• Title/Summary/Keyword: Membership characteristics

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Features Extraction for Classifying Parkinson's Disease Based on Gait Analysis (걸음걸이 분석 기반의 파킨슨병 분류를 위한 특징 추출)

  • Lee, Sang-Hong;Lim, Joon-S.;Shin, Dong-Kun
    • Journal of Internet Computing and Services
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    • v.11 no.6
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    • pp.13-20
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    • 2010
  • This paper presents a measure to classify healthy persons and Parkinson disease patients from the foot pressure of healthy persons and that of Parkinson disease patients using gait analysis based characteristics extraction and Neural Network with Weighted Fuzzy Membership Functions (NEWFM). To extract the inputs to be used in NEWFM, in the first step, the foot pressure data provided by the PhysioBank and changes in foot pressure over time were used to extract four characteristics respectively. In the second step, wavelet coefficients were extracted from the eight characteristics extracted from the previous stage using the wavelet transform (WT). In the final step, 40 inputs were extracted from the extracted wavelet coefficients using statistical methods including the frequency distribution of signals and the amount of variability in the frequency distribution. NEWFM showed high accuracy in the case of the characteristics obtained using differences between the left foot pressure and the right food pressure and in the case of the characteristics obtained using differences in changes in foot pressure over time when healthy persons and Parkinson disease patients were classified by extracting eight characteristics from foot pressure data. Based on these results, the fact that differences between the left and right foot pressures of Parkinson disease patients who show a characteristic of dragging their feet in gaits were relatively smaller than those of healthy persons could be identified through this experiment.

Development of intelligent model to predict the characteristics of biodiesel operated CI engine with hydrogen injection

  • Karrthik, R.S.;Baskaran, S.;Raghunath, M.
    • Advances in Computational Design
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    • v.4 no.4
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    • pp.367-379
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    • 2019
  • Multiple Inputs and Multiple Outputs (MIMO) Fuzzy logic model is developed to predict the engine performance and emission characteristics of pongamia pinnata biodiesel with hydrogen injection. Engine performance and emission characteristics such as brake thermal efficiency (BTE), brake specific energy consumption (BSEC), hydrocarbon (HC), carbon monoxide (CO), carbon dioxide ($CO_2$) and nitrous oxides ($NO_X$) were considered. Experimental investigations were carried out by using four stroke single cylinder constant speed compression ignition engine with the rated power of 5.2 kW at variable load conditions. The performance and emission characteristics are measured using an Exhaust gas analyzer, smoke meter, piezoelectric pressure transducer and crank angle encoder for different fuel blends (Diesel, B10, B20 and B30) and engine load conditions. Fuzzy logic model uses triangular and trapezoidal membership function because of its higher predictive accuracy to predict the engine performance and emission characteristics. Computational results clearly demonstrate that, the proposed fuzzy model has produced fewer deviations and has exhibited higher predictive accuracy with acceptable determination correlation coefficients of 0.99136 to 1 with experimental values. The developed fuzzy logic model has produced good correlation between the fuzzy predicted and experimental values. So it is found to be useful for predicting the engine performance and emission characteristics with limited number of available data.

On the Ship's Berthig Control by introducing the Fuzzy Neural Network (선박 접이안의 퍼지학습제어)

  • 구자윤;이철영
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 1994.04a
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    • pp.55-67
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    • 1994
  • Studies on the ship's automatic navigation & berthing control have been continued by way of solving the ship's mathematical model but the results of such studies have not reached to our satisfactory level due to its non-linear characteristics ar low speed. In this paper the authors propose a new berthing control system which can evaluate as closely as captain's decision-making by using the FNN(Fuzzy Neural Network) controller which can simulate captain's decision-making by using the FNN(Fuzzy neural Network) controller which can simulate captain's knowledge. This berthing controller consists of the navigation subsystem FNN controller and the berthing subsystem FNN controller. The learning data are drawn from Ship Handling Simulator (NavSim NMS90 MK III) and represent the ship motion characteristics internally According to learning procedure both FNN controllers can tune membership functions and identify fuzzy control rules automatically The verified results show the FNN controllers effective to incorporate captain's knowledge and experience of berthing.

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Successful Joint Venture Strategies Based on Data Mining (데이터마이닝 기법을 기반으로 한 성공적인 Joint Venture 전략)

  • Kim, Jin Hyung;Sohn, So Young
    • Journal of Korean Institute of Industrial Engineers
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    • v.33 no.4
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    • pp.424-429
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    • 2007
  • The purpose of this study is to propose types of joint venturesthat can increase the competitivenessof a company in the marketplace. We examine the characteristics of individual venture enterprises based on technology. We considered 16 TEA in order to categorize companies into four groups. Next, we used a multinomial logistic regression model to identify the significant characteristics of a venture company that successfully predicts group membership. Based on this information, we propose various forms of joint venture which complement each other and produce higher overall competence. Our study can provide important feedback information to academics, Policy-makers.

Nonlinear Characteristics of Fuzzy Scatter Partition-Based Fuzzy Inference System

  • Park, Keon-Jun;Huang, Wei;Yu, C.;Kim, Yong K.
    • International journal of advanced smart convergence
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    • v.2 no.1
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    • pp.12-17
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    • 2013
  • This paper introduces the fuzzy scatter partition-based fuzzy inference system to construct the model for nonlinear process to analyze nonlinear characteristics. The fuzzy rules of fuzzy inference systems are generated by partitioning the input space in the scatter form using Fuzzy C-Means (FCM) clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of FCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the parameters of the consequence part are estimated by least square errors. The proposed model is evaluated with the performance using the data widely used in nonlinear process. Finally, this paper shows that the proposed model has the good result for high-dimension nonlinear process.

On the Ship's Berthing Control by introducing the Fuzzy Neural Network (선박 접리안의 퍼지학습제어)

  • 구자윤;이철영
    • Journal of the Korean Institute of Navigation
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    • v.18 no.2
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    • pp.69-81
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    • 1994
  • Studies on the ship's automatic navigation & berthing control have been continued by way of solving the ship's mathematical model, but the results of such studies have not reached to our satisfactory level due to its non-linear characteristics at low speed. In this paper, the authors propose a new berthing control system which can evaluate as closely as cap-tain's decision-making by using the FNN(Fuzzy Neural Network) controller which can simulate captain's knowledge. This berthing controller consists of the navigation subsystem FNN controller and the berthing subsystem FNN controller. The learning data are drawn from Ship Handling Simulator (NavSim NMS-90 MK Ⅲ) and represent the ship motion characteristics internally. According to learning procedure, both FNN controllers can tune membership functions and identify fuzzy control rules automatically. The verified results show the FNN controllers effective to incorporate captain's knowledge and experience of berthing.

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A Study on Korean and English Speaker Recognitions using the Fuzzy Theory (퍼지 이론을 이용한 한국어 및 영어 화자 인식에 관한 연구)

  • 김연숙;김희주;김경재
    • Journal of the Korea Society of Computer and Information
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    • v.7 no.3
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    • pp.49-55
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    • 2002
  • This paper proposes speaker recognition algorithm which includes both the pitch parameter and the fuzzy. This study proposes a pitch detection method for the peak and valley pitch detection function by means of comparing spectra which utilizes the transform characteristics between time and frequency. It measures the similarity to the original spectrum while arbitrarily varying the period in the time domain. It heavily weights the error due to the changing characteristics of the phonemes, while it is strong against noise. In this paper, makes reference pattern using membership function and performs vocal track recognition of common character using fuzzy pattern matching in odor to include time variation width for non-linear utterance time.

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A Study on Korean and Japanese Speaker Recognitions using the Fuzzy Theory (퍼지 이론을 이용한 한국어 및 일어 화자 인식에 관한 연구)

  • 김연숙;김창완
    • Journal of the Korea Society of Computer and Information
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    • v.5 no.3
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    • pp.51-57
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    • 2000
  • This paper proposes speaker recognition algorithm which includes both the pitch and the fuzzy. This study proposes a pitch detection method for the peak and valley pitch detection function by means of comparing spectra which utilizes the transform characteristics between time and frequency. It measures the similarity to the original spectrum while arbitrarily varying the period in the time domain. It heavily weights the error due to the changing characteristics of the phonemes, while it is strong against noise. In this paper, makes reference pattern using membership function and performs vocal track recognition of common character using fuzzy pattern matching in order to include time variation width for non-linear utterance time.

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On the Control of Ship Maneuvering in Channel by Introducing the Fuzzy Neural Network (수로에 있어서 선박조종의 퍼지학습제어)

  • Koo, J. Y.;Lee, C. Y.
    • Journal of Korean Port Research
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    • v.7 no.2
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    • pp.61-68
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    • 1993
  • Studies on the ship's automatic navigation & berthing control have been continued by way of solving the ship's mathematical model, but the results of such studies have not reached to our satisfactory level due to its non-linear characteristics at low speed. In this paper, the authors propose a new control system which can evaluate as closely as captain's decision-making by using the FNN(Fuzzy Neural Network) controller which can simulate captain's knowledge. This controller contains the concept of safety according to channel width. The learning data are drawn from ship Handling simulator(NavSim NMS-90 MK III) and represent the ship motion characteristics internally. According to learning procedure, the FNN controller can tune membership functions and identify fuzzy control rules automatically. The verified results show that the FNN controller is effective to incorporate captain's knowledge and experience of manoeuvrability in channel.

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A Study on the Consciousness of Rural Community Residents' Environment Preservation (농촌지역주민의 환경보전 의식구조에 관한 연구)

  • 김성수;오해섭;고운미
    • Hwankyungkyoyuk
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    • v.12 no.1
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    • pp.348-364
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    • 1999
  • The objectives of this study were: (a) to measure the level of rural community residents' environmental preservation consciousness, (b) to identify the variables related to their level of environmental preservation consciousness, and (c) to provide suggestions to improve their environmental preservation consciousness. The major findings of this study were as follows; 1) Personal characteristics- gender, years of education, age, and income- were related to the rural communities residents' the environmental preservation consciousness. 2) Social characteristics- membership in environmental organizations, participation in environmental preservation campaigns, environmental dispute within their communities, experiences of participation in environmental dispute in their communities, participation in environmental education-were related to the rural community residents' the environmental preservation consciousness. Based on the above findings, the following suggestions are offered: 1) To improve rural community residents' environmental preservation consciousness, residents in rural community should be motivated and encouraged to participate in environmental and agriculture-related organizations. 2) To effectively solve environmental disputes among rural community residents and between rural communities, central and local governments should provide opportunities for rural residents to acquire their sound environmental consciousness. 3) Environmental preservation consciousness should be assessed including affective domain, cognitive domain, and behavioral domain. Appropriate environmental education programs should be developed after considering rural residents' personal characteristics including education level, income, gender, years of residency, and are.

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