• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.176-181
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• 2007

This paper presents evolvable neural networks based on a developmental model for navigation control of autonomous mobile robots in dynamic operating environments. Bio-inspired mechanisms have been applied to autonomous design of artificial neural networks for solving practical problems. The proposed neural network architecture is grown from an initial developmental model by a set of production rules of the L-system that are represented by the DNA coding. The L-system is based on parallel rewriting mechanism motivated by the growth models of plants. DNA coding gives an effective method of expressing general production rules. Experiments show that the evolvable neural network designed by the production rules of the L-system develops into a controller for mobile robot navigation to avoid collisions with the obstacles.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1D
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• pp.11-19
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• 2008

Currently, existing car following models among several basic systems of advanced vehicle systems are almost developed related to the physical relation between two vehicles except for the driver's behavior or environmental factors. But the consideration of driver's character and environmental factors on driving are very essential factors for actual application. Hence, we suggested calibrating the degree of driver's discomfort on driving that is the former study to develop a new car following model of advanced vehicle to use in actuality. The degree of driver's discomfortness (Measure-of-Alarmness; MOA)is measured related to the relationship between the following vehicle and the preceding vehicle, the environmental factors and driver's characters in ubiquitous traffic. We made up questions to drivers to obtain the general and the objective measurement of driver's MOA. And the fuzzy logic model for measurement of MOA was constructed based on the results of survey. We verified the suitability of fuzzy logic model through the computation of MOA with several scenarios. And we measured the quantitative degree of driver's discomfortness on car following related to several factors which affect drivers. In accordance with this study, development of car following model applying driver's MOA will promote the actual application of advanced vehicle more effectively than the existing models. Finally, we thought the measurement of driver's MOA will be applied significantly to evaluate safety and comfort of drivers on driving.

• Journal of Environmental Health Sciences
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• v.42 no.5
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• pp.302-313
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• 2016

Objectives: This study was conducted to assess environmental health status on a local scale using environmental health-related indicators. It demonstrated the possibility of using a structural equation model, a methodological approach to provide synthesized information. Methods: Eighteen indicators were selected from official statistical data published by local governments. Each environmental health-related indicator was classified according to the PSR (pressure-state-response) model. Aggregation methods were performed using principal component analysis and fuzzy sets. Results: The five principal components were classified through principal component analysis (PCA) and obtained eigenvalues >1.0 from the initial 18 indicators. The aggregated index was obtained by condensing the original information into two broad and simple categories through fuzzy sets. Conclusion: This could be useful in that the aggregation procedure may provide a basis for establishing environmental health policies and a decision-making process. However, the availability and quality of indicators, assessment of aggregation method bias, choice of weighted scores for indicators, and other factors should be examined in future studies.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.69-74
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• 2005

In this paper, we suggested user assistant soft computing method for 3D effect optimization. In order to maximize 3D effect of image, intervals among cameras have to be set up properly according to distance between cameras and an object. Two data such as interval and distance was obtained to use in neural network as the data for learning. However, if the data for learning was obtained by only human's subjective views, it could be that the obtained data was not optimal for learning because the data had an accidental ewer To obtain optimal data lot learning, we added candidature data to obtained data through data analysis, and then selected the most proper data between the candidature data and the obtained data for learning in neural network. Usually, 3D effect of image was affected by both distance from an object to cameras and an object size. Therefore, we suggested fuzzy inference model which was able to represent two factors like distance and size. Candidature data was added by fuzzy model. In the simulation result, we verified that the mote the obtained data was affected by human's subjective views, the more effective the suggested system was.

• Journal of IKEEE
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• v.15 no.3
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• pp.191-197
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• 2011

An image segmentation model using fuzzy c-means with intuition (FCM-I) model is proposed for the segmentation of magnetic resonance image in this paper. In FCM-I, a measurement called intuition level is adopted so that the intuition level helps to alleviate the effect of noises. A practical magnetic resonance image data set is used for image segmentation experiment and the performance is compared with those of some conventional algorithms. Results show that the segmentation method based on FCM-I compares favorably to several conventional clustering algorithms. Since FCM-I produces cluster prototypes less sensitive to noises and to the selection of involved parameters than the other algorithms, FCM-I is a good candidate for image segmentation problems.

• Journal of Korean Society of Forest Science
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• v.95 no.1
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• pp.38-44
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• 2006

Using GJS and fuzzy sets, a model was developed for evaluating the site-suitability of forest stands for extracting sap of Acer pictum Thunb. var. mono in Mt. Baekun area. In the model, the productivity of sap extraction was expressed as the function of biotic and abiotic site factors. Among the factors, the topographic terrain conditions and accessibility of forest stands were chosen to consider working environment of the sap extraction. The difference in measurements of the factors between sap-extraction and non-sap-extraction forest stands was used in determining the weight of the relative importance for sap extraction productivity. The weight for distance-to-stream, vegetation type and shading condition turned out relatively higher than those for tree age, distance-to-road and DBH. Based on the results, a site-suitability map in Mt. Baekun area for sap extraction was built.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.499-505
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• 2015

Trend Impact Analysis(: TIA) is an advanced forecasting tool used in futures studies for identifying, understanding and analyzing the consequences of unprecedented events on future trends. An adaptive neuro-fuzzy inference system is a kind of artificial neural network that integrates both neural networks and fuzzy logic principles, It is considered to be a universal estimator. In this paper, we propose an advanced mechanism to generate more justifiable estimates to the probability of occurrence of an unprecedented event as a function of time with different degrees of severity using Adaptive Neuro-Fuzzy Inference System(: ANFIS). The key idea of the paper is to enhance the generic process of reasoning with fuzzy logic and neural network by adding the additional step of attributes simulation, as unprecedented events do not occur all of a sudden but rather their occurrence is affected by change in the values of a set of attributes. An ANFIS approach is used to identify the occurrence and severity of an event, depending on the values of its trigger attributes. The trigger attributes can be calculated by a stochastic dynamic model; then different scenarios are generated using Monte-Carlo simulation. To compare the proposed method, a simple simulation is provided concerning the impact of river basin drought on the annual flow of water into a lake.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1302-1306
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• 2004

This paper proposes a model for information filtering (IF) on the Web. The user information need is described into two levels in this model: profiles on category level, and Boolean queries on document level. To efficiently estimate the relevance between the user information need and documents by fuzzy, the user information need is treated as a rough set on the space of documents. The rough set decision theory is used to classify the new documents according to the user information need. In return for this, the new documents are divided into three parts: positive region, boundary region, and negative region. We modified user profile by the user's relevance feedback and discerning words in the documents. In experimental we compared the results of three methods, firstly is to search documents that are not passed the filtering system. Second, search documents that passed the filtering system. Lastly, search documents after modified user profile. The result from using these techniques can obtain higher precision.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.821-828
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• 2011

This paper developed the algorithm for improving the performance the auto pilot in the autonomous vehicle system consisting of the Track keeping control, the Automatic steering, and the Automatic mooring control. The automatic steering is the control device that could save the voyage distance and cost of fuel by reducing the unnecessary burden of driving due to the continuous artificial navigation, and avoiding the route deviation. During the step of the ship autonomic navigation control, since the wind power or the tidal force could make the ship deviate from the fixed course, the automatic steering calculates the difference between actual sailing line and the set course to keep the ship sailing in the vicinity of intended course. first, we could get the transfer function for the modeling of ship according to the Nomoto model. Considering the maneuverability, we propose it as linear model with only 4 degree of freedoms to present the heading angle response to the input of rudder angle. In this paper, the model of ship is derived from the simplified Nomoto model. Since the proposed model considers the maximum angle and rudder rate of the ship auto pilot and also designs the Fuzzy controller based on existing PID controller, the performance of the steering machine is well improved.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.3
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• pp.133-141
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• 2012

Service and manufacturing companies' efforts are increasingly focused on utilizing services to satisfy customers' needs and survive in today's competitive market environment. The value of services depends mainly on service reliability that is identified by satisfaction derived from the relationship between customer and service provider. In this paper, we extend concepts from the failure modes and effects analysis of tangible systems to services. We use an event-based process model to facilitate service design and represent the relationships between functions and failures in a service. The objective of this research is to propose a method for evaluating service reliability based on service processes using fuzzy failure mode effects analysis (FMEA) and grey theory. We define the failure mode of service as interaction ways that can be failed in a service delivery process. The fuzzy set theory is used to characterize service reliability based on linguistic terms during FMEA. Grey theory is employed to determine the degree of relation and ranking among risk factors that are represented as potential failure causes. To demonstrate implementation of the proposed method, we use a case study involving a typical automotive service operation.