• Title/Summary/Keyword: Fuzzy Rules Based

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A Basic Study on the Collision Risk Inference Reflecting Maneuverability of a Ship(I) (선박의 조종성능을 반영한 충돌위험도 추론에 관한 기초연구(I))

  • Ahn, Jin-Hyeong;Rhee, Key-Pyo
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.29 no.1
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    • pp.77-83
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    • 2005
  • In collision avoidance problem of a ship, collision risk model is usually set up using the interview results fron experts who sit on a simulator by varying parameters, in which DCPA and TCPA are commonly used. This method, however, has the weakness in that not only it is expensive but also it shows different results depending on the inerviewees and other navigational parameters. In this study, a fuzzy inference system is designed based on own ship's maneuverability verified fron simulation instead of interviewing navigators. The time and distance corresponding to the collision risk value on which avoidance maneuver should be started are set to the minimum marginal time at which own ship starts maneuvering and the minimum marginal distance suggested by marine traffic rules respectively. This system can be recorfigured as a nonlinearity-strengthened one by increasing the number of fuzzy membership functions.

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Automatic Control for Ship Automatic Collision Avoidance Support (선박자동충돌회피지원을 위한 자동제어)

  • 임남균
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2003.05a
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    • pp.81-86
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    • 2003
  • The studies on automatic ship collision avoidance system, which have been carried out last 10 years, are facing on new situation due to newly developed high technology such as computer and other information system. It was almost impossible to make it used in real navigation 3-4 years ago because of the absence of the tool to get other ship's information, however recently developed technology suggests new possibility. This study is carried out to develop the algorithm of automatic ship collision support system. The NOMOTO ship's mathematic model is adopted in simulation for its simplicity. The fuzzy reason rules are used for course-keeping system and for the calculation of Collision Risk using TCPA/DCPA. Moreover‘encounter type’ between two ships is analyzed based on Regulations for Preventing Collisions at Sea and collision avoidance action is suggested, Some situations are simulated to verity the developed algorithm and appropriate avoidance action is shown in the simulation.

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Automatic Control for Ship Collision Avoidance Support System (선박충돌회피지원 시스템을 위한 자동제어)

  • Im, Nam-Kyun
    • Journal of Navigation and Port Research
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    • v.27 no.4
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    • pp.375-381
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    • 2003
  • The studies on automatic ship collision avoidance system, which have been carried out last 10 years, are facing on new situation due to newly developed high technology such as computer and other information system. It was almost impossible to make it used in real navigation 3-4 years ago because of the absence of the tool to get other ship's information, however recently developed technology suggests new possibility. This study is carried out to develop the algorithm of automatic ship collision support system. The NOMOTO ship's mathematic model is adopted in simulation for its simplicity. The fuzzy reason rules are used for course-keeping system and for the calculation of Collision Risk using TCPA/DCPA. Moreover ‘encounter type’ between two ships is analyzed based on Regulations for Preventing Collisions at Sea and collision avoidance action is suggested. Some situations are simulated to verity the developed algorithm and appropriate avoidance action is shown in the simulation.

Disease Prediction System based on WEB (WEB 기반 질병 예측 시스템)

  • Hong, YouSik;Han, Y.H.;Lee, W.B.
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.3
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    • pp.125-132
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    • 2022
  • The Ministry of Environment recently analyzed the output data of 10 fine dust measuring stations and, as a result, announced that about 60% had an error that the existing atmospheric measurement concentration was higher. In order to accurately predict fine dust, the wind direction and measurement position must be corrected. In this paper, in order to solve these problems, fuzzy rules are used to solve these problems. In addition, in order to calculate the fine particulate sensation index actually felt by pedestrians on the street, a computer simulation experiment was conducted to calculate the fine particulate sensation index in consideration of weather conditions, temperature conditions, humidity conditions, and wind conditions.

An Automatic Control System of the Blood Pressure of Patients Under Surgical Operation

  • Furutani, Eiko;Araki, Mituhiko;Kan, Shugen;Aung, Tun;Onodera, Hisashi;Imamura, Masayuki;Shirakami, Gotaro;Maetani, Shunzo
    • International Journal of Control, Automation, and Systems
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    • v.2 no.1
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    • pp.39-54
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    • 2004
  • We developed an automatic blood pressure control system to maintain the blood pressure of patients at a substantially low level during a surgical operation. The developed system discharges two functions, continuous feedback control of the mean arterial pressure (MAP) by a state-predictive servo controller and risk control based on the inference by fuzzy-like logics and rules using measured data. Twenty-eight clinical applications were made beginning in November 1995, and the effects of the automatic blood pressure control on the operation time and on bleeding were assessed affirmatively by means of Wilcoxon testing. This paper essentially reports the engineering details of the control system.

An Evolutionary Computing Approach to Building Intelligent Frauds Detection System

  • Kim, Jung-Won;Peter Bentley;Chol, Jong-Uk;Kim, Hwa-Soo
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.97-108
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    • 2001
  • Frauds detection is a difficult problem, requiring huge computer resources and complicated search activities Researchers have struggled with the problem. Even though a fee research approaches have claimed that their solution is much better than others, research community has not found 'the best solution'well fitting every fraud. Because of the evolving nature of the frauds. a novel and self-adapting method should be devised. In this research a new approach is suggested to solving frauds in insurance claims credit card transaction. Based on evolutionary computing approach, the method is itself self-adjusting and evolving enough to generate a new self of decision-makin rules. We believe that this new approach will provide a promising alternative to conventional ones, in terms of computation performance and classification accuracy.

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Arduino Sensor based on Traffic Safety System using Intelligence

  • Choi, Myeong-Bok;Hong, You-Sik
    • International Journal of Internet, Broadcasting and Communication
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    • v.9 no.1
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    • pp.18-23
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    • 2017
  • In 2015, 100-car pileup was happened because the safe distance from the car in front did not be kept due to much fog at YoungJong Bridge in South Korea. This is why the road would be benumbed with cold weather in winter. For this weather condition, if the driver of the car in front changed the lane suddenly or suddenly slammed on the brake in fog or freezing area, the braking distance of the real car has to be 2 or 3 times longer than usual. In this paper, we have simulated the function that warns and notice about the fog area or the freezing one in the road using Arduino sensors and Beacon. Also we propose the intelligent traffic system to protect the accidents in winter.

A study on time-varying control of learning parameters in neural networks (신경망 학습 변수의 시변 제어에 관한 연구)

  • 박종철;원상철;최한고
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.12a
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    • pp.201-204
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    • 2000
  • This paper describes a study on the time-varying control of parameters in learning of the neural network. Elman recurrent neural network (RNN) is used to implement the control of parameters. The parameters of learning and momentum rates In the error backpropagation algorithm ate updated at every iteration using fuzzy rules based on performance index. In addition, the gain and slope of the neuron's activation function are also considered time-varying parameters. These function parameters are updated using the gradient descent algorithm. Simulation results show that the auto-tuned learning algorithm results in faster convergence and lower system error than regular backpropagation in the system identification.

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Real-time Fault Detection and Classification of Reactive Ion Etching Using Neural Networks (Neural Networks을 이용한 Reactive Ion Etching 공정의 실시간 오류 검출에 관한 연구)

  • Ryu Kyung-Han;Lee Song-Jae;Soh Dea-Wha;Hong Sang-Jeen
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.7
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    • pp.1588-1593
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    • 2005
  • In coagulant control of water treatment plants, rule extraction, one of datamining categories, was performed for coagulant control of a water treatment plant. Clustering methods were applied to extract control rules from data. These control rules can be used for fully automation of water treatment plants instead of operator's knowledge for plant control. To perform fuzzy clustering, there are some coefficients to be determined and these kinds of studies have been performed over decades such as clustering indices. In this study, statistical indices were taken to calculate the number of clusters. Simultaneously, seed points were found out based on hierarchical clustering. These statistical approaches give information about features of clusters, so it can reduce computing cost and increase accuracy of clustering. The proposed algorithm can play an important role in datamining and knowledge discovery.

CMP: A Context Information-based Routing Scheme with Energy-based Message Prioritization for Delay Tolerant Networks

  • Cabacas, Regin;Ra, In-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.14 no.4
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    • pp.295-304
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    • 2014
  • Communication infrastructure supports wide variety of mobile services such as photo and file sharing, location tracking, social network services and instant messaging. However, instances like power-loss and natural disasters disrupt these communication infrastructures unable to render support to these mobile services. Delay-tolerant networks (DTNs) offer a solution to these problems at hand. By utilizing mobility and opportunistic contacts among mobile devices, a plausible communication network can be establish and enable support to mobile applications. This paper presents an energy-efficient, reliable message delivery routing scheme with message prioritization rules for DTN. It uses the context information of nodes (mobile devices) such as the contact history (location and time of contact), speed/velocity, moving direction to determine the best forwarders among nodes in the network. The remaining energy of the nodes is also used to determine the message types a node can deliver successfully. The simulation results show that proposed approach outperforms Epidemic and Prophet routing schemes in terms of delivery ratio, overhead ratio, delivered messages per types and remaining energy.