• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.239-259
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• 2019

The transmuted generalized extreme value (TGEV) distribution was first introduced by Aryal and Tsokos (Nonlinear Analysis: Theory, Methods & Applications, 71, 401-407, 2009) and applied by Nascimento et al. (Hacettepe Journal of Mathematics and Statistics, 45, 1847-1864, 2016). However, they did not give explicit expressions for all the moments, tail behaviour, quantiles, survival and risk functions and order statistics. The TGEV distribution is a more flexible model than the simple GEV distribution to model extreme or rare events because the right tail of the TGEV is heavier than the GEV. In addition the TGEV distribution can adjusted various forms of asymmetry. In this article, explicit expressions for these measures of the TGEV are obtained. The tail behavior and the survival and risk functions were determined for positive gamma, the moments for nonzero gamma and the moment generating function for zero gamma. The performance of the maximum likelihood estimators (MLEs) of the TGEV parameters were tested through a series of Monte Carlo simulation experiments. In addition, the model was used to fit three real data sets related to financial returns.

• Journal of Drive and Control
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• v.15 no.4
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• pp.67-73
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• 2018

The paper deals with an approach to time domain simulation for closed end at the downstream of pipe, hydraulic lines terminating into a tank and series lines with change of cross sectional area. Time domain simulation of a fluid power systems containing hydraulic lines is very complex and difficult if the transfer functions consist of hyperbolic Bessel functions which is the case for the distributed parameter dissipative model. In this paper, the magnitudes and phases of the complex transfer functions of hydraulic lines are calculated, and the MATLAB Toolbox is used to formulate a rational polynomial approximation for these transfer functions in the frequency domain. The approximated transfer functions are accurate over a designated frequency range, and used to analyze the time domain response. This approach is usefully to simulate fluid power systems with hydraulic lines without to approximate the frequency dependent viscous friction.

• Smart Media Journal
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• v.10 no.2
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• pp.48-54
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• 2021

Sepsis is one of the leading causes of mortality globally, and it costs billions of dollars annually. However, treating septic patients is currently highly challenging, and more research is needed into a general treatment method for sepsis. Therefore, in this work, we propose a reinforcement learning method for learning the optimal treatment strategies for septic patients. We model the patient physiological time series data as the input for a deep recurrent Q-network that learns reliable treatment policies. We evaluate our model using an off-policy evaluation method, and the experimental results indicate that it outperforms the physicians' policy, reducing patient mortality up to 3.04%. Thus, our model can be used as a tool to reduce patient mortality by supporting clinicians in making dynamic decisions.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.55-60
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• 2022

Churn prediction is a critical long-term problem for many business like music, games, magazines etc. The churn probability can be used to study many aspects of a business including proactive customer marketing, sales prediction, and churn-sensitive pricing models. It is quite challenging to design machine learning model to predict the customer churn accurately due to the large volume of the time-series data and the temporal issues of the data. In this paper, a parallel artificial neural network is proposed to create a highly-accurate customer churn model on a large customer dataset. The proposed model has achieved significant improvement in the accuracy of churn prediction. The scalability and effectiveness of the proposed algorithm is also studied.

• Geomechanics and Engineering
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• v.29 no.3
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• pp.269-279
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• 2022

In this research, a series of dynamic numerical analysis were carried out for deep underground building structures under the various earthquake conditions. Dynamic numerical analysis model was developed based on the PLAXIS2D and calibrated with centrifuge test data from Kim et al. (2016). The hardening soil model with small strain stiffness (HSSMALL) was adopted for soil constitutive model, and interface elements was employed at the interface between plate and soil elements to simulate dynamic interaction effect. In addition, parametric study was performed for fixed condition and embedded depth. Finally, the dynamic behavior of underground building structure was thoroughly analyzed and evaluated.

• Steel and Composite Structures
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• v.43 no.2
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• pp.153-164
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• 2022

In this study, a series of cyclic loading tests were performed on viscoelastic dampers (VED) composed of viscoelastic polymer composite material and thin steel plates to observe the variation of the mechanical properties under different loading conditions. A mathematical model was developed based on the Kelvin-Voigt and Bouc-Wen models to formulate the nonlinear force-displacement relationship of the viscoelastic damper. The accuracy of the proposed mathematical model was verified using the data obtained from the tests. The mathematical model was applied to analyze a reinforced concrete framed structure retrofitted with viscoelastic dampers. Nonlinear dynamic analysis results showed that the average maximum inter-story drift ratios of the retrofitted structure met the target limit state after installing the VED. In addition, both the maximum and residual displacements were significantly reduced after the installation of the VED.

• Journal of the Ergonomics Society of Korea
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• v.6 no.1
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• pp.9-24
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• 1987

The design and philosophy are presented for an intelligent aid for a hyman operator who must diagnose a novel fault in a physical system. A novel fault is defined as one that the operator has not experienced in either real system operation or training. When the operator must diagnose a novel fault, deep reasoning about the behavior of the system components is required. To aid the human operator in this situation, four aiding approaches which provide useful information are proposed. The aiding information is generated by a qualitative, component-level model of the physical system. Both the aid and the human are able to reason causally about the system in a cooperative search for a diagnosis. The aiding features were designed to help the hyman's use of his/her mental model in predicting the normal system behavior, integrating the observations into the actual system behavior, or finding discrepancies between the two. The aid can also have direct access to the operator's hypotheses and run a hypothetical system model. The different aiding approaches will be evaluated by a series of experiments.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10a
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• pp.183-186
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• 2003

A finite element-based, integrated process model is presented for a three dimensional, coupled analysis of the thermal and mechanical behavior of type 304 stainless slab during hot charge rolling (HCR) and cold charge rolling (CCR) processes. The validity of the proposed model is examined through comparison with measurements. The susceptibility on micro-crack initiation or propagation due to the thermal stress in these two different process conditions was examined. The model's capability of revealing the effect of diverse process parameters is demonstrated through a series of process simulation.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.181-193
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• 2022

This paper seeks to investigate major macroeconomic factors and bond yield interactions in Thai bond markets, with the goal of forecasting future bond yields. This study examines the best predictive yields for future bond yields at different maturities of 1-, 3-, 5-, 7-, and 10-years using time series data of economic indicators covering the period from 1998 to 2020. The empirical findings support the hypothesis that macroeconomic factors influence bond yield fluctuations. In terms of forecasting future bond yields, static predictions reveal that in most cases, the BVAR model offers the best predictivity of bond rates at various maturities. Furthermore, the BVAR model has the best performance in dynamic rolling-window, forecasting bond yields with various maturities for 2-, 4-, and 8-quarters. The findings of this study imply that the BVAR model forecasts future yields more accurately and consistently than other competitive models. Our research could help policymakers and investors predict bond yield changes, which could be important in macroeconomic policy development.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.947-961
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• 2023

This paper summarizes some research findings that show how the differential transform method (DTM) is used to resolve the Holling-Tanner model. To confirm the application, effectiveness, and correctness of the approach, a comparison between the differential transform method (DTM) and the Adomian decomposition method (ADM) is carried out, and an accurate solution representation in truncated series is discovered. The approximate solution obtain using both techniques and comparison demonstrates same outcome which remains a preferred numerical method for resolving a system of nonlinear differential equations.