• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.555-561
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• 2009

The established mathematical modeling methods have limitation to know the hydraulic characteristics at the wastewater treatment plant which are complex and nonlinear systems. So, an artificial neural network (ANN) model based on hydraulic characteristics is applied for modeling wastewater quality of a full-scale wastewater treatment plant using DNR (Daewoo nutrient removal) process. ANN was trained using data which are influents (TSS, BOD, COD, TN, TP) and effluents (COD, TN, TP) components in a year, and predicted the effluent results based on the training. To raise the efficiency of prediction, inputs of ANN are added the influent and effluent information that are in yesterday and the day before yesterday. The results of training data tend to have high accuracy between real value and predicted value, but test data tend to have lower accuracy. However, the more hydraulic characteristics are considered, the results become more accuracy.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3224-3226
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• 1999

This paper introduces a nonlinear wavelet transform based on the lifting scheme, which is applied to signal denoising through the translation invariant wavelet transform. The wavelet representation using orthogonal wavelet bases has received widespread attention. Recently the lifting scheme has been developed for the construction of biorthogonal wavelets in the spatial domain. In this paper, we adaptively reduce the vanishing moments in the discontinuities to suppress the ringing artifacts and this customizes wavelet transforms providing an efficient framework for the translation invariant denoising. Special care has been given to the boundaries, where we design a set of different prediction coefficients to reduce the prediction error.

• Journal of Navigation and Port Research
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• v.33 no.4
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• pp.255-261
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• 2009

Prediction of the stability for ships is very complex in reality. In this paper, risk based approach is applied to predict the probability of capsize for a certified ship, which is effected by the forces of sea especially the wave loading Safety assessment and risk analysis process are also applied for the probabilistic prediction of stability for ships. The probability of shipsencountering different waves at sea is calculated by the existed statistics data and risk based models. Finally, ship capsizing probability is calculated according to single degree of freedom(SDF) rolling differential equation and basin erosion theory of nonlinear dynamics. Calculation results show that the survival probabilities of ship excited by the forces of the seas, especially in the beam seas status, can be predicted by the risk based method.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.151-152
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• 2021

The sale price of apartment buildings is a key factor in the success or failure of apartment projects, and the factors that affect the sale price of apartments vary widely, including location, environmental factors, and economic conditions. Existing methods of predicting the sale price do not reflect the nonlinear characteristics of apartment prices, which are determined by the complex impact factors of reality, because statistical analysis is conducted under the assumption of a linear model. To improve these problems, a new analysis technique is needed to predict apartment sales prices by complex nonlinear influencing factors. Using machine learning techniques that have recently attracted attention in the field of engineering, it is possible to predict the sale price reflecting the complexity of various factors. Therefore, this study aims to conduct a basic study for the development of a machine learning-based prediction model for apartment sale prices.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.371-382
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• 2024

Measurement or prediction of compression index (C_c) of soils is essential for assessment of total and differential settlement of structures. It is a well-known fact that this parameter is controlled by several index identifiers of soil including initial void ratio, Atterberg limits, overconsolidation ratio, specific gravity, etc. Many studies in the past proposed relationships for prediction of C_c based on different index properties. Therefore, this study aims to present a comparison of previously proposed equations for estimation of C_c. Data from literature was compiled, and a total of 90 and 623 test results on remolded and undisturbed specimens were used to question the validity of previously proposed equations. Nevertheless, the modeling ability of 7 and 12 equations for estimation of C_c of remolded and undisturbed soils were questioned by use of compiled data. Moreover, new empirical relationships based on initial void ratio and toughness limit for prediction of C_c was proposed by use of nonlinear multivariable regression and evolutionary based regression analyses. The results are promising-the performances of models established are quite acceptable, which are verified by statistical analyses.

• Journal of the Earthquake Engineering Society of Korea
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• v.20 no.1
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• pp.45-54
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• 2016

This study suggests a prediction model of ground motion spectral shape considering characteristics of earthquake records in Korea. Based on the Graizer and Kalkan's prediction procedure, a spectral shape model is defined as a continuous function of period in order to improve the complex problems of the conventional models. The approximate spectral shape function is then developed with parameters such as moment magnitude, fault distance, and average shear velocity of independent variables. This paper finally determines estimator coefficients of subfunctions which explain the corelation among the independent variables using the nonlinear optimization. As a result of generating the prediction model of ground motion spectral shape, the ground motion spectral shape well estimates the response spectrum of earthquake recordings in Korea.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.8
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• pp.765-773
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• 1991

In this paper, a new hierarchical optimization algorithm which is called here as

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2019.05a
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• pp.413-413
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• 2019

• Earthquakes and Structures
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• v.26 no.2
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• pp.97-115
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• 2024

In this paper, a database consisting of the dynamic shear modulus ratio and damping ratio test data of clay obtained from 406 groups of triaxial tests is constructed with the starting area of Xiong'an New Area as the research background. The aim is to study the nonlinear dynamic properties of clay in this area under cyclic loading. The study found that the effective confining pressure and plasticity index have certain influences on the dynamic shear modulus ratio and damping ratio of clay in this area. Through data analysis, it was found that there was a certain correlation between effective confining pressure and plasticity index and dynamic shear modulus ratio and damping ratio, with fitting degree values greater than 0.1263 for both. However, other physical indices such as the void ratio, natural density, water content and specific gravity have only a small effect on the dynamic shear modulus ratio and the damping ratio, with fitting degree values of less than 0.1 for all of them. This indicates that it is important to consider the influence of effective confining pressure and plasticity index when studying the nonlinear dynamic properties of clays in this area. Based on the above, prediction models for the dynamic shear modulus ratio and damping ratio in this area were constructed separately. The results showed that the model that considered the combined effect of effective confining pressure and plasticity index performed best. The predicted dynamic shear modulus ratio and damping ratio closely matched the actual curves, with approximately 88% of the data falling within ±1.3 times the measured dynamic shear modulus ratio and approximately 85.1% of the data falling within ±1.3 times the measured damping ratio. In contrast, the prediction models that considered only a single influence deviated from the actual values, particularly the model that considered only the plasticity index, which predicted the dynamic shear modulus ratio and the damping ratio within a small distribution range close to the average of the test values. When compared with existing prediction models, it was found that the predicted dynamic shear modulus ratio in this paper was slightly higher, which was due to the overall hardness of the clay in this area, leading to a slightly higher determination of the dynamic shear modulus ratio by the prediction model. Finally, for the dynamic shear modulus ratio and damping ratio of the engineering site in the starting area of Xiong'an New Area, we confirm that the prediction formulas established in this paper have high reliability and provide the applicable range of the prediction model.

• Architectural research
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• v.18 no.1
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• pp.39-47
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• 2016

A finite element analysis technology applicable to the prediction of the static nonlinear response of cable roof structure is presented. The unified kinematic description is employed to formulate the present cable element and different strain definitions such as Green-Lagrange strain, Biot strain and Hencky strain can be adopted. The Newton-Raphson method is used to trace the nonlinear load-displacement path. In the iteration process, the compressive stress of a cable element is not allowed. For the verification of the present cable element, four numerical examples are tackled. Finally, numerical results obtained by using the present cable element are provided as new benchmark test results for cable structures under static loads.