• Korean Journal of Artificial Intelligence
• /
• v.9 no.1
• /
• pp.9-14
• /
• 2021

This paper predicted a model that indicates whether to buy a car based on primary health insurance customer data. Currently, automobiles are being used to land transportation and living, and the scope of use and equipment is expanding. This rapid increase in automobiles has caused automobile insurance to emerge as an essential business target for insurance companies. Therefore, if the car insurance sales are predicted and sold using the information of existing health insurance customers, it can generate continuous profits in the insurance company's operating performance. Therefore, this paper aims to analyze existing customer characteristics and implement a predictive model to activate advertisements for customers interested in such auto insurance. The goal of this study is to maximize the profits of insurance companies by devising communication strategies that can optimize business models and profits for customers. This study was conducted through the Microsoft Azure program, and an automobile insurance purchase prediction model was implemented using Health Insurance Cross-sell Prediction data. The program algorithm uses Two-Class Logistic Regression and Two-Class Boosted Decision Tree at the same time to compare two models and predict and compare the results. According to the results of this study, when the Threshold is 0.3, the AUC is 0.837, and the accuracy is 0.833, which has high accuracy. Therefore, the result was that customers with health insurance could induce a positive reaction to auto insurance purchases.

• Proceedings of the KSR Conference
• /
• 1998.11a
• /
• pp.321-328
• /
• 1998

In this study we have studied running stability, safety and passenger comfort of the Chinese first class passenger car made by our company and CCRW. A fine analysis model of 72 d.o.f. was constructed for simulating dynamic behavior of the car on straight and curved tracks having irregularity configurations. We have calculated the various characteristic values such as critical speed, lateral force, derailment ratio, wheel unloading ratio and passenger comfort index, then evaluated them by comparing with reference values.

• Journal of the Korea Convergence Society
• /
• v.9 no.6
• /
• pp.33-38
• /
• 2018

In this study, we try to detect new attacks for vehicle by learning only one class. We use Car-Hacking dataset, an intrusion detection dataset, which is used to evaluate classification performance. The dataset are created by logging CAN (Controller Area Network) traffic through OBD-II port from a real vehicle. The dataset have four attack types. One class classification is one of unsupervised learning methods that classifies attack class by learning only normal class. When using unsupervised learning, it difficult to achieve high efficiency because it does not use negative instances for learning. However, unsupervised learning has the advantage for classifying unlabeled data, which are new attacks. In this study, we use one class classifier to detect new attacks that are difficult to detect using signature-based rules on network intrusion detection system. The proposed method suggests a combination of parameters that detect all new attacks and show efficient classification performance for normal dataset.

• Proceedings of the KSR Conference
• /
• 2005.05a
• /
• pp.257-262
• /
• 2005

Sleeping cars mean railroad cars which are equipped with facilities available business, travel, rest, sleep for long distance travel. Domestic sleeping cars , as the concept of ‘night train’, provide passenger who travel at night with simple berth . German, Japanese, American sleeping cars are classified with sleeping car, coach car, seat car or first class, standard class, family room, room for the handicapped, which offer not only sleep but various facilities and service such as snack, reading, available shower for daytime travel. Accordingly, through the analyzing spatial factor of domestic and foreign sleeping cars, we first should abstract the demand for fundamental design to enhance our passenger's comfort. And then we should try to improve the quality of travel culture by offering it passenger.

• Journal of the Korean Mathematical Society
• /
• v.58 no.5
• /
• pp.1147-1180
• /
• 2021

By considering the polynomial function 𝜙_car(z) = 1 + z + z²/2, we define the class 𝓢^*_car consisting of normalized analytic functions f such that zf'/f is subordinate to 𝜙_car in the unit disk. The inclusion relations and various radii constants associated with the class 𝓢^*_car and its connection with several well-known subclasses of starlike functions is established. As an application, the obtained results are applied to derive the properties of the partial sums and convolution.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.9
• /
• pp.105-111
• /
• 2015

This paper suggests O(n) linear-time algorithm for car sequencing problem (CSP) that has been classified as NP-complete because of the polynomial-time algorithm to solve the solution has been unknown yet. This algorithm applies maximum options-equiped car type first production rule to decide the car sequencing of n meet the r:s constraint. This paper verifies thirteen experimental data with the six data are infeasible. For thirteen experimental data, the proposed algorithm can be get the solution for in all cases. And to conclude, This algorithm shows that the CSP is not NP-complete but the P-problem. Also, this algorithm proposes the solving method to the known infeasible cases. Therefore, the proposed algorithm will stand car industrial area in good stead when it comes to finding a car sequencing plan.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.6
• /
• pp.2493-2501
• /
• 2013

Various schemes of transportation demand management(TDM) to discourage the use of cars and enhance public transit performance have been implemented in large cities. Nevertheless, policy effects in reducing car have not been satisfactory. Car-dependent travelers who tend to keep driving cars regardless of the change of the trip circumstances as such increase of travel time and cost according to car use or improvement of public transit service may be due to not according to utility reflecting mode-specific impedance and their own socio-economic characteristics. In this study, travelers were classified into four groups by their choice frequency of private car and public transit in unspecified multiple trip(car-dependent, car-choice, public transit-choice, public transit-dependent class). And the characteristics of each group were comparative analyzed. The results show that the group of a higher car-dependent is a higher priority on convenience and comfortability of the car when making decisions and the group of a lower of car-dependent is likely to change to public transit.

• East Asian Economic Review
• /
• v.16 no.3
• /
• pp.249-272
• /
• 2012

This paper examines how a Korean automobile firm price-discriminates between the Korean and the U.S. markets. We argue that a Korean automobile firm's pricing behavior depends on the differences in price elasticity over the segmented markets between the countries. Our findings are that differences in price elasticity may help explain why a medium-class car's price is higher in Korea than that in the U.S. while a small-sized car's price is higher in the U.S. than in Korea, which implies that a Korean automobile firm $3^{rd}$ degree price-discriminates on the same or similar products between Korea and the U.S. This type of $3^{rd}$ degree price discrimination differs from a typical home-bias effect (charging higher prices to domestic consumers) because a small-sized car which is produced domestically sells at higher price abroad. This finding can be added as a source that violates the law of one price.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.606-611
• /
• 2009

This paper describes a method for achieving a novel design within a class of 3D objects that would create a preferred impression on users. Physical parameters of the 3D objects that might strongly contribute to their visual impressions are sought through computational investigation of the impression ratings obtained for learning samples. "Car body" was selected as the class of 3D objects to be investigated. A morphable 3D model of car bodies that describes the variations in appearance using a smaller number of parameters was obtained. Based on each car body's rating for the impression of speediness obtained by paired comparison, the visual impression was transformed by manipulating the parameters defined in the morphable 3D model. The validity of the proposed method was confirmed by psychological experiments. A new scheme is also proposed to properly re-sample a novel object of a peculiar shape so that such an object could also be represented by the morphable 3D model.

• Proceedings of the KSR Conference
• /
• 2004.10a
• /
• pp.1553-1558
• /
• 2004

With the opening of the KTX(Korean Train Express) in April 2004, Express Train service started in KNR(Korean National Railroad). Each KTX train consists of 18 passenger compartments in total, such as of 4 first class car and 14 standard class car. And 2 compartments of standard class are serviced as a unreserved seat only. The Unreserved seat system of the KTX is convenient to the customer who wants to take a train without making a reservation. This study was designed to analyze the unreserved seat system of the KTX which is currently used, and to investigate the necessary conditions for gaining in public favor by developing the system.