• Journal of Distribution Research
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• v.5 no.2
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• pp.91-105
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• 2001

Wholesale club is one of the fastest expanding retailer formats. Given its key features such as limited assortment and no promotion policy, the current paper provides a theory on why the wholesale clubs charge their members fixed annual fees. In a competitive setting with supermarkets, the proposed model demonstrates that the membership fee is the optimal reaction of wholesale clubs to supermarkets" sales promotion. More specifically, the positive amount of annual fee is only justified under the condition that there exists consumer heterogeneity in consumption rate and when the supermarket exercises price promotion on the product that the wholesale club carries. This paper describes the competition in a stylized fashion and derives the optimal membership fee under a scenario where retail promotion is present. This study is valuable in that it offers a different explanation on wholesale club membership fee than conventional wisdoms such as cost sharing and that it provides insights to the managers who consider no-fee format.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1668-1683
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• 2011

The importance of secure communication between only legitimate group members in ad hoc networks has been growing in recent years. Due to the ad hoc nature the scalability on dynamic membership change is a major concern. However, the previous models require at least O(log n) communication cost for key update per each membership change, which imposes a heavy burden on the devices. In this paper we present a scalable model that supports communication-efficient membership change in ad hoc networks by exclusionary keys and RSA functions. The multicast cost for key update is extremely low, that is O(1) , and one-to-one communications occur mostly in neighboring devices.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2885-2887
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• 2005

We introduce a hybrid identification of information granulation(IG)-based fuzzy model to carry out the model identification of complex and nonlinear systems. To optimally design the IG-based fuzzy model we exploit a hybrid identification through genetic alrogithms(GAs) and Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the seleced input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of HCM clustering help determine the initial paramters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the inital parameters are tuned effectively with the aid of the GAs and the least square method. Numerical example is included to evaluate the performance of the proposed model.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.9-11
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• 2005

We propose a optimal identification of information granulation(IG)-based fuzzy model to carry out the model identification of complex and nonlinear systems. To optimally identity we use genetic algorithm (GAs) sand Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the selected input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method. Numerical example is included to evaluate the performance of the proposed model.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.146-148
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• 2005

In this paper, we propose a genetically optimized identification of information granulation(IG)-based fuzzy model. To optimally design the IG-based fuzzy model we exploit a hybrid identification through genetic alrogithms(GAs) and Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the seleced input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the inital parameters are tuned effectively with the aid of the genetic algorithms and the least square method. And also, we exploite consecutive identification of fuzzy model in case of identification of structure and parameters. Numerical example is included to evaluate the performance of the proposed model.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.1
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• pp.44-54
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• 2023

In this study, the second-order Nomoto's nonlinear expansion model was implemented as a Tagaki-Sugeno fuzzy model based on the heading angular velocity to design the automatic steering system of a ship considering nonlinear elements. A Tagaki-Sugeno fuzzy PID controller was designed using the applied fuzzy membership functions from the Tagaki-Sugeno fuzzy model. The linear models and fuzzy membership functions of each operating point of a given nonlinear expansion model were simultaneously tuned using a genetic algorithm. It was confirmed that the implemented Tagaki-Sugeno fuzzy model could accurately describe the given nonlinear expansion model through the Zig-Zag experiment. The optimal parameters of the sub-PID controller for each operating point of the Tagaki-Sugeno fuzzy model were searched using a genetic algorithm. The evaluation function for searching the optimal parameters considered the route extension due to course deviation and the resistance component of the ship by steering. By adding a penalty function to the evaluation function, the performance of the automatic steering system of the ship could be evaluated to track the set course without overshooting when changing the course. It was confirmed that the sub-PID controller for each operating point followed the set course to minimize the evaluation function without overshoot when changing the course. The outputs of the tuned sub-PID controllers were combined in a weighted average method using the membership functions of the Tagaki-Sugeno fuzzy model. The proposed Tagaki-Sugeno fuzzy PID controller was applied to the second-order Nomoto's nonlinear expansion model. As a result of examining the transient response characteristics for the set course change, it was confirmed that the set course tracking was satisfactorily performed.

• Journal of KIISE:Software and Applications
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• v.29 no.8
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• pp.573-583
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• 2002

Pattern recognition process is made up of the feature extraction in the pre-processing, the pattern clustering by training and the recognition process. This paper presents the F-LVQ (Fuzzy Learning Vector Quantization) pattern classification model which is optimized by the fuzzy membership function for the OCR(Optical Character Recognition) system. We trained 220 numeric patterns of 22 Hangul and English fonts and tested 4840 patterns whose forms are changed variously. As a result of this experiment, it is proved that the proposed model is more effective and robust than other typical LVQ models.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.1
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• pp.123-149
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• 2024

The purpose of this study is to present a plan to simplify the issuance of public library loan membership cards for children under the age of 14, and to devise measures to promote the convenience of using public libraries and to promote their use. To this end, related laws and systems, related services, and systems were analyzed. The issuance cases for each type were derived and analyzed by thoroughly investigating the procedure for issuing loan membership cards for children under the age of 14 in 1,211 public libraries nationwide, and focus group interviews were conducted. Based on this, the "double diamond model" was employed among service design methodologies to propose step-by-step guidelines for simplifying the procedure for issuing public library loan membership cards for children under the age of 14, as well as improving the environment, such as the roles of stakeholders, laws, and systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.138-143
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• 2006

In this paper, we have presented a Sequential Agglomerative Hierarchical Nested (SAHN) algorithm-based data clustering method in fuzzy inference system to achieve optimal performance of fuzzy model. SAHN-based algorithm is used to give possible range of number of clusters with cluster centers for the system identification. The axes of membership functions of this fuzzy model are optimized by using cluster centers obtained from clustering method and the consequence parameters of the fuzzy model are identified by standard least square method. Finally, in this paper, we have observed our model's output performance using the Box and Jenkins's gas furnace data and Sugeno's non-linear process data.

• Computational Structural Engineering
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• v.4 no.3
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• pp.107-115
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• 1991

A probabilistic-Fuzzy model for seismic hazard analysis is developed. The proposed model is able to reproduce both the randomness and the imprecision in conjunction with earthquake occurrences. Results-of this research are (a) membership functions of both peak ground accelerations associated with a given probability of exceedance and probabilities of exceedance associated with a given peak ground acceleration, and (b) characteristic values of membership functions at each location of interest. The proposed probabilistic-fuzzy model for assessment of seismic hazard is successfully applied to the Wasatch Front Range in Utah in order to obtain the seismic maps for different annual probabilities of exceedance, different peak ground accelerations, and different time periods.