Analysis of the factors influencing the nonuniform deformation and a deformation prediction model of soft rock tunnels by data mining

Stock market is a very volatile in-deterministic system with vast number of factors influencing the direction of trend on varying scales and multiple layers. Efficient Market Hypothesis (EMH) states that the market is unbeatable. This makes predicting the uptrend or downtrend a very challenging task. This research aims to combine multiple existing techniques into a much more robust prediction model which can handle various scenarios in which investment can be beneficial. Existing techniques like sentiment analysis or neural network techniques can be too narrow in their approach and can lead to erroneous outcomes for varying scenarios. By combing both techniques, this prediction model can provide more accurate and flexible recommendations. Embedding Technical indicators will guide the investor to minimize the risk and reap better returns.

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Prediction Model for Under-Graduating Student�s Salary Using Data Mining Techniques

International Journal of Scientific Research in Network Security and Communication ◽

10.26438/ijsrnsc/v6i2.5053 ◽

2018 ◽

Vol 6 (2) ◽

pp. 50-53

Author(s):

Himanshi ◽

Komal Kumar Bhatia

Keyword(s):

Data Mining ◽

Prediction Model ◽

Data Mining Techniques ◽

Using Data

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Study on Prediction Model of Karstic Large Spring Water Level Dynamic Coupling Multiple Factors in Jinan

The Open Fuels & Energy Science Journal ◽

10.2174/1876973x01508010309 ◽

2015 ◽

Vol 8 (1) ◽

pp. 309-317 ◽

Cited By ~ 1

Author(s):

Xing Liting ◽

Zhou Juan ◽

Zhang Fengjuan ◽

Wang Song ◽

Dou Tongwen ◽

...

Keyword(s):

Prediction Model ◽

Water Level ◽

Spring Water ◽

Anthropogenic Factors ◽

Karst Water ◽

Multiple Factors ◽

Factors Influencing ◽

Heterogeneous Features ◽

Dry Seasons ◽

Natural Decay

In karst regions, due to the heterogeneous features of karst medium, the characteristics of the groundwater flow turn to be of high complexity. Researchers have been seeking proper forecasting methods for karst water dynamic for many years. This paper, taking the spring in Jinan as an example, using regression analysis, analyzed the factors influencing spring water dynamic, and quantitatively evaluated the influencing coefficients of spring water level concerning rainfall, exploitation and recharge as well as the natural decay coefficient of spring water in dry seasons. The prediction model coupling multiple factors was built by investigating natural and anthropogenic factors influencing groundwater level, which could be used for forecasting dynamic of spring water in Jinan. The calculated value of model was highly coincided with the observed value. In consideration of the characteristics of uneven precipitation in Jinan, the suitable zones and volume of artificial recharge were investigated finally, which could help to sustain the spewing of Jinan springs significantly.

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Study on fire risk assessment for underwater soft rock tunnels based on AHP

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/714/2/022039 ◽

2021 ◽

Vol 714 (2) ◽

pp. 022039

Author(s):

Jie Chen

Keyword(s):

Risk Assessment ◽

Soft Rock ◽

Fire Risk ◽

Fire Risk Assessment ◽

Rock Tunnels

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Study on the Mechanical Behavior of Double Primary Support of Soft Rock Tunnel under High Ground Stresses and Large Deformation

Advances in Civil Engineering ◽

10.1155/2020/8832797 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Zhe Liu

Keyword(s):

Mechanical Behavior ◽

Large Deformation ◽

Design Method ◽

Characteristic Curve ◽

Soft Rock ◽

Support Design ◽

Deformation Amount ◽

Secondary Lining ◽

Rock Tunnels ◽

Primary Support

Double primary support structures could effectively solve the problem of large deformation of surrounding rock for soft rock tunnels. However, the mechanical behavior of this new support structure is still incomplete, and the design method should be revised. Based on the theory of energy conversion, this paper analyzes the support characteristic curve of double primary support and puts forward the dynamic design method of double primary support. Considering that the secondary lining can be set after monitoring the deformation amount and deformation rate of the first primary support, its support parameters can be dynamically adjusted according to the actual situation. By applying the double primary support design method in the Maoxian tunnel of Chenglan Railway, the field monitoring results show that the double primary support has a significant effect on the energy release of surrounding rocks, greatly reducing the load acting on the secondary lining and ensuring the safety and reliability of the tunnel structure.

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