• Journal of Internet Computing and Services
• /
• v.2 no.2
• /
• pp.117-126
• /
• 2001

This paper presents fuzzy Pr/T nets to represent the fuzzy production rules of a knowledge-based system in the level of first-order predicate logic. The fuzzy Pr/T nets are fuzzy extension of the Pr/T nets. Based on the fuzzy Pr/T net, we propose a fuzzy reasoning algorithm. This algorithm is much closer to human intuition and reasoning than other methods because of using the proper belief functions according to fuzzy concepts in fuzzy production rules.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.13 no.4
• /
• pp.56-67
• /
• 1999

In this paper, the new composition Irethod of global and local fuzzy reasoning concepts is proposed to reduce, optimize and automatically acquire the number of rules, without any lose of the general performances in conventional fuzzy controllers. In order to control the interaction between global reasoning and local reasoning, the DNA coding algorithm is introduced to the local fuzzy reasoning of the proposed composition fuzzy reasoning rrethod. The method is awlied to the real liquid level control system for the purpose of evaluating the performance. The sinru1ation results show that the proposed technique can control the system with higher accuracy and automatical1y acquire the fuzzy rules with rmre feasibility, than the conventional methods.ethods.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.7 no.3
• /
• pp.398-403
• /
• 2006

In this paper, we describe a fuzzy threshold selection technique for feature extraction in digital color images. this is achieved by the formulation a fuzzy inference system that evaluates threshold for feature configurations. The system uses two fuzzy measures. They capture desirable characteristics of features such as dependency of local intensity and continuity in an image. We give a graphical description of a nonlinear sketch feature extraction filter and design the fuzzy inference system in terms of the characteristics of the feature. Through the design, we provide selection method on the choice of a threshold to achieve certain characteristics of the extracted features. Experimental results show the usefulness of our fuzzy threshold inference approach which is able to extract features without human intervention.

• The KIPS Transactions:PartB
• /
• v.10B no.7
• /
• pp.757-768
• /
• 2003

This paper proposes a weighted fuzzy reasoning algorithm for rule-based systems based on weighted fuzzy Pr/T nets, where the certainty factors of the fuzzy production rules, the truth values of the predicates appearing in the rules and the weights representing the importance of the predicates are represented by the fuzzy numbers. The proposed algorithm is more flexible and much closer to human intuition and reasoning than other methods : $\circled1$ calculate the certainty factors using by the simple min and max operations based on the only certainty factors of the fuzzy production rules without the weights of the predicates[10] : $\circled2$ evaluate the belief of the fuzzy production rules using by the belief evaluation functions according to fuzzy concepts in the fuzzy rules without the weights of the predicates[12], because this algorithm uses the weights representing the importance of the predicates in the fuzzy production rules.

• Fire Science and Engineering
• /
• v.18 no.4
• /
• pp.42-51
• /
• 2004

This paper presents a study on the analysis of fire detection system using fuzzy logic with input variables of temperature and smoke density. The input variables for the fuzzy logic algorithm are measured by fire experiment of small scale with temperature detector and smoke detector. The antecedent part of fuzzy rules consists of temperature and smoke density, and the consequent part consists of fire possibility. Also the triangular fuzzy membership function is chosen for input variables and fuzzy rules to simplify computation. In order to calculate fuzzy values of such fuzzy system, a computer program is developed with Matlab based on graphics user interface. The experiment was conducted with paper and ethanol to simulate flaming fire and with plastic and sawdust to model smoldering fire. The results showed that the fire detection system presented here was able to diagnose fire very precisely. With the help of algorithms using fuzzy logic we could distinguish whether fire or not.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.10 no.4
• /
• pp.293-298
• /
• 2000

In fuzzy expert systems or database systems that have volumes of fuzzy data or large fuzzy rules, the inference time is much increased. Therefore, a high performance parallel fuzzy computing environment is needed. In this paper, we propose a parallel fuzzy inference mechanism in parallel computing environments. In this, fuzzy rules are distributed and executed simultaneously. The ONE_TO_ALL algorithm is used to broadcast the fuzzy input input vector to the all nodes. The results of the MIN/MAX operations are transferred to the output processor by the ALL_TO_ONE algorithm. By parallel processing of fuzzy or data, the parallel fuzzy inference algortihm extracts effective and achieves and achieves a good speed factor.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.6
• /
• pp.613-620
• /
• 1992

Recently, there are lots of research work on fuzzy Information theory for many practlcal applications. As the fuzzy control systems become to be sophisticated, they demand more fuzzy parameters, membership functions and fuzzy Inference rules. Eventually, they need effective parallel computing architectures to implement those complex fuzzy inference rules. In this paper, a optical fuzzy Inference system based on 2-D spatial light modulator and digital image board Is Implemented as a new approach for real-time parallel fuzzy computing system. From its good experimental results on the practical fuzzy airconditioner system, a new real-time Opto Fuzzy Inference system Is suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.193-196
• /
• 2008

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. In this paper, we propose 2. Cao's fuzzy inference method using learning ability witch is used a gradient descent method in order to improve the performances. Because it is difficult to determine the relation matrix elements by trial and error method which is needed many hours and effort. Simulation results are applied linear and nonlinear system show that the proposed inference method has good performances.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.6
• /
• pp.731-737
• /
• 2007

In this paper, we propose a system for analyzing nutrition status based on hierarchical fuzzy inference approach, where the hierarchical fuzzy approach used to analyze the transition process on the nutritional status from an obesity degree, the previous nutritional status, and the eating pattern with an individual. Moreover we discussed about the selection method of fuzzy membership intervals of the next layer to improve the reliability of inference results in hierarchical fuzzy system, where their intervals are modified by using statistical information of the defuzzified results obtained from the previous layer. To show the effectiveness of this system, we evaluated the nutritional status from the information of anthropometric measurement, biochemical test, and INQ on 113 people over the age of 65, and also analyzed their nutritional status.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2001.05a
• /
• pp.184-197
• /
• 2001

In this paper, we provide the formal specification of a fuzzy object inference language and propose ICOT(Integrated C-Object Tool) as its implementation for knowledge-based programming with the disjunctive fuzzy information. The novelty of our model is that it seamlessly combines object inference and fuzzy reasoning into a unified framework without compromising a compatibility with extant databases, especially object-relational ones. In this model most of the object-oriented paradigm is successfully expressed in terms of relational constructs, tailoring fuzzy reasoning style to be well suited to the framework of the databases. It turns out to be useful in preserving its conceptual simplicity as well, since simple-to-use is one of important criteria in designing the databases. Additionally this model considerably enhanced the semantic expressiveness of data allowing disjunctive fuzzy information.