• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.14
• /
• pp.5883-5888
• /
• 2014

Background: Breast cancer is the most common cancers in female populations. The exact cause is not known, but is most likely to be a combination of genetic and environmental factors. Log-logistic model (LLM) is applied as a statistical method for predicting survival and it influencing factors. In recent decades, artificial neural network (ANN) models have been increasingly applied to predict survival data. The present research was conducted to compare log-logistic regression and artificial neural network models in prediction of breast cancer (BC) survival. Materials and Methods: A historical cohort study was established with 104 patients suffering from BC from 1997 to 2005. To compare the ANN and LLM in our setting, we used the estimated areas under the receiver-operating characteristic (ROC) curve (AUC) and integrated AUC (iAUC). The data were analyzed using R statistical software. Results: The AUC for the first, second and third years after diagnosis are 0.918, 0.780 and 0.800 in ANN, and 0.834, 0.733 and 0.616 in LLM, respectively. The mean AUC for ANN was statistically higher than that of the LLM (0.845 vs. 0.744). Hence, this study showed a significant difference between the performance in terms of prediction by ANN and LLM. Conclusions: This study demonstrated that the ability of prediction with ANN was higher than with the LLM model. Thus, the use of ANN method for prediction of survival in field of breast cancer is suggested.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.05a
• /
• pp.191-194
• /
• 2001

The ozone forecasting systems have many problems because the mechanism of the ozone concentration is highly complex, nonlinear, and nonstationary. Also, the results of prediction are not a good performance so far, especially in the high-level ozone concentration. This paper describes the modeling method of the ozone prediction system using neuro-fuzzy approaches and fuzzy clustering. The dynamic polynomial neural network (DPNN) based upon a typical algorithm of GMDH (group method of data handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system.

• International Journal of Highway Engineering
• /
• v.10 no.3
• /
• pp.199-208
• /
• 2008

Prediction the performance of pavement provides proper information to an agency on decision-making process; especially evaluating the pavement performance and prioritizing the work plan. To date, there are a number of approaches to predict the future deterioration of pavements. However, there are some limitation to proper prediction of the pavement service life. In this paper, pavement performance model and pavement condition prediction model are developed in order to improve pavement condition prediction method. The prediction model of pavement condition through the regression analysis of real pavement condition is based on the probability distribution of pavement condition, which set to 5%, 15%, 25% and 50%, by condition of the pavement and traffic volume. The pavement prediction model presented from the behavior of individual pavement condition which are set to 5%, 15%, 25% and 50% of probability distribution. The performance of the prediction model is evaluated from analyzing the average, standard deviation of HPCI, and the percentage of HPCI which is lower than 3.0 of comparable section. In this paper, we will suggest the more rational method to determine the future pavement conditions, including the probabilistic duration and deterministic modeling methods regarding the impact of traffic volume, age, and the type of the pavement.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2002.05a
• /
• pp.948-954
• /
• 2002

The structural vibration of a diesel generator set was investigated through analyses and tests. FE modeling and normal mode analysis were performed and compared with measured results for both structure components and generator set assembly. The results of component analyses were fairly well coincident with measured results but those of assembled generator set showed more or less discrepancies. Discussions were given about the uncertainties for vibration characteristics of component structures and assembled running structures especially concerning their nonlinearities and damping effects. Detailed excitation analysis fellowed by forced response analysis was done from the engine and pressure data to compare with the actual measured vibration. As results the vibration prediction for frame structures of reciprocating internal combustion engine was confirmed reliable to some extent.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.47 no.3
• /
• pp.257-266
• /
• 2011

Recently, the manufacturers of life-jacket are very interested in the acquisition of USCG(US Coast Guard) approval because the acquisition of USCG approval has an important role in the purchasing decision of the buyer's. Be based on criterion of USCG, we studied how to predict the change of floating position of human model with life-jacket to verify the backside restore. For this, in this study, the human model and the lifejacket was modeled in three dimension, the application program for prediction of floating position was developed, and plugged-in commercial program.

• Structural Engineering and Mechanics
• /
• v.69 no.3
• /
• pp.243-255
• /
• 2019

Utilization of fiber beam-column element has gained considerable attention in recent years due mainly to its ability to model distributed plasticity over the length of the element through a number of integration points. However, the relatively high sensitivity of the method to modeling parameters as well as material behavior models can pose a significant challenge. Residual drift is one of the seismic demands which is highly sensitive to modeling parameters and material behavior models. Permanent deformations play a prominent role in the post-earthquake evaluation of serviceability of bridges affected by a near-fault ground shaking. In this research, the influence of distributed plasticity modeling parameters using both force-based and displacement-based fiber elements in the prediction of internal forces obtained from the nonlinear static analysis is studied. Having chosen suitable type and size of elements and number of integration points, the authors take the next step by investigating the influence of material behavioral model employed for the prediction of permanent deformations in the nonlinear dynamic analysis. The result shows that the choice of element type and size, number of integration points, modification of cyclic concrete behavior model and reloading strain of concrete significantly influence the fidelity of fiber element method for the prediction of permanent deformations.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2003.07b
• /
• pp.607-610
• /
• 2003

The characteristic prediction and analysis of 3-dimensional (3-D) solenoid-type embedded inductors is investigated. The four different structures of 3-D inductor are fabricated by using low-temperature cofired ceramic (LTCC) process. The circuit model parameters of the each building block are optimized and extracted using the partial element equivalent circuit method and HSPICE circuit simulator. Based on the model parameters, predictive modeling is applied for the structures composed of the combination of the modeled building blocks. And the characteristics of test structures, such as self-resonant frequency, inductance and Q-factor, are analyzed. This approach can provide the characteristic conception of 3-D solenoid embedded inductors for structural variations.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2019.11a
• /
• pp.266-266
• /
• 2019

Marine accidents are increasing year by year, and various accidents occur such as engine failure, collision, stranding, and fire. These marine accidents present a risk of large casualties. It is important to prevent accidents beforehand. In this study, we propose a modeling to predict the occurrence of marine accidents by applying the Markov Chain Process that can predict the future based on past data. Applying the proposed modeling, the probability of future marine accidents was calculated and compared with the actual frequency. Through this, a probabilistic model was proposed to prepare a prediction system for marine accidents, and it is expected to contribute to predicting various marine accidents.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.10 no.3
• /
• pp.270-281
• /
• 2018

Application of the LeMoS hybrid (LH) URANS/LES method for the wake parameters prediction is considered. The wake fraction coefficient is calculated for inland ship model M1926 under shallow water conditions and compared to results of PIV measurements. It was shown that due to lack of the resolved turbulence at the interface between LES and RANS zones the artificial grid induced separations can occur. In order to overcome this drawback, a shielding function is introduced into LH model. The new version of the model is compared to the original one, RANS $k-{\omega}$ SST and SST-IDDES models. It is demonstrated that the proposed modification is robust and capable of wake prediction with satisfactory accuracy.

• Proceedings of the KSME Conference
• /
• 2008.11b
• /
• pp.2548-2553
• /
• 2008

Prediction of the rotor blade performance is important for determining design factors such as weight and size in development of a small-scale helicopter. Generally, prediction of helicopter performance means the estimation of the power required for a given flight condition. However, due to lack of test data and analyzed results for small-scale rotor blade operated at low Reynolds numbers ($Re{\approx}10^5$), this is not an easy task. As an initial research, this work performs a modeling of a single rotor configuration with FLIGHTLAB and a experimental research with rotor test bed. In this process, we performed small-scale isolated single rotor by experimental and numerical method and achieved good agreement of the hover performance on the test data and simulation results.