• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.692-700
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• 2017

In this paper, we propose the structural design of Interval Type-2 FCM based RBFNN. Proposed model consists of three modules such as condition, conclusion and inference parts. In the condition part, Interval Type-2 FCM clustering which is extended from FCM clustering is used. In the conclusion part, the parameter coefficients of the consequence part are estimated through LSE(Least Square Estimation) and WLSE(Weighted Least Square Estimation). In the inference part, final model outputs are acquired by fuzzy inference method from linear combination of both polynomial and activation level obtained through Interval Type-2 FCM and acquired activation level through Interval Type-2 FCM. Additionally, The several parameters for the proposed model are identified by using differential evolution. Final model outputs obtained through benchmark data are shown and also compared with other already studied models' performance. The proposed algorithm is performed by using Iris and Vehicle data for pattern classification. For the validation of regression problem modeling performance, modeling experiments are carried out by using MPG and Boston Housing data.

• Industrial Engineering and Management Systems
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• v.15 no.3
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• pp.231-238
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• 2016

Traditional acceptance sampling plans have focused on the proportion of nonconforming items as an attribute criterion for quality. In today's modern quality management under high quality production environments, the reduction of the deviation from a target value in a quality characteristic has become the most important purpose. In consequence, various inspection plans for the purpose of reducing the deviation from the target value in the quality characteristic have been investigated. In this case, a concept of the quality loss evaluated by the deviation from the target value has been accepted as the variable evaluation criterion of quality. Further, some quality measures based on the quality loss have been devised; e.g. the process loss and the process capability index. Then, as one of inspection plans based on the quality loss, the rigorous design procedure for the variable sampling plan having desired operating characteristics (VS-OC plan) indexed by the quality loss has been proposed by Yen and Chang in 2009. By the way, since the estimator of the quality loss obeys the non-central chi-square distribution, the rigorous design procedure for the VS-OC plan indexed by the quality loss is complicated. In particular, the rigorous design procedure for the VS-OC plan requires a large number of the repetitive and complicated numerical calculation about the non-central chi-square distribution. On the other hand, an approximate design procedure for the VS-OC plan has been proposed before the proposal of the above rigorous design procedure. The approximate design procedure for the VS-OC plan has been constructed by combining Patnaik approximation relating the non-central chi-square distribution to the central chi-square distribution and Wilson-Hilferty approximation relating the central chi-square distribution to the standard normal distribution. Then, the approximate design procedure has been devised as a convenient procedure without complicated and repetitive numerical calculations. In this study, through some comparisons between the rigorous and approximate design procedures, the applicability of the approximate design procedure has been confirmed.

• The Journal of Society for e-Business Studies
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• v.8 no.1
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• pp.85-102
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• 2003

Nowadays an information exchange on XML such as B2B electronic commerce is spreading. Therefore the systematic and stable management mechanism for storing the exchanged information is needed. For this goal there are many research activities for connection between XML application and relational database. But because XML data have hierarchical structures and relational database can store only flat-structured data, we need to make the conversion rule which changes the hierarchical architecture to 2-dimensional information. Accordingly the modeling methodology for storing each structured information in relational database is needed. In this paper, we introduce a XML modeling methodology to design W3C XML schema using UML and we propose a unified design methodology for relational database schema to store XML data efficiently in relational databases. In the second place, in order to verify objectivity of a unified design methodology. By the way of Ronald Bourret, First we introduce the method of the transformation from XML schema to object model and second we translate object model into relational database schema. Therefore we show the mutual consistency between those consequence, and so can verify a unified design methodology.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.340-342
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• 2004

In this paper, we introduce a new category of fuzzy inference systems baled on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects(data, in particular) drawn together by the criteria of proximity, similarity, or functionality. Granulation of information 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 polyminial 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. The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.200-205
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• 1993

A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type 1), linear inference (type 2), and modified linear inference (type 3). The fuzzy c-means clustering and modified complex methods are used in order to identify the preise structure and parameter of fuzzy implication rules, respectively and the least square method is utilized for the identification of optimal consequence parameters. Time series data for gas funace and sewage treatment processes are used to evaluate the performances of the proposed rule-based fuzzy modeling.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.130-133
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• 2000

In this paper, a new design methodology named FNNN(Fuzzy Polynomial Neural Network) algorithm is proposed to identify the structure and parameters of fuzzy model using PNN(Polynomial Neural Network) structure and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and modified quadratic besides the biquadratic polynomial used in the GMDH. The premise of fuzzy inference rules defines by triangular and gaussian type membership function. The fuzzy inference method uses simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture Several numerical example are used to evaluate the performance of out proposed model. Also we used the training data and testing data set to obtain a balance between the approximation and generalization of proposed model.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.236-244
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• 2005

In this study, we introduce a new topology of Fuzzy Polynomial Neural Networks(FPNN) that is based on fuzzy relation and evolutionally optimized Multi-Layer Perceptron, discuss a comprehensive design methodology and carry out a series of numeric experiments. The construction of the evolutionally optimized FPNN(EFPNN) exploits fundamental technologies of Computational Intelligence. The architecture of the resulting EFPNN results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks(PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the EFPNN. The consequence part of the EFPNN is designed using PNN. As the consequence part of the EFPNN, the development of the genetically optimized PNN(gPNN) dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the EFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed EFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.451-453
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• 2012

Conceptual design and manufacturing scheme of a gas generator for 7 tonf class rocket engine were described. The combustion chamber pressure, O/F ratio, and total flow rate were decided to be 6 MPa, 0.321, and 1 kg/s respectively in consequence of the engine system design. Based on the parameters conceptual design of the gas generator was carried out and its outer dimension was about ${\Phi}100{\times}250mm$. Most parts of the gas generator to be jointed together by brazing or TIG welding and, if possible, the strength and leakproof tests are to be conducted in every step for checking the welding section.

• Transactions of the Society of Information Storage Systems
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• v.2 no.3
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• pp.208-213
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• 2006

The present state of the design of swing arm actuators for optical disc drives is to obtain the high efficient dynamic characteristics within a very compact volume. As a necessary consequence, the need of the small form factor (SFF) storage device has been arisen as major interests in the information storage technology. In this paper, we suggest the miniaturized swing arm type actuator that has high efficient dynamic characteristics for SFF optical disk drive (ODD). For the operating mechanism, it uses a tracking electromagnetic (EM) circuit for a focusing motion together. Moreover, due to the size constraint, the thermal stability of optical head is important. Therefore, the actuator is designed to emit the heat, which is generated by optical pick-up, along the actuator body easily. Initial model is designed based on the topology optimization method considering the thermal conductivity. Then, the structural parts of the actuator are modified to maintain the high sensitivity and to have wide control bandwidth by the design of experiments method (DOE) and new concept of decreasing mass and inertia. Finally, a swing arm type actuator for SFF ODD is suggested and its dynamic characteristics are verified.