نتایج جستجو برای: prediction settlement

تعداد نتایج: 269778  

2002
Mohamed A. Shahin Mark B. Jaksa Holger R. Maier

The problem of estimating the settlement of shallow foundations on granular soils is very complex and not yet entirely understood. The geotechnical literature has included many formulae that are based on several theoretical or experimental methods to obtain an accurate, or near-accurate, prediction of such settlement. However, these methods fail to achieve consistent success in relation to accu...

2005
M. A. Shahin M. B. Jaksa H. R. Maier

Traditional methods of settlement prediction of shallow foundations on granular soils are far from accurate and consistent. This can be attributed to the fact that the problem of estimating the settlement of shallow foundations on granular soils is very complex and not yet entirely understood. Recently, artificial neural networks (ANNs) have been shown to outperform the most commonly used tradi...

Journal: :international journal of civil engineering 0
t.h. kim taejong-ro, yeongdo-gu, busan 606-791, korea s.h. you director, geotechnical research & development co., ltd., korea

the ground improvement using plastic board drain (pbd) in soft soil was undertaken by sand mat formation, pbd installation, preloading surcharge, and removal of surcharge. during this procedure, the sand mat formation induced an initial settlement. however, it was very difficult to estimate that settlement due to pbd installation, which frequently destroyed the instruments installed in the grou...

2014
Jun Feng Xi-yong Wu

Based on the method of BP neural network,a foundation settlement of BP neural network prediction model was established for a railway subgrade in HeFei area China. In the model, the previous field monitoring data was used as the training sample and the later settlement was predicted. The model was used for four test sections of the railway subgrade. The results showed that for the four test sect...

2005
R. Maier

The problem of estimating the settlement of shallow foundations on granular soils is complex and not yet entirely understood. In the past, many empirical and theoretical methods have been developed for predicting the settlement of shallow foundations on granular soils; however, these methods are far from accurate and consistent. In recent times, artificial neural networks (ANNs) have been used ...

Due to urbanization and population increase, need for metro tunnels, has been considerably increased in urban areas. Estimating the surface settlement caused by tunnel excavation is an important task especially where the tunnels are excavated in urban areas or beneath important structures. Many models have been established for this purpose by extracting the relationship between the settlement a...

Journal: :journal of artificial intelligence and data mining 0
v. r. kohestani department of civil engineering, central tehran branch, islamic azad university, tehran, iran. m. r. bazarganlari department of civil engineering, east tehran branch, islamic azad university, tehran, iran j. asgari marnani department of civil engineering, central tehran branch, islamic azad university, tehran, iran

due to urbanization and population increase, need for metro tunnels, has been considerably increased in urban areas. estimating the surface settlement caused by tunnel excavation is an important task especially where the tunnels are excavated in urban areas or beneath important structures. many models have been established for this purpose by extracting the relationship between the settlement a...

2016
Isabel Fuentes-Santos Uxío Labarta X. Antón Álvarez-Salgado Mª José Fernández-Reiriz

Identifying the environmental factors driving larval settlement processes is crucial to understand the population dynamics of marine invertebrates. This work aims to go a step ahead and predict larval presence and intensity. For this purpose we consider the influence of solar irradiance, wind regime and continental runoff on the settlement processes. For the first time, we conducted a 5-years w...

Journal: :International Journal of Geosynthetics and Ground Engineering 2015

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