• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.4 no.1
• /
• pp.7-11
• /
• 2004

This paper proposes a new immunotronic approach for the fault detection in hardware. The suggested method is, inspired by biology and its implementation is based on genetic algorithm. Tolerance conditions in the immunotronic system for fault detection correspond to the antibodies in the biological immune system. A novel algorithm of generating tolerance conditions is suggested based on the principle of the antibody diversity and GA optimization is employed to select mature tolerance conditions in immunotronic fault detection system. The suggested method is applied to the fault detection for MCNC benchmark FSMs (finite state machines) and its effectiveness is demonstrated by the computer simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.7 no.4
• /
• pp.221-227
• /
• 2007

This paper introduces an on-line particle-filtering-based framework for failure prognosis in nonlinear, non-Gaussian systems. This framework uses a nonlinear state-space model of the plant(with unknown time-varying parameters) and a particle filtering(PF) algorithm to estimate the probability density function(pdf) of the state in real-time. The state pdf estimate is then used to predict the evolution in time of the fault indicator, obtaining as a result the pdf of the remaining useful life(RUL) for the faulty subsystem. This approach provides information about the precision and accuracy of long-term predictions, RUL expectations, and 95% confidence intervals for the condition under study. Data from a seeded fault test for a UH-60 planetary carrier plate are used to validate the proposed methodology.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.2
• /
• pp.116-120
• /
• 2006

This paper discusses an approach for detecting a new edge in color images. The color image is to be represented by a vector field, and the color image edges are detected as differences in the local vector statistics. This method is based on the calculation for the vector angle between two adjacent pixels. Unlike Euclidean distance in RGB space, the vector angle distinguishes the differences in chromaticity, independent of luminance or intensity. The proposed approach can easily accommodate concepts, such as variable template edge detection, as well as the latest developments in vector order statistics for color image processing. In this paper, it is used not a conventional fixed template operator but a variable template operator The variable template is implemented and experimental results for digital color images are included.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.1
• /
• pp.86-93
• /
• 2012

This paper presents a new approach to solve the pursuit problem based on a univector field method. In our proposed method, a set of eight agents works together instantaneously to find suitable moving directions and follow the univector field to pursue and capture a prey agent by surrounding it from eight directions in an infinite grid-world. In addition, a set of strategies is proposed to make the pursuit problem more realistic in the real world environment. This is a general approach, and it can be extended for an environment that contains static or moving obstacles. Experimental results show that our proposed algorithm is effective for the pursuit problem.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.1
• /
• pp.77-85
• /
• 2012

This paper describes a novel approach to adaptive courseware generation. This approach adopts its structure from existing intelligent tutoring systems and introduces a new component called pedagogical scenario model to support pedagogical flexibility in the adaptation process of courseware generation system. The adaptation is carried out using Dynamic Constraint Satisfaction Problem framework, which is a variant of classical Constraint Satisfaction Problem, to deliver courseware tailored to individual learner. Such a framework provides a high level of expressiveness to deal with the particular characteristics of courseware generation problem. Further, it automatically designs a sound courseware satisfying the design constraints imposed by the domain, the pedagogical scenario and learner models.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.1
• /
• pp.59-64
• /
• 2002

In the sender-initiated load balancing algorithms, the sender continues to send an unnecessary request message fur load transfer until a receiver is found while the system load is heavy. Meanwhile, in the receiver-initiated load balancing algorithms, the receiver continues to send an unnecessary request message for load acquisition until a sender is found while the system load is light. These unnecessary request messages result in inefficient communications, low CPU utilization, and low system throughput in distributed systems. To solve these problems, in this paper, we propose a genetic algorithm based approach fur improved sender-initiated and receiver-initiated load balancing. The proposed algorithm is used for new adaptive load balancing approach. Compared with the conventional sender-initiated and receiver-initiated load balancing algorithms, the proposed algorithm decreases the response time and increases the acceptance rate.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.22 no.2
• /
• pp.292-297
• /
• 2013

Nowadays, a strategy of the self-optimizing machining process is an imperative approach to improve the product quality and increase productivity of manufacturing systems. This paper presents a concept of self-optimizing forming system that allows the forming system automatically to adjust the forming parameters online for guarantee the product quality and avoiding the machine stop. An intelligent monitoring system that has the functions of observation, evaluation and diagnostic is developed to evaluate the pully quality during forming process. Any abnormal variation of forming machining parameters could be detected and adjusted by an intelligent control system aiming to maintain the machining stability and the desired product quality. This approach is being practiced on the pully forming machine for evaluating the efficiency of the proposed strategy.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.446-451
• /
• 1992

In this paper, we propose a method to manage production system easily for operators when either equipments or products are changed. And we explain the scheduling AI tool which realizes the proposal method. The tool's knowledge expression consists of models, rules, mathematical expression and fuzzy logic. The model expresses the relations between products and manufacture, and properties of products. The models are separated into three type, equipment model, operation model, and product model. These models are classified by applicable fields as the assembly process or continuous plant process, The model expression of each type is based on object oriented paradigm. We report systems utilizing our approach.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.4 no.2
• /
• pp.205-210
• /
• 2004

This paper deals with rule extraction from data using rough set theory. We construct the rule base in a hierarchical granulation structure by applying core as a classification criteria at each level. When more than one core exist, the coverage is used for the selection of an appropriate one among them to increase the classification rate and accuracy. In Addition, a probabilistic approach is suggested so that the partially useful information included in inconsistent data can be contributed to knowledge reduction in order to decrease the effect of the uncertainty or vagueness of data. As a result, the proposed method yields more proper and efficient rule base in compatability and size. The simulation result shows that it gives a good performance in spite of very simple rules and short conditionals.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.1
• /
• pp.23-26
• /
• 2003

This paper proposes a new artificial immune approach to hardware test. A novel algorithm of generating tolerance conditions is suggested based on the principle of the antibody diversity. Tolerance conditions in artificial immune system correspond to the antibody in biological immune system. The suggested method is applied to the on-line monitoring of a typical FSM (a decade counter) and its effectiveness is demonstrated by the computer simulation.