• Computers and Concrete
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• v.13 no.6
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• pp.765-780
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• 2014

Many building codes use the empirical equation to determine fundamental period of vibration where in effect of length, width and the stiffness of the building is not explicitly accounted for. In the present study, ANN models are developed in three categories, varying the number of input parameters in each category. Input parameters are chosen to represent mass, stiffness and geometry of the buildings indirectly. Total numbers of 206 buildings are analyzed out of which, data set of 142 buildings is used to develop these models. It is demonstrated through developed ANN models that geometry of the building and the sizes of the columns are significant parameters in the dynamic analysis of building frames. The testing dataset of these three models is used to obtain the empirical relationship between the height of the building and fundamental period of vibration and compared with the similar equations proposed by other researchers. Experiments are conducted on Mild Steel frames using uniaxial shake table. It is seen that the values obtained through the ANN models are close to the experimental values. The validity of ANN technique is verified by experimental values.

• Computers and Concrete
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• v.32 no.1
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• pp.1-13
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• 2023

This paper discusses a framework for predicting the flexural strength of prestressed and non-prestressed FRP reinforced T-shaped concrete beams using soft computing techniques. An analysis of 83 tests performed on T-beams of varying widths has been conducted for this purpose with different widths of compressive face, beam depth, compressive strength of concrete, area of prestressed and non-prestressed FRP bars, elasticity modulus of prestressed and non-prestressed FRP bars, and the ultimate tensile strength of prestressed and non-prestressed FRP bars. By analyzing the data using two soft computing techniques, named artificial neural networks (ANN) and gene expression programming (GEP), the fundamental parameters affecting the flexural performance of prestressed and non-prestressed FRP reinforced T-shaped beams were identified. The results showed that although the proposed ANN model outperformed the GEP model with higher values of R and lower error values, the closed-form equation of the GEP model can provide a simple way to predict the effect of input parameters on flexural strength as the output. The sensitivity analysis results revealed the most influential input parameters in ANN and GEP models are respectively the beam depth and elasticity modulus of FRP bars.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.334-341
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• 2004

The coefficient of permeability is one of the most important properties in unsaturated soils. The permeability varies with change in the water content as the soil water characteristic curve(SWCC) does. Thus the permeability curve of unsaturated soils has the similar shape with the soil-water characteristic curve(SWCC). Therefore, the methodologies have been studied to simply predict the unsaturated permeability from the SWCC. In this study, the experimental tests of SWCC and permeability were carried out for domestic weathered granite soils. The SWCC test results were fitted to Fredlund and Xing's SWCC equation and then it was found that there are some relationships between the parameters of SWCC equation and the basic soil properties. Accordingly we used an ANN(artificial neural network) model to obtain the SWCC parameters from the basic soil properties. Finally, the coefficients of permeability were predicted from these results by a prediction model.

• Geomechanics and Engineering
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• v.31 no.3
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• pp.291-304
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• 2022

Maximum shear modulus (G_max or G₀) is an important soil property useful for many engineering applications, such as the analysis of soil-structure interactions, soil stability, liquefaction evaluation, ground deformation and performance of seismic design. In the current study, bender element (BE) tests are used to evaluate the effect of the void ratio, effective confining pressure, grading characteristics (D₅₀, C_u and C_c), anisotropic consolidation and initial fabric anisotropy produced during specimen preparation on the G_max of sand-gravel mixtures. Based on the tests results, an empirical equation is proposed to predict G_max in granular soils, evaluated by the experimental data. The artificial neural network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) models were also applied. Coefficient of determination (R²) and Root Mean Square Error (RMSE) between predicted and measured values of G_max were calculated for the empirical equation, ANN and ANFIS. The results indicate that all methods accuracy is high; however, ANFIS achieves the highest accuracy amongst the presented methods.

• Journal of the Korean Geotechnical Society
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• v.21 no.1
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• pp.15-27
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• 2005

In this paper, a method reasonably predicting soil water characteristic curve of domestic weathered granite soils was suggested, based on the test results obtained through experiments. In other words, a method to estimate the parameters of Fredlund and Xing's equation using an ANN (artificial neural network) was proposed. The particle size distribution, compacted water content and void ratio were used as input data in the ANN model for predicting the parameters, since it was found that these basic soil properties affect the parameters obtained from the test results and the fitting results of SWCC. The network model proposed in this study to obtain the parameters of Fredlund and Xing's SWCC equation produced reliable predictions, and the precision of the prediction results from the proposed method was high, in comparison with the prediction results of other methods.

• The Korean Journal of Franchise Management
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• v.9 no.4
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• pp.7-19
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• 2018

Purpose - Recently, global management in Korea franchise industry is becoming an important keyword. As an important branch market, Chinese market plays a major role not only by making experience of the competitiveness among global brands which offers a foothold to become a top global brand, but also by actualizing an economies of scale in production, sales, etc. Therefore, it is necessary to identify key successful factor influencing customer evaluation and responses of Korean franchise restaurant targeting Chinese consumers in China context. The purpose of this study is to examine the effects for Korean franchise restaurant selection attributes on perceived value, customer satisfaction and customer loyalty in Chinese context with SmartPLS 3 and Artifical Neural Network(ANN). Research design, data, and methodology - For these purposes, the authors developed several hypotheses. A questionnaire survey was conducted on the panel of online survey companies for Chinese consumers who have visited Korean franchise restaurants. A total of 404 data were analyzed using structural equation modeling(SEM) and artifical neural network(ANN) with SPSS 22.0 and SmartPLS 3.0. Result - The findings of this study are as follows: First, the alternative model findings show that facilities & atmosphere, employee service, and menu influenced on utilitarian value, customer satisfaction, and customer loyalty directly. Second, employee service influenced on customer satisfaction. Third, menu influenced on hedonic value. Fourth, brand reputation influenced on utilitarian value. Fifth, hedonic value increase customer satisfaction and customer loyalty. Sixth, hedonic value increase customer loyalty. Seventh, customer increase customer loyalty. And, the ANN analysis shows that utilitarian value is the first most important factor influencing customer satisfaction, followed by hedonic value, facilities & atmosphere, menu and employee service. However, the ANN analysis shows that customer satisfaction is the first most important factor influencing customer loyalty, followed by utilitarian value, hedonic value, brand reputation, menu, and employee service. Conclusions - This study provides practical implications for enhancing customer satisfaction and customer loyalty by applying the ANN technique that complements the limitations of the linear structural relationship analysis using the proposed model and the alternative model. In other words, the SEM-ANN model provides guidelines on how Korean franchise restaurants should formulate facilities & atmosphere, employee service, and menu mix strategies in China. In addition, ANN 's analysis shows that restaurant brand reputation plays a pivotal role in increasing customer loyalty. The fact suggests that Korean franchise companies should establish their domestic brand reputation prior to their entry into overseas markets such as China.

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.934-956
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• 2023

This study focuses on the adoption of Healthcare Information System (HIS) in India's healthcare services, which has led to an increased use of HIS software for managing patient information in hospitals. The study aims to evaluate the factors that influence hospital workers' satisfaction with HIS usage and its impact on their intention to continue in the use of HIS. Primary data was collected through a survey questionnaire from 265 hospital workers. A new framework was developed, and Structural Equation Modeling (SEM) was used for analysis. Sensitivity analysis was also conducted on demographic data using an Artificial Neural Network (ANN) approach. The results indicated that all hypotheses were significant (p < 0.05). Effort expectancy was the most significant factor influencing hospital workers' satisfaction (p < 0.01). Sensitivity analysis showed that education (Model-A) and experience in use of HIS (Model-B) were the most important factors. The study contributes by proposing a new theoretical framework and extending the previous research on HIS usage satisfaction. Overall, the study highlights the importance of easiness and usefulness in predicting HIS usage satisfaction.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.11B no.3
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• pp.81-85
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• 2001

Processes for optimizing the coil shape of deflection yoke are proposed A very accurate and practical winding modeler is developed and volume integral equation method (VIEM) is used for field calculation. Two steps of optimizations are done by using (1+1) evolution strategy. Those are dimensional optimization and pin-position optimization Various techniques are applied for reducing computational time for the optimization.

• International Journal of Safety
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• v.7 no.2
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• pp.12-16
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• 2008

Lower flash points for the binary systems, carbon tetrachloride+o-xylene and water+n-butanol were measured by Pensky-Martens closed cup tester. The Raoult's law and optimization method using van Laar equation were used to predict the lower flash points and were compared with experimental data. The calculated values based on the optimization method were found to be better than those based on the Raoult's law.

• 한국전산유체공학회:학술대회논문집
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• 2004.10a
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• pp.161-164
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• 2004

A finite volume numerical model is developed for simulating non-equilibrium electroosmotic flow in micro- and nanochannels. The Guoy-Chapman model is adopted to compute the flow and electric potential. The Nernst-Planck equation is employed to trace unsteady transports of ionic species, i.e., time-dependent net charge density. A new set of boundary conditions based on surface charge density are designed rather than using the conventionally-employed zeta potential. A few issues for an efficient computation of electroosmotic flows are discussed. Representative computational examples are given to illustrate the robustness of the numerical model.