• Earthquakes and Structures
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• v.16 no.6
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• pp.679-690
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• 2019

This paper presents machine learning methods using Support Vector Machine (SVM) and Multilayer Perceptron (MLP) to analyze optimal damper distribution for structural vibration control. Regarding different building structures, a genetic algorithm based optimization method is used to determine optimal damper distributions that are further used as training samples. The structural features, the objective function, the number of dampers, etc. are used as input features, and the distribution of dampers is taken as an output result. In the case of a few number of damper distributions, multi-class prediction can be performed using SVM and MLP respectively. Moreover, MLP can be used for regression prediction in the case where the distribution scheme is uncountable. After suitable post-processing, good results can be obtained. Numerical results show that the proposed method can obtain the optimized damper distributions for different structures under different objective functions, which achieves better control effect than the traditional uniform distribution and greatly improves the optimization efficiency.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.768-783
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• 2020

Typically, a Dynamic Positioning System (DPS) uses a PID feed-back system, and it often adopts a wind feed-forward system because of its easier implementation than a feed-forward system based on current or wave. But, because a ship's drifting motion is caused by wind, current, and wave drift loads, all three environmental loads should be considered. In this study, a motion predictive control for the PID feedback system of the DPS is proposed, which considers the three environmental loads by utilizing predicted drifted ship positions in the future since it contains information about the three environmental loads from the moment to the future. The prediction accuracy for the future drifted ship position is ensured by adopting deep learning algorithms and a replay buffer. Finally, it is shown that the proposed motion predictive system results in better station-keeping performance than the wind feed-forward system.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.19 no.4
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• pp.328-334
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• 2009

There are various methods for welding fume control. These methods can be divided into local exhaust system, general ventilation system and integrated control system. With the general ventilation system, we should have a good prediction tool for testing various appropriate control options. But, until now there are not many studies about how to predict the welding fume concentrations. Especially, the prediction of welding fume concentration is not a very easy task because welding fume is the particulate matters. In this study, we tried to measure $CO_2$ concentrations and welding fume concentrations in a small single room with a small ventilation opening. Using commercially available CFD (Computational Fluid Dynamics) software, we tried to predict $CO_2$ concentrations under the exactly same conditions. Then, we tried to compare the numerical $CO_2concentrations$ with the experimental results to know whether we could predict $CO_2$ concentrations. Then we tried to compare $CO_2$ concentrations with experimental welding fume concentrations to know whether we can use the numerical $CO_2concentrations$ to predict the welding fume concentration indirectly.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.226-229
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• 1999

We have been developing a method to build models for time series using Genetic Programming. The proposed method has been applied to various kinds of time series e.g. computer-generated chaos, natural phenomena, and financial market indices etc. Now we apply the prediction method to time histories of seismic ground motion i.e. one-step-ahead prediction of seismographic amplitude. Waves of earthquakes are composed of P-waves and S-waves. They propagate in different speeds and have different characteristics. It is believed that P-waves arrive firstly and S-waves arrive secondly. Simulations were performed based on real data of Hyuganada earthquake which broke out at southern part of Kyushuu Island in Japan. To our surprise, prediction model built using the earthquake waves in early time can enough precisely predict main huge waves in later time. Lots of experiments lead us to conclude that every slice of data involves P-wave and S-wave. The simulation results suggest the GP-based prediction method can be utilized in alarm systems or dispatch systems in an emergency.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.203-211
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• 2009

Korean public owners who order public multi-family housing construction projects have yet to gain access to a model for predicting construction cost. For this reason, their construction cost prediction is mainly dependent upon historic data and experience. In this paper, a cost-prediction model based on Case-Based Reasoning (CBR) in the design phase of public multi-family housing construction projects was developed. The developed model can determine the total construction cost by estimating the different Building, Civil, Mechanical, Electronic and Telecommunication, and Landscaping work costs. Model validation showed an accuracy of 97.56%, confirming the model's excellent viability. The developed model can thus be used to predict the construction cost to be shouldered by public owners before the design is completed. Moreover, any change orders during the design phase can be immediately applied to the model, and various construction costs by design alternative can be verified using this model. Therefore, it is expected that public owners can exercise effective design management by using the developed cost prediction model. The use of such an effective cost prediction model can enable the owners to accurately determine in advance the construction cost and prevent increase or decrease in cost arising from the design changes in the design phase, such as change order. The model can also prevent the untoward increase in the duration of the design phase as it can effectively control unnecessary change orders.

• Parasites, Hosts and Diseases
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• v.55 no.2
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• pp.167-174
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• 2017

China still has more than 30,000 patients of advanced schistosomiasis while new cases being reported consistently. D-dimer is a fibrin degradation product. As ascites being the dominating symptom in advanced schistosomiasis, the present study aimed to explore a prediction model of ascites with D-dimer and other clinical easy-achievable indicators. A case-control study nested in a prospective cohort was conducted in schistosomiasis-endemic area of southern China. A total of 291 patients of advanced schistosomiasis were first investigated in 2013 and further followed in 2014. Information on clinical history, physical examination, and abdominal ultrasonography, including the symptom of ascites was repeatedly collected. Result showed 44 patients having ascites. Most of the patients' ascites were confined in the kidney area with median area of $20mm^2$. The level of plasma D-dimer and pertinent liver function indicators were measured at the initial investigation in 2013. Compared with those without ascites, cases with ascites had significantly higher levels of D-dimer ($0.71{\pm}2.44{\mu}g/L$ vs $0.48{\pm}2.12{\mu}g/L$, P=0.005), as well ALB (44.5 vs 46.2, g/L) and Type IV collagen (50.04 vs $44.50{\mu}g/L$). Receiver operating characteristic curve analyses indicated a moderate predictive value of D-dimer by its own area under curve (AUC) of 0.64 (95% CI: 0.54-0.73) and the cutoff value as $0.81{\mu}g/L$. Dichotomized by the cutoff level, D-dimer along with other categorical variables generated a prediction model with AUC of 0.76 (95% CI: 0.68-0.89). Risks of patients with specific characteristics in the prediction model were summarized. Our study suggests that the plasma D-dimer level is a reliable predictor for incident ascites in advanced schistosomiasis japonica patients.

• JSTS:Journal of Semiconductor Technology and Science
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• v.9 no.4
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• pp.187-191
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• 2009

This paper proposes a high-performance architecture of the H.264 intra prediction circuit. The proposed architecture uses the 4-input and 2-input common computation units and common registers for fast and efficient prediction operations. It avoids excessive power consumption by the efficient control of the external and internal memories. The implemented circuit based on the proposed architecture can process more than 60 HD ($1,920{\times}1,088$) image frames per second at the maximum operating frequency of 101 MHz by using 130 nm standard cell library.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.3
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• pp.377-385
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• 2012

The Automatic Dependent Surveillance Broadcast (ADS-B) system is a key component of CNS/ATM recommended by the International Civil Aviation Organization (ICAO) as the next generation air traffic control system. ADS-B broadcasts identification, positional data, and operation information of an aircraft to other aircraft, ground vehicles and ground stations in the nearby region. This paper explores the ADS-B based trajectory prediction and the conflict detection algorithm. The multiple-model based trajectory prediction algorithm leads accurate predicted conflict probability at a future forecast time. We propose an efficient and accurate algorithm to calculate conflict probability based on approximation of the conflict zone by a set of blocks. The performance of proposed algorithms is demonstrated by a numerical simulation of two aircraft encounter scenarios.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.6
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• pp.816-821
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• 2015

In this paper, an in-flight prediction method of thrust profiles for solid rocket motors is proposed. Actually, it is very difficult to have detailed information about the performance of the rocket motors beforehand because it is quite sensitive to combustion environments. To overcome this problem, we have developed an algorithm for generating in-flight prediction of rocket motor performance in realistic environments via a reference burnback profile and accelerations measured at a short time-interval just after launch. The performance is evaluated through a lot of flight test results.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.524-524
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• 2000

We have been developing a method to build one-step-ahead prediction models for time series using genetic programming (GP). Our model building method consists of two stages. In the first stage, functional forms of the models are inherited from their parent models through crossover operation of GP. In the second stage, the parameters of the newborn model arc optimized based on an iterative method just like the back propagation. The proposed method has been applied to various kinds of time series problems. An application to the seismic ground motion was presented in the KACC'99, and since then the method has been improved in many aspects, for example, additions of new node functions, improvements of the node functions, and new exploitations of many kinds of mutation operators. The new ideas and trials enhance the ability to generate effective and complicated models and reduce CPU time. Today, we will present a couple of financial applications, espc:cially focusing on gold price prediction in Tokyo market.