• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.159-164
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• 1995

Driving maneuver in car following are affected by not only the factors related to road structure and traffic condition, but also the factors related to driver's cognition to them. So the aim of this research this to model the relation of driver's cognition for car-following distance considering driver's fuzziness for imformation cognition, As a result, driver's cognition of car-following distance model with fuzzy number is proposed. The 'width', which characterizes the fuzzy number can introduce car-following informtion into the model.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.343-346
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• 2012

There are many realistic system necessities on the huge size of rule matrices with any Fuzzy Logical Inferences. This paper indicates the experimental design policy on the PCS design for the Platoon and AOS for the social application with some identical resemblances in between them so that we could use a design for two different usages feasibly.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.171-177
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• 2004

In this paper, we propose a cognition-based navigational algorithm for mobile robots in dynamic environments. The proposed algorithm consists of two main stages: (i) the fuzzy logic-based perception stage that constructs knowledge from the sensory data for subsequent usage in reasoning, and (ii) the planning stage that identifies the path between a starting and a goal position within its environment on the basis of the knowledge base on the environment and information from the perception stage. A mobile robot reasons places and moves to goal using ambiguous information and ambiguous knowledge through ‘perception’ and ‘planning’. We provide computer simulation results for a mobile robot in order to show the validity of the proposed algorithm.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.447-453
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• 2003

Emotion Technology is used in many field such as computer A.I., graphics, robot, and interaction with agent. We focus on the theory, the technology and the features in emotion application. Firstly in the field of theory, there are psychological approach, behavior-based approach, action-selection approach. Secondly in the field of implementation technologies use the learning algorithm, self-organizing map of neural network and fuzzy cognition maps. Thirdly in the field of application, there are software agent, agent robot and entrainment robot. In this paper, we research the case of application and analyze emotion architecture.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.3
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• pp.11-21
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• 2011

The development of computer-based modeling system has allowed the operationalization of cognitive science issues. Human cognition has become one of most interesting research subjects in artificial intelligence to emulate human mentality and behavior. This paper introduces a methodology well-suited for designing the intelligent system of human cognition. The research investigates how to elicit and represent cognitive knowledge obtained from individual city-dwellers through the application of fuzzy relational theory to personal construct theory. Crucial to this research is to implement formally and process interpretatively the psychological cognition of urbanites who interact with their environment in order to offer useful advice on urban problem. What is needed is a techniques to analyze cognitive structures which are embodiments of this perceptive knowledge for human being.

• Korean Journal of Construction Engineering and Management
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• v.1 no.1 s.1
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• pp.53-62
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• 2000

This study proposes FREES(Fuzzy Risk Evaluation Expert System) for analyzing and evaluating risks occurring during the construction process. The feasibility of this system model was tested by virtual scenario. For the development of the model, at first, risk breakdown structure was established based on risks identified in the existing researches, that is quantitative and qualitative. FREES can reflect human cognition process in the risk analysis and evaluation by adopting artificial intelligence fuzzy theory, differentiating the existing quantitative analysis model. The FREES can be applied to all the project phases from planning to operation & maintenance stage.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.167-183
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• 2018

Electroencephalogram (EEG) recording provides a new way to support human-machine communication. It gives us an opportunity to analyze the neuro-dynamics of human cognition. Machine learning is a powerful for the EEG classification. In addition, machine learning can compensate for high variability of EEG when analyzing data in real time. However, the optimal EEG electrode location must be prioritized in order to extract the most relevant features from brain wave data. In this paper, we propose an intelligent system model for the extraction of EEG data by training the optimal electrode location of EEG in a specific problem. The proposed system is basically a fuzzy system and uses a neural network structurally. The fuzzy clustering method is used to determine the optimal number of fuzzy rules using the features extracted from the EEG data. The parameters and weight values found in the process of determining the number of rules determined here must be tuned for optimization in the learning process. Genetic algorithms are used to obtain optimized parameters. We present useful results by using optimal rule numbers and non - symmetric membership function using EEG data for four movements with the right arm through various experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.139-143
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• 2004

Lee et al have proposed a framework for the linguistic map-based navigational planning of a mobile robot on dynamic environment and provided simulation results applied it to the static environment[1], In this paper, we extends the navigational planning of a mobile robot into dynamic environment. There are two kinds of dynamic obstacles： (1) Time-obstacles that change condition of obstacles with time. (2) Space-obstacles that move their position with time. We propose an algorithm which a mobile robot identifies and avoids the two kinds of dynamic obstacles. The proposed algorithm consists of two stages： (1) The fuzzy logic-based perception stage which identifies the dynamic obstacles around a mobile robot by using sensory data and fuzzy rules, (2) The planning stage which plans the path to goal by avoiding the dynamic obstacles[2-6]. We provide computer simulation results for a mobile robot in order to show the validity of the proposed algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.911-914
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• 1993

This paper makes a trial to build the model of car-following in the state of starting to stable driving on the basic of driver's knowledge that is easily characterized by linguistical cognition. There are three main steps in building the model. Firstly, each driver's rule of three testees is studied in linguistical experssion by the interview and questionary surveys that are repeated once a day for ten days. Secondly, quantification of the linguistical expression is investigated by driving experiments that includes the questionary survey to the testee in the test vehicle, and the membership functions of variables of rule are obtained. Thirdly, implicaton and composition of fuzzy inference is made by Max-Min Methods and defuzzification by gravity method. It can be said that the proposed model of car-following based on driver's knowledge is practically allpicable to the estimation of drivering of car-following on trunk roads in urban area.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.13-23
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• 2001

Most current machine vision systems for industrial inspection were developed with one specific task in mind. Hence, these systems are inflexible in the sense that they cannot easily be adapted to other applications. In this paper, a general vision system framework has been developed that can be easily adapted to a variety of industrial web inspection problems. The objective of this system is to automatically locate and identify \\\"defects\\\" on the surface of the material being inspected. This framework is designed to be robust, to be flexible, and to be as computationally simple as possible. To assure robustness this framework employs a combined strategy of top-down and bottom-up control, hierarchical defect models, and uncertain reasoning methods. To make this framework flexible, a modular Blackboard framework is employed. To minimize computational complexity the system incorporates a simple multi-thresholding segmentation scheme, a fuzzy logic focus of attention mechanism for scene analysis operations, and a partitioning if knowledge that allows concurrent parallel processing during recognition.cognition.