Development of a prediction model for the wear evolution of disc cutters on rock TBM cutterhead

2017 ◽  
Vol 67 ◽  
pp. 147-157 ◽  
Author(s):  
Lihui Wang ◽  
Haipeng Li ◽  
Xiangjun Zhao ◽  
Qian Zhang
Keyword(s):  
Prediction Model ◽  
Disc Cutters

A Case-Based Reasoning Combined with AHP Wighting for Cutter Conceptual Configuration Prediction Model

2011 ◽  
Vol 418-420 ◽  
pp. 1919-1924
Author(s):  
Xian Yun Wang ◽  
Jian Qin Liu ◽  
Wei Guo
Keyword(s):  
Analytic Hierarchy Process ◽  
Prediction Model ◽  
Relative Weight ◽  
Case Based Reasoning ◽  
Analytic Hierarchy ◽  
Disc Cutters ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process ◽  
Case Based

Abstract For complex and difficult geology, it is difficult to design right cutters for TBM in the conventional ways. So the successful experiences and data accumulated are very useful in TBM disc cutters design. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. This paper proposes an AHP-Based CBR model that overcomes the difficulty of measuring experience for determining the relative weight of attributes by the analytic hierarchy process. By comparing, the model using the analytic hierarchy process was more accurate, reliable, and explanatory for solving new problems using experience from previous cases.

Prediction Model for Normal and Flat Wear of Disc Cutters during TBM Tunneling Process

2021 ◽  
Vol 21 (3) ◽  
pp. 06021002
Author(s):  
Haiqing Yang ◽  
Bolong Liu ◽  
Yanqing Wang ◽  
Chenchen Li
Keyword(s):  
Prediction Model ◽  
Tunneling Process ◽  
Disc Cutters

1575: External Validation of Outcome Prediction Model for Ureteral/Renal Calculi

2005 ◽  
Vol 173 (4S) ◽  
pp. 427-427
Author(s):  
Sijo J. Parekattil ◽  
Udaya Kumar ◽  
Nicholas J. Hegarty ◽  
Clay Williams ◽  
Tara Allen ◽  
...  
Keyword(s):  
Prediction Model ◽  
Outcome Prediction ◽  
External Validation ◽  
Renal Calculi

Development of a headlamp dimming request prediction model

1975 ◽  
Author(s):  
Vivek D. Bhise ◽  
Thomas F. Swigart ◽  
Eugene I. Farber
Keyword(s):  
Prediction Model

Short-Version YLS-CMI: An Alternative Prediction Model for Juvenile Offenders at Intake

2009 ◽  
Author(s):  
Christina Campbell ◽  
Eyitayo Onifade ◽  
William Davidson ◽  
Jodie Petersen
Keyword(s):  
Juvenile Offenders ◽  
Prediction Model ◽  
Short Version

Career Choice Prediction--Model

2019 ◽  
Author(s):  
Zool Hilmi Mohamed Ashari ◽  
Norzaini Azman ◽  
Mohamad Sattar Rasul
Keyword(s):  
Prediction Model ◽  
Career Choice

Speed Prediction Model of Trucks on Gradient Sections Considering Vertical Curve

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Qianqian Liang ◽  
Xiaodong Zhang ◽  
Jinliang Xu ◽  
Yang Zhang
Keyword(s):  
Prediction Model ◽  
Speed Prediction

Stock Market Prediction using Data Mining Techniques

2020 ◽  
pp. 310-313
Author(s):  
Karunesh Makker ◽  
Prince Patel ◽  
Hrishikesh Roy ◽  
Sonali Borse
Keyword(s):  
Neural Network ◽  
Stock Market ◽  
Prediction Model ◽  
Efficient Market Hypothesis ◽  
Deterministic System ◽  
Vast Number ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Using Data ◽  
Robust Prediction

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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