• East Asian mathematical journal
• /
• v.23 no.1
• /
• pp.103-110
• /
• 2007

The purpose of this paper is to introduce the concept of fuzzy set connected functions and investigate their properties.

• Korean Journal of Mathematics
• /
• v.4 no.2
• /
• pp.95-100
• /
• 1996

In this note, the notion of fuzzy almost s-continuity is introduced and some results related to this notion are obtained.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.16 no.5
• /
• pp.484-493
• /
• 2011

The MPPT algorithm using neuro-fuzzy controller is proposed to improve the performance of fuzzy controller in this paper. The width of membership function and fuzzy rule have an effect on the performance of fuzzy controller. The neuro-fuzzy controller has the response characteristic which is superior to the existing fuzzy controller, because of using the optimal width of the fuzzy membership function through the neural learning. The superior control characteristic of a proposed algorithm is confirmed through simulation and experiment results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1151-1154
• /
• 1993

The purpose of the paper is to explain some heuristic, common sense suppositions of fuzzy control. It is shown that Fuzzy Control is a kind of quasilinear interpolation of prototypes. Control function can be sufficiently exact represented as piecewise-linear function. The best interpolation is connected with normalized intersected fuzzy sets.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.15-15
• /
• 2000

In the past couple of years, there has been increasing interest in the fusion of neural networks and fuzzy logic. Most of the existing fused models have been proposed to implement different types of fuzzy reasoning mechanisms and inevitably they suffer from the dimensionality problem when dealing with complex real-world problem. To overcome the problem, we propose the self-organizing networks with activation nodes based on fuzzy inference and polynomial function. The proposed model consists of two parts, one is fuzzy nodes which each node is operated as a small fuzzy system with fuzzy implication rules, and its fuzzy system operates with Gaussian or triangular MF in Premise part and constant or regression polynomials in consequence part. the other is polynomial nodes which several types of high-order polynomials such as linear, quadratic, and cubic form are used and are connected as various kinds of multi-variable inputs. To demonstrate the effectiveness of the proposed method, time series data for gas furnace process has been applied.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.10 no.5
• /
• pp.147-159
• /
• 2002

This paper proposes a method to recognize the noisiness of road images connected with the extraction of lane-related information in order to prevent the usage of erroneous information. The proposed method uses a fuzzy neural network(FNN) with the back-Propagation loaming algorithm. The U decides road images good or bad with respect to visibility of lane marks on road images. Most input parameters to the FNN are extracted from an edge distribution function(EDF), a function of edge histogram constructed by edge phase and norm. The shape of the EDF is deeply correlated to the visibility of lane marks of road image. Experimental results obtained by simulations with real images taken by various lighting and weather conditions show that the proposed method was quite successful, providing decision-making of noisiness with about 99%.

• Proceedings of the ESK Conference
• /
• 1996.04a
• /
• pp.113-127
• /
• 1996

In Human Reliability Analysis(HRA), the uncertainties involved in many factors that affect human reliability have to be represented as the quantitative forms. Conventional probability- based human reliability theory is used to evaluate the effect of those uncertainties but it is pointed out that the actual human reliability should be different from that of conventional one. Conventional HRA makes use of error rates, however, it is difficult to collect data enough to estimate these error rates, and the estimates of error rates are dependent only on engineering judgement. In this paper, the error possibility that is proposed by Onisawa is used to represent human reliability, and the error possibility is obtained by use of fuzzy reasoning that plays an important role to clarify the relation between human reliability and human error. Also, assuming these factors are connected to the top event through Fault Tree structure, the influence and correlation of these factors are measured by fuzzy operation. When a fuzzy operation is applied to Fault Tree Analysis, it is possible to simplify the operation applying the logic disjuction and logic conjuction to structure function, and the structure of human reliability can be represented as membership function of the top event. Also, on the basis of the the membership function, the characteristics of human reliability can be evaluated by use of the concept of pattern recognition.

• Journal of the Ergonomics Society of Korea
• /
• v.16 no.2
• /
• pp.1-14
• /
• 1997

In conventional probability-based human reliability analysis, the basic human error rates are modified by experts to consider the influences of many factors that affect human reliability. However, these influences are not easily represented quantitatively, because the relation between human reliability and each of these factors in not clear. In this paper, the relation is expressed quantitatively. Furthermore, human reliability is represented by error possibilities proposed by Onisawa, which is a fuzzy set on the interval [0,1]. Fuzzy reasoning is used in this method in order to obtain error possibilities. And, it is supposed that many basic events affected by the above factors are connected to the top event through Fault Tree structure, and an estimate of the top event expressed by a member- ship function is obtained by using the fuzzy measure and fuzzy integral. Finally, a numerical example of human reliability analysis obtained by this method is given.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.46
• /
• pp.173-180
• /
• 1998

In conventional probability-based quality evaluation of products with qualitative characteristics, many factors that affect the evaluation are not easily represented quantitatively, because the relation between reliability of human evaluator and each of these factors is not clear. In order to evaluate the quality of product with qualitative characteristics quantitatively, in this paper, the relation is represented as the shape of possibility distribution function of fuzzy set on the interval [0,1]. Furthermore, fuzzy reasoning is used to obtain the estimates of quality characteristics. And, it is supposed that many quality characteristics affected by the above factors are connected with the final characteristic through hierarchical structures. Finally, using the estimates gained from the final evaluation, qualitative characteristics are evaluated by use of concept of pattern recognition.

• Journal of Advanced Marine Engineering and Technology
• /
• v.38 no.3
• /
• pp.292-301
• /
• 2014

This paper describes development of distributed type independent electro-hydraulic ballast valve remote control system with diagnostic function based on fuzzy inference using redundant Modbus communication and ethernet Modbus TCP/IP. Diagnostic function estimate degradation of system components and diagnose system faults, which results in shortage of fault maintenance time and improvement of system safety. Slave devices which control each valve and master device which command, monitor and diagnose slave system are developed. Slave devices are connected to master device with redundant Modbus networks and master device is connected to ship's integrated control system with Modbus TCP/IP. Also this paper describes development of simulator to test and confirm whether developed system can be integrated with ship's integrated control and monitoring system.