway A1. The results show that the Richards model based on Linear Least Squares Iteration (LLS-I) method has high precision, and it has proven to be a better option for settlement prediction of soft soil sub-grades. The model analysis indicates that the mean absolute percentage error (MAPE) can be minimized as compared to other soft soil sub-grades settlement prediction methods. Hence, Richards's model-based LLS-I method has a capability for simulation and settlement prediction of soft soil subgrades.
Źródło:
Archives of Civil Engineering; 2021, 67, 2; 491-506
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The use of genetic expression programming to optimize the parameters of the Muskingum method comparison with numerical methods, Euphrates river a case study
Autorzy:
Al-Bedyry, Najah
Mergan, Maher
Rasheed, Maha
Al-Khafaji, Zainab
Al-Husseinawi, Fatimah Nadeem
Powiązania:
https://bibliotekanauki.pl/articles/27312169.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
trasowanie rzeczne
programowanie ekspresji genetycznej
regresja liniowa wykładnicza
metoda Runge – Kutta czwartego rzędu
river routing
genetic expression programming
exponential linear regression
forth-order Runge–Kutta method
Opis:
The Muskingham method uses two formulas to describe the translation of flow surges in a river bed. The continuity formula is the first formula, while the relationship between the reach’s storage, inflow, and outflow is the second formula (the discharge storage formula); these formulas are applied to a portion of the river between two river cross sections. Several methods can be utilized to estimate the model’s parameters. This section contrasts the conventional graphic approach with three numerical methods: Genetic algorithm, Exponential regression, and Classical fourth-order Runge-Kutta. This application’s most noticeable plus point was the need to employ a few hydrological variables, such as intake, output, and duration. The location of the Euphrates entrance to the Iraqi territory in Husaybah city was chosen with its hydrological data during the period (1993-2017) to conduct this study. The goal function is established by accuracy criterion approaches (Sum of squares error and sum of squared deviations). Depending on the simulation findings, the suggested predictive flood routing ideawas highly acceptable with the prospect of adopting the Genetic Expression Programming model as a suitable and more accurate replacement to existing methods such as the Muskingum model and other numerical models, where this method gave results (R2 = 0.9984, SSQ = 1.06, SSSD = 80.75), These results achieved a hydrograph that is largely identical to what was given by the hydrological method called Muskingham.
Źródło:
Archives of Civil Engineering; 2023, 69, 3; 507--519
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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