• Title/Summary/Keyword: 퍼지센서알고리즘

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Development of RGBW Dimming Control Sensitivity Lighting System based on the Intelligence Algorithm (지능형 알고리즘 기반 RGBW Dimming control LED 감성조명 시스템 개발)

  • Oh, Sung-Kwun;Lim, Sung-Joon;Ma, Chang-Min;Kim, Jin-Yul
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.3
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    • pp.359-364
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    • 2011
  • The study uses department of the sensitivity and fuzzy reasoning, one of artificial intelligence algorithms, so that develop LED lighting system based on fuzzy reasoning for systematical control of the LED color temperature. In the area of sensitivity engineering, by considering the relation between color and emotion expressed as an adjective word, the corresponding sensitivity word can be determined, By taking into consideration the relation between the brain wave measured from the human brain and the color temperature, the preferred lesson subject can be determined. From the decision of the sensitivity word and the lesson subject, we adjust the color temperature of RGB (Red, Green, Blue) LED. In addition, by using the information of the latitude and the longitude from GPS(Global Positioning System), we can calculate the on-line moving altitude of sun. By using the sensor information of both temperature and humidity, we can calculate the discomfort index. By considering the altitude of sun as well as the value of the discomfort index, the illumination of W(white) LED and the color temperature of RGB LED can be determined. The (LED) sensitivity lighting control system is bulit up by considering the sensitivity word, the lesson subject, the altitude of sun, and the discomfort index The developed sensitivity lighting control system leads to more suitable atmosphere and also the enhancement of the efficiency of lesson subjects as well as business affairs.

Development of a Fuzzy Control Based Chainless PAS Bicycle (Fuzzy 제어기 기반의 무체인 파워 보조 자전거 개발)

  • Jeong, Hoi-Seong;Kim, Gwan-Hyung;Lee, Hyung-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.1
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    • pp.119-125
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    • 2012
  • This paper proposes a model for a chainless power assistor system(PAS) that can provide the required power based upon operational status by designing a chainless electric bicycle that can be substituted for a general chain type bicycle and which is also an environmentally friendly means of transportation. This paper designed a fuzzy control algorithm that can intelligently examine operational status through the stopping force sensor of a chainless intelligently auxiliary power system it and also have the power of an auxiliary power system to be controlled by the vehicle's operational status. This paper designed an intelligent electric bicycle that provides auxiliary power to a general bicycle system relying only upon the stepping force of a human and systems to provide auxiliary power to the intelligent chainless bicycle model designing presented.

Implementation of Stimulated Brillouin Scattering in Optical Fiber Sensor for Improved Stability by Using Neuro-Fuzzy Theory (뉴로-퍼지 알고리즘을 적용한 광파이버 유도 브릴루앙 산란 센서의 신뢰도 향상에 관한 연구)

  • Hwang, Kyoung-Jun;Yeom, Keong-Tae;Kim, Yong-Kab
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.1
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    • pp.92-97
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    • 2008
  • This is a research to apply 1310nm single-mode optical fiber to a temperature sensor. The existing study of optical fiber sensor is complicated because it was made with various equipment. To vary scattering, the variation of optical frequency is measured by using Bragg(lattice) or pulse generator and also bulk system is created by YAG laser but there were some difficulties creating experimental environment and it was a problem that the stability of measured data was low. The temperature sensor system using the suggested sBs(stimulated Brillouin scattering:sBs) from this research is much more simplified straight-line system. To improve the trust and accuracy of noises from optical frequency and unclear results, it was analysed by using Neuro-Fuzzy algorithm. we tried to get more correct data than existing system. sBs measure that optical frequency changed due to the variation of temperature. The analyzed change rate of outcome by Fuzzy theory is 1.1 MHz.

Absolute Vehicle Speed Estimation of Unmanned Container Transporter using Neural Network Model (무인 컨테이너 운송차량의 절대속도 추정을 위한 뉴럴 네크워크 모델 적용)

  • Ha, Hee-Kwon;Oh, Kyeung-Heub
    • Journal of Navigation and Port Research
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    • v.28 no.3
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    • pp.227-232
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    • 2004
  • Vehicle dynamics control systems are complex and non-linear, so they have difficulties in developing a controller for the anti-lock braking systems and the auto-traction systems. Currently the fuzzy-logic technique to estimate the absolute vehicle speed supplies good results in normal conditions. But the estimation error in severe braking is discontented In this paper, we estimate the absolute vehicle speed of UCT(Unmanned Container Transporter) by using the wheel speed data from standard anti-lock braking system wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and estimate the absolute vehicle speed, and principal component analysis on input data is used 10 algorithms are verified experimentally to estimate the absolute vehicle speed and one of them is perfectly shown to estimate the vehicle speed within 4% error during a braking maneuver.

Evaluation of Body Movement during Sleep with a Thermopile, Wavelets and Neuro-fuzzy Reasoning

  • Yoon, Young-Ro;Shin, Jae-Woo;Lee, Hyun-Sook;Jose C.Principe
    • Journal of Biomedical Engineering Research
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    • v.25 no.1
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    • pp.5-10
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    • 2004
  • Body movement is one of the important factors in sleep analysis. In this study, a thermopile detector with four channels was implemented as a non-contacting detector of body movement in sleep. Using a thermopile mathematical model and several frames of thermal images, the possibility of detecting body movement was evaluated. Instant body movement signals were evaluated for the upper, lower, and entire body using the Haar wavelet. This decomposition shows the points in time when the upper-body or lower-body movement occurred and the level of body movement. Additionally, partial body movement was decomposed in head-only, whole body, and leg-only movement using the ANFIS algorithm. Finally, three subject's data were evaluated for 60 minutes, and the detection rates of instant and partial body movement, on average, were 96.3% and 89.2%, respectively.

Emotion Recognition and Expression System of User using Multi-Modal Sensor Fusion Algorithm (다중 센서 융합 알고리즘을 이용한 사용자의 감정 인식 및 표현 시스템)

  • Yeom, Hong-Gi;Joo, Jong-Tae;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.1
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    • pp.20-26
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    • 2008
  • As they have more and more intelligence robots or computers these days, so the interaction between intelligence robot(computer) - human is getting more and more important also the emotion recognition and expression are indispensable for interaction between intelligence robot(computer) - human. In this paper, firstly we extract emotional features at speech signal and facial image. Secondly we apply both BL(Bayesian Learning) and PCA(Principal Component Analysis), lastly we classify five emotions patterns(normal, happy, anger, surprise and sad) also, we experiment with decision fusion and feature fusion to enhance emotion recognition rate. The decision fusion method experiment on emotion recognition that result values of each recognition system apply Fuzzy membership function and the feature fusion method selects superior features through SFS(Sequential Forward Selection) method and superior features are applied to Neural Networks based on MLP(Multi Layer Perceptron) for classifying five emotions patterns. and recognized result apply to 2D facial shape for express emotion.

An Implementation of Lighting Control System using Interpretation of Context Conflict based on Priority (우선순위 기반의 상황충돌 해석 조명제어시스템 구현)

  • Seo, Won-Il;Kwon, Sook-Youn;Lim, Jae-Hyun
    • Journal of Internet Computing and Services
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    • v.17 no.1
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    • pp.23-33
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    • 2016
  • The current smart lighting is shaped to offer the lighting environment suitable for current context, after identifying user's action and location through a sensor. The sensor-based context awareness technology just considers a single user, and the studies to interpret many users' various context occurrences and conflicts lack. In existing studies, a fuzzy theory and algorithm including ReBa have been used as the methodology to solve context conflict. The fuzzy theory and algorithm including ReBa just avoid an opportunity of context conflict that may occur by providing services by each area, after the spaces where users are located are classified into many areas. Therefore, they actually cannot be regarded as customized service type that can offer personal preference-based context conflict. This paper proposes a priority-based LED lighting control system interpreting multiple context conflicts, which decides services, based on the granted priority according to context type, when service conflict is faced with, due to simultaneous occurrence of various contexts to many users. This study classifies the residential environment into such five areas as living room, 'bed room, study room, kitchen and bath room, and the contexts that may occur within each area are defined as 20 contexts such as exercising, doing makeup, reading, dining and entering, targeting several users. The proposed system defines various contexts of users using an ontology-based model and gives service of user oriented lighting environment through rule based on standard and context reasoning engine. To solve the issue of various context conflicts among users in the same space and at the same time point, the context in which user concentration is required is set in the highest priority. Also, visual comfort is offered as the best alternative priority in the case of the same priority. In this manner, they are utilized as the criteria for service selection upon conflict occurrence.