• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.52-57
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• 2003

In this paper, we propose a Fuzzy Classifier System(FCS) to find a set of fuzzy rules which can carry out the edge detection. The classifier system of Holland can evaluate the usefulness of rules represented by classifiers with repeated learning. FCS makes the classifier system be able to carry out the mapping from continuous inputs to outputs. It is the FCS that applies the method of machine learning to the concept of fuzzy logic. It is that the antecedent and consequent of classifier is same as a fuzzy rule. In this paper, the FCS is the Michigan style. A single fuzzy if-then rule is coded as an individual. The average gray levels which each group of neighbor pixels has are represented into fuzzy set. Then a pixel is decided whether it is edge pixel or not using fuzzy if-then rules. Depending on the average of gray levels, a number of fuzzy rules can be activated, and each rules makes the output. These outputs are aggregated and defuzzified to take new gray value of the pixel. To evaluate this edge detection, we will compare the new gray level of a pixel with gray level obtained by the other edge detection method such as Sobel edge detection. This comparison provides a reinforcement signal for FCS which is reinforcement learning. Also the FCS employs the Genetic Algorithms to make new rules and modify rules when performance of the system needs to be improved.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.2 s.40
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• pp.43-49
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• 2007

In this study, a GIS spatial analysis method adopted fuzzy concept was introduced and land suitability analysis of waste landfill were conducted through this method. Previous studies conducted site evaluation and land suitability analysis by appling spatial overlay of conventional GIS that based on the boolean logic of crisp set. However these method can not consider the uncertainty of spatial data and the incongruity of data classification criteria, because these method handle spatial data based on the boolean logic of crisp set. As not provided trustable analysis result, conventional GIS spatial overlay method lacks opportunity for expanding use in reality. This study selected waste landfill as facility for analysis and applied fuzzy spatial analysis method as an objective approach. In the concrete contents of study, a series process with regard to the definition procedure of membership function for continuous data and the fuzzy input value generation of spatial data for fuzzy analysis is established. As a result, in this study we proposed a method that derive parameters for deciding the membership function of spatial data by considering the criterion of data classification and factor selection for land suitability analysis of waste landfill.

• KSBB Journal
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• v.15 no.1
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• pp.14-21
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• 2000

In this study, algae cultivation using the photobioreactor has been applied to remove the nitrogen and phosphorus compounds in the wastewater of the livestock industry. The optimal ratio of nitrate and ortho-phosphate concentration was found for the enhancement of removal efficiency. To achieve the high density culture of algae, the photobioreactor consisted of optical fibers wes developed to get the sufficient light intensity. The light could be illuminated uniformly from light source to the entire reactor by the optical fibers. The structured kinetic model was proposed to describe the growth rate, consumption rate of nitrates and ortho-phosphates in algae culture. The self-organizing fuzzy logic controller incorporated with genetic algorithm was constructed to control the semi-continuous wastewater treatment system. The proposed fuzzy logic controller was applied to maintain the nitrated concentration at the given set-point with the control of wastewater feeding rate. The experimental results showed that the self-organizing fuzzy logic controller could keep the nitrate concentration and enhance algae growth.

• Journal of KIISE
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• v.45 no.1
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• pp.22-29
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• 2018

Over the decades, neural networks have been successfully used in numerous applications from speech recognition to image classification. However, these neural networks cannot explain their results and one needs to know how and why a specific conclusion was drawn. Most studies focus on extracting binary rules from neural networks, which is often impractical to do, since data sets used for machine learning applications contain continuous values. To fill the gap, this paper presents an algorithm to extract logic rules from a trained neural network for data with continuous attributes. It uses hyperplane-based linear classifiers to extract rules with numeric values from trained weights between input and hidden layers and then combines these classifiers with binary rules learned from hidden and output layers to form non-linear classification rules. Experiments with different datasets show that the proposed approach can accurately extract logical rules for data with nonlinear continuous attributes.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.554-560
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• 2017

Accurate altimetry is required for the reliable flight control of drones or unmanned air vehicles (UAVs), and the radar altimeter is commonly used owing to its accuracy for the ground level. Due to the limitation for size, weight and power consumption, the frequency modulated continuous wave (FMCW) radar is appropriate for drone because it has lower complexity than that of pulse Doppler (PD) radar. Especially, fast-ramp FMCW radar, which transmits linear FM signal during very short period, is generally utilized, because it is robust for the ego-motion of drone. Therefore, we present the design and implementation results of the radar signal processor (RSP) for fast-ramp FMCW radar system. The proposed RSP was designed with Verilog-HDL and implemented with Altera Cyclone-IV FPGA device. Implementation results show that the proposed RSP includes 27,523 logic elements, 15,798 registers and memory of 138Kbits and can measure the altimeter at the rate of 100Hz with the operating frequency of 50MHz.

• Journal of Advanced Navigation Technology
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• v.24 no.2
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• pp.85-91
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• 2020

Recently, a multi-mode radar system was designed for efficient operation of unmanned aerial vehicles (UAVs) in various environments, which has the advantage of being able to integrate and utilize methods of the pulse Doppler (PD) radar and the frequency modulated continuous wave (FMCW) radar. For the range detection part of the multi-mode radar signal processor (RSP), the hardware structure using the FFT processor and the IFFT processor is required to be designed in a way that improves efficiency on the area side. In addition, given the radar application environment that requires a variety of distance resolutions, FFT processors need to support variable-length operations. In this paper, the FFT processor and IFFT processor in multi-mode RSP range estimation are designed and proposed as hardware for a single FFT processor that supports variable length operation of 16-1024 points. The proposed FFT processor designed in hardware description language (HDL) and can be implemented with 7,452 logic elements and 5,116 registers.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.11-17
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• 2008

Typical wireless sensor networks used in structural monitoring are continuous types wherein data transmission is progressive at all time that may include irrelevant and insignificant data and information. Continuous types of wireless monitoring systems often pose problems of handling large-sized data that may deteriorate the performance of the system. The proposed method is to suggest an event-triggered monitoring system that captures and transmits relevant data only. An error signal generated by the Principal Components Analysis (PCA) is utilized as an index for event detection and selective data transmission. With this new monitoring scheme, the remote server is relieved of unwanted data by receiving only relevant information from the wireless sensor networks. The performance of the proposed scheme was verified with simulation studies.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.9
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• pp.545-551
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• 2004

CBTC(Communication Based Train Control) System can improve train operation efficiency by realizing moving block system which makes a continuous train interval control in accordance with the position and speed of train. Adopting radio transmission to make a continuous detection of train position and transmit the control data from the ground to a train, CBTC needs dedicated train operation and control algorithm which should be quite different from the conventional track-circuit-based train control system. This paper provides a train operation display and control algorithm for CBTC system in making train interval control, train route control and train supervision. Signalling pattern diagram is devised to analyze the train interval control mechanism of moving block system, and interlocking logic is devised to represent the train route control mechanism of moving block system. For train supervision, train occupation status on railway are displayed by using the segment which virtually divide the whole railway. The proposed method has been successfully applied to the development of CBTC system for the standardized AGT(automatic guided transit) which is under construction now in Korea, and also can be applied to any other CBTC system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.60-65
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• 2012

This paper presents a method for occluded object based motion estimation and tracking system in dynamic image sequences using particle filter with 3D reconstruction. A unique characteristic of this study is its ability to cope with partial occlusion based continuous motion estimation using particle filter inspired from the mirror neuron system in human brain. To update a prior knowledge about the shape or motion of objects, firstly, fundamental 3D reconstruction based occlusion tracing method is applied and object landmarks are determined. And optical flow based motion vector is estimated from the movement of the landmarks. When arbitrary partial occlusions are occurred, the continuous motion of the hidden parts of object can be estimated by particle filter with optical flow. The resistance of the resulting estimation to partial occlusions enables the more accurate detection and handling of more severe occlusions.

• Journal of Electrical Engineering and Technology
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• v.1 no.1
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• pp.63-72
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• 2006

The purpose of this raper is to address the negative impedance instability in DC/DC converters. We present the negative impedance instability of PWM DC/DC converters loaded by constant power loads (CPLs). An approach to design digital controllers for DC/DC converters Is presented. The proposed method, called Power Alignment control technique, is applied to DC/DC step-down choppers operating in continuous conduction or discontinuous conduction modes with CPLs. This approach uses two predefined state variables instead of conventional pulse width modulation (PWM) to regulate the output voltage. A comparator compares actual output voltage with the reference and then switches between the appropriate states. It needs few logic gates and comparators to be implemented thus, making it extremely simple and easy to develop using a low-cost application specific integrated circuit (ASIC) for converters with CPLs. Furthermore, stability of the proposed controllers using the small signal analysis as well as the second theorem of Lyapunov is verified. Finally, simulation and analytical results are presented to describe and verify the proposed technique.