• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of Mechanical Science and Technology
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• v.18 no.10
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• pp.1829-1836
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• 2004

This study presents the performance optimization of hypervelocity launcher system by using the experimentall data. During the optimization, the RSM (Response Surface Method) is adopted to find the operating parameters that could maximize the projectile speed. To construct a reliable response surface model, 3 full factorial method is used with the selected design variables, such as piston mass and 2 driver fill pressure. Nine test data could successfully construct the reasonable response surface, which used to yield the optimal operational conditions of the system using the genetic algorithm. The optimization results are confirmed by the experimental test with a good accuracy. Thus, the optimization can improve the performance of the facility.

• Journal of Korean Association for Spatial Structures
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• v.16 no.1
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• pp.95-104
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• 2016

Recently, the concept of damped outrigger system has been proposed for tall buildings. But, structural characteristics and design method of this system were not sufficiently investigated to date. In this study, the dynamic response control performance of outrigger damper has been analyzed. To this end, a simplified analysis model with outrigger damper system has been developed. Use the El Centro seismic(1940, NS) analysis was performed. Analysis results, on the top floor displacement response to the earthquake response, did not have a big effect. However, acceleration response control effect was found to be excellent. The increase of outrigger damper capacity usually results in the improved control performance. However, it is necessary to select that proper stiffness and damping values of the outrigger damper system because, the outrigger damper having large capacity is result in heavy financial burden.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.810-813
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• 2004

A study on the dynamic response of single-storey steel frames equipped with a rotational friction damper is presented. Extensive testing was carried out for assessing the friction pad material, damper unit performance and foaled model frame response to lateral harmonics excitation. Numerical simulations based on non-linear time history analysis were used to evaluate the seismic behaviour of steel frames with rotational frictional damper. It Is demonstrated that using discrete friction dampers of proper parameters to link steel frame can reduce dynamic response significantly.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.610-615
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• 2003

This paper proposes a nonlinear virtual coupling fur haptic interface, which offers better performance while maintaining stability of the system. The nonlinear virtual coupling is designed based on a human response model. This human response model exploits delay between the human Intention and the actual change of arm impedance. The proposed approach provides with less conservative constraints for the design of stable haptic interface, compared with the traditional passivity condition. This allows increased performance that is verified through experiments.

• Korean Journal of Construction Engineering and Management
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• v.20 no.5
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• pp.72-82
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• 2019

The purpose of this study is to find out how any organizational response or dispute-related consulting has a significant impact on management performance before or during a dispute over a construction subcontract dispute. In this study, multiple regression models were used to analyze the impact on consulting performance. According to the result of the analysis, the positive effects on the overall external consulting effect is influenced by five variables such as financial values, increase of the number of disputes, construction of response system by contents, construction of response system in each period, dispute response external response system. The original business operators were also more likely to be affected by internal activities of conflict response companies and the extent to which external response systems were established. This means that the supply and demand service provider's business environment is relatively poor, forcing it to be lower than the internal and external activities and influences of the original business operators of the conglomerates.

• Structural Engineering and Mechanics
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• v.63 no.1
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• pp.115-124
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• 2017

In this paper, a different technique to predict the effects of soil-structure interaction (SSI) on seismic response of building systems is investigated. The technique use a machine learning algorithm called Support Vector Regression (SVR) with technical and analytical results as input features. Normally, the effects of SSI on seismic response of existing building systems can be identified by different types of large data sets. Therefore, predicting and estimating the seismic response of building is a difficult task. It is possible to approximate a real valued function of the seismic response and make accurate investing choices regarding the design of building system and reduce the risk involved, by giving the right experimental and/or numerical data to a machine learning regression, such as SVR. The seismic response of both single-degree-of-freedom system and six-storey RC frame which can be represent of a broad range of existing structures, is estimated using proposed SVR model, while allowing flexibility of the soil-foundation system and SSI effects. The seismic response of both single-degree-of-freedom system and six-storey RC frame which can be represent of a broad range of existing structures, is estimated using proposed SVR model, while allowing flexibility of the soil-foundation system and SSI effects. The results show that the performance of the technique can be predicted by reducing the number of real data input features. Further, performance enhancement was achieved by optimizing the RBF kernel and SVR parameters through grid search.

• Earthquakes and Structures
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• v.14 no.5
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• pp.389-398
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• 2018

The seismic isolation system makes a structure isolated from ground motions to protect the structure from seismic events. Seismic isolation techniques have been implemented in full-scale buildings and bridges because of their simplicity, economic effectiveness, inherent stability and reliability. As for the responses of an isolated structure due to seismic events, it is well known that the most uncertain aspects are the seismic loading itself and structural properties. Due to the randomness of earthquakes and uncertainty of structures, seismic response distributions of an isolated structure are needed when evaluating the seismic fragility assessment (or probabilistic seismic safety assessment) of an isolated structure. Seismic response time histories are useful and often essential elements in its design or evaluation stage. Thus, a large number of non-linear dynamic analyses should be performed to evaluate the seismic performance of an isolated structure. However, it is a monumental task to gather the design or evaluation information of the isolated structure from too many seismic analyses, which is impractical. In this paper, a new methodology that can evaluate the seismic fragility assessment of an isolated structure is proposed by using stochastic response database, which is a device that can estimate the seismic response distributions of an isolated structure without any seismic response analyses. The seismic fragility assessment of the isolated nuclear power plant is performed using the proposed methodology. The proposed methodology is able to evaluate the seismic performance of isolated structures effectively and reduce the computational efforts tremendously.

• Korea Trade Review
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• v.46 no.1
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• pp.135-154
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• 2021

This study aims to investigate the difference in the perception of shippers on the quality of air freight service between air express and air freight forwarders. This study suggests hypothesis verification and implications on importance-performance between two groups of air express and air freight forwarders. In this study, we find that important variables through paired t-test and importance-performance analysis. As a result of paired t-test, there was a difference in the use variables of the document work variables through computerization in the importance area. In the satisfaction area, there was a difference between the groups in the response to customer request and the response to accidents. The variables that need to improve the focus derived from the importance-performance analysis are document work through computer and response to accidents. It is necessary to observe and manage the response of shippers continuously by holding various transportation schedules in the schedule area, possibility of adjustment of transportation schedule, regular freight and schedule provision.

• Journal of the Korea Computer Industry Society
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• v.2 no.12
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• pp.1557-1562
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• 2001

The echo response time has been a concern in the performance of the UNIX systems, a significant tail always appears in the distribution of echo response time, though the average echo response time is less serious. This paper addresses the issue of echo response times in the UNIX systems. We explain how the Fair Share Scheduler (FSS) works and explain why the FSS might cause excessive echo response times and show by analysis how echo response time reacts to key parameters under FSS. Finally, we present a recommended solution that should improve the echo response time drastically. This solution is a refined FSS which will overcome the echo response time problem while retaining the essence of the FSG. This will enhance the UNIX performance and productivity.