A Study of the Prediction of Load-Settlement Curves of Bored Piles with an Improved Grey Model

An improved grey system model GM(1,1) was proposed in this paper, considered that the large difference between predicted results and measured load-settlement relationship results of bored piles, in which the prediction results were given by the original theory. The complete and incomplete load-settlement curves from pile loading tests were fitted and predicated by the improved grey model. The results calculated with empirical equations or methods in technical code for building pile foundations were compared with those predicted with the improved grey model. Analysis of a case study showed that the results predicted by the improved grey theory model GM(1,1) had higher precision, which demostrated that this improved theory was of significance in engineering practice.

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Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model

Mathematical Problems in Engineering ◽

10.1155/2021/5541650 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Yubin Cai ◽

Xin Ma ◽

Wenqing Wu ◽

Yanqiao Deng

Keyword(s):

United States ◽

Natural Gas ◽

The United States ◽

Grey Model ◽

System Model ◽

Grey System ◽

Power Sector ◽

Gas Consumption ◽

Natural Gas Consumption ◽

Grey System Model

Natural gas is one of the main energy resources for electricity generation. Reliable forecasting is vital to make sensible policies. A randomly optimized fractional grey system model is developed in this work to forecast the natural gas consumption in the power sector of the United States. The nonhomogeneous grey model with fractional-order accumulation is introduced along with discussions between other existing grey models. A random search optimization scheme is then introduced to optimize the nonlinear parameter of the grey model. And the complete forecasting scheme is built based on the rolling mechanism. The case study is executed based on the updated data set of natural gas consumption of the power sector in the United States. The comparison of results is analyzed from different step sizes, different grey system models, and benchmark models. They all show that the proposed method has significant advantages over the other existing methods, which indicates the proposed method has high potential in short-term forecasting for natural gas consumption of the power sector in United States.

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The Anomalous Threshold Voltage Prediction by Grey Model GM(1,1) for Submicron MOSFETs

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.605-607.2027 ◽

2012 ◽

Vol 605-607 ◽

pp. 2027-2030

Author(s):

Shen Li Chen ◽

Dun Ying Shu

Keyword(s):

Threshold Voltage ◽

Grey Model ◽

System Model ◽

Grey System ◽

Experiment Data ◽

Real Experiment ◽

Anomalous Threshold ◽

Grey System Model ◽

Geometric Effects ◽

Good Agreement

This paper proposes a new application to predict the anomalous threshold voltage (Vth) behavior in submicron MOSFETs by using the GM(1,1) grey system model. It can be developed to analyze the threshold voltage inclination due to the device geometric effects. The prediction results are compared with experiment data obtained from actual devices, we found that the different value of real experiment data and estimation data from the GM(1,1) is small and a good agreement has been obtained.

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Correction to: Improvement of Grey System Model using Particle Swarm Optimization

Journal of Electrical Systems and Information Technology ◽

10.1186/s43067-021-00037-8 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Elvis Twumasi ◽

Emmanuel Asuming Frimpong ◽

Daniel Kwegyir ◽

Denis Folitse

Keyword(s):

Particle Swarm Optimization ◽

Body Text ◽

Particle Swarm ◽

System Model ◽

Grey System ◽

Swarm Optimization ◽

Grey System Model

Following publication of the original article [1], the authors reported an error in the title and body text.

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Utilizing an Adaptive Grey Model for Short-Term Time Series Forecasting: A Case Study of Wafer-Level Packaging

Mathematical Problems in Engineering ◽

10.1155/2013/526806 ◽

2013 ◽

Vol 2013 ◽

pp. 1-6 ◽

Cited By ~ 7

Author(s):

Che-Jung Chang ◽

Der-Chiang Li ◽

Wen-Li Dai ◽

Chien-Chih Chen

Keyword(s):

Semiconductor Manufacturing ◽

Manufacturing System ◽

Grey System Theory ◽

Grey Model ◽

Grey System ◽

Wafer Level ◽

Short Term ◽

Packaging Process ◽

Wafer Level Packaging

The wafer-level packaging process is an important technology used in semiconductor manufacturing, and how to effectively control this manufacturing system is thus an important issue for packaging firms. One way to aid in this process is to use a forecasting tool. However, the number of observations collected in the early stages of this process is usually too few to use with traditional forecasting techniques, and thus inaccurate results are obtained. One potential solution to this problem is the use of grey system theory, with its feature of small dataset modeling. This study thus uses the AGM(1,1) grey model to solve the problem of forecasting in the pilot run stage of the packaging process. The experimental results show that the grey approach is an appropriate and effective forecasting tool for use with small datasets and that it can be applied to improve the wafer-level packaging process.

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