• Title/Summary/Keyword: Fuzzy Application

Search Result 912, Processing Time 0.028 seconds

An Induced Hesitant Linguistic Aggregation Operator and Its Application for Creating Fuzzy Ontology

  • Kong, Mingming;Ren, Fangling;Park, Doo-Soon;Hao, Fei;Pei, Zheng
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.12 no.10
    • /
    • pp.4952-4975
    • /
    • 2018
  • An induced hesitant linguistic aggregation operator is investigated in the paper, in which, hesitant fuzzy linguistic evaluation values are associated with probabilistic information. To deal with these hesitant fuzzy linguistic information, an induced hesitant fuzzy linguistic probabilistic ordered weighted averaging (IHFLPOWA) operator is proposed, monotonicity, boundary and idempotency of IHFLPOWA are proved. Then andness, orness and the entropy of dispersion of IHFLPOWA are analyzed, which are used to characterize the weighting vector of the operator, these properties show that IHFLPOWA is extensions of the induced linguistic ordered weighted averaging operator and linguistic probabilistic aggregation operator. In this paper, IHFLPOWA is utilized to gather linguistic information and create fuzzy ontologies, and a movie fuzzy ontology as an illustrative case study is used to show the elaboration of the proposed method and comparison with the existing linguistic aggregation operators, it seems that the IHFLPOWA operator is an useful and alternative operator for dealing with hesitant fuzzy linguistic information with probabilistic information.

A Design of GA-based TSK Fuzzy Classifier and Its Application (GA 기반 TSK 퍼지 분류기의 설계와 응용)

  • 곽근창;김승석;유정웅;김승석
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • v.11 no.8
    • /
    • pp.754-759
    • /
    • 2001
  • In this paper, we propose a TSK(Takagi-Sugeno-Kang)-type fuzzy classifier using PCA(Principal Component Analysis), FCM(Fuzzy c-Means) clustering, ANFIS(Adaptive Neuro-Fuzzy Inference System) and hybrid GA(Genetic Algorithm). First, input data is transformed to reduce correlation among the data components by PCA. FCM clustering is applied to obtain a initial TSK-type fuzzy classifier. Parameter identification is performed by AGA(Adaptive GA) and RLSE(Recursive Least Square Estimate). Finally, we applied the proposed method to Iris data classificationl problems and obtained a better performance than previous works.

  • PDF

Comparing type-1, interval and general type-2 fuzzy approach for dealing with uncertainties in active control

  • Farzaneh Shahabian Moghaddam;Hashem Shariatmadar
    • Smart Structures and Systems
    • /
    • v.31 no.2
    • /
    • pp.199-212
    • /
    • 2023
  • Nowadays fuzzy logic in control applications is a well-recognized alternative, and this is thanks to its inherent advantages. Generalized type-2 fuzzy sets allow for a third dimension to capture higher order uncertainty and therefore offer a very powerful model for uncertainty handling in real world applications. With the recent advances that allowed the performance of general type-2 fuzzy logic controllers to increase, it is now expected to see the widespread of type-2 fuzzy logic controllers to many challenging applications in particular in problems of structural control, that is the case study in this paper. It should be highlighted that this is the first application of general type-2 fuzzy approach in civil structures. In the following, general type-2 fuzzy logic controller (GT2FLC) will be used for active control of a 9-story nonlinear benchmark building. The design of type-1 and interval type-2 fuzzy logic controllers is also considered for the purpose of comparison with the GT2FLC. The performance of the controller is validated through the computer simulation on MATLAB. It is demonstrated that extra design degrees of freedom achieved by GT2FLC, allow a greater potential to better model and handle the uncertainties involved in the nature of earthquakes and control systems. GT2FLC outperforms successfully a control system that uses T1 and IT2 FLCs.

APPLICATION OF SIR-C DATA FOR EXPLORATION OF MINERALIZEDD ZONES (HWANGGANG-Rl, KOREA)

  • Jiang, Wei W.;Park, S.W.;Park, Jeong-Ho;Lee, Cahng-Won;Kim, Duk-Jin;So, Byung-Han;So, C. S.;Moon, Wooil M.
    • Proceedings of the KSRS Conference
    • /
    • 1999.11a
    • /
    • pp.158-164
    • /
    • 1999
  • This paper investigated and evaluated the NASA's Shuttle Imaging Radar-C (SIR-C) multiple frequency SAR data for differential backscattering effects of microwave from the surface geological materials overlying the skarn type mineralization. Although an integrated approach in mineral exploration is more cost effective and is well in use, there are still many technical and scientific issues to be further investigated and researched. In this study we have reprocessed several sets of previously surveyed exploration data and experimented with fuzzy logic digital fusion of the preprocessed data with respect to chosen exploration targets. Among the numerous fuzzy logic operators, which are currently available for a data driven integrated exploration strategy, we used varying combinations of fuzzy MIN, fuzzy MAX, and fuzzy SUM operators along with Gamma operator for fusion of exploration data, including the contact metamorphic zone information. The final exploration target tested was a skarn type W-Mo-F mineralization in the study area. The fuzzy logic derived mineral potential anomaly almost exactly matched the differential backscattering anomalies on the C-band and L-band SIR_C data when overlaid on each other. Although this high degree of correlation between these two data sets is remarkable, the differential backscattering anomaly over the skarn type W-Mo-F mineralization in the study area requires further investigation.

  • PDF

Classification Customer characteristic of Pole-Transformer using Fuzzy Model (퍼지 모델을 이용한 주상 변압기 수용가 특성 구분)

  • Kim, Gi-Hyun;Im, Jin-Soon;Yun, Sang-Yun;Oh, Jung-Hwan;Kim, Jae-Chul
    • Proceedings of the KIEE Conference
    • /
    • 1999.11b
    • /
    • pp.276-278
    • /
    • 1999
  • In this paper, we analyze customers' working electric energy (kWh) which is served pole-transformer in order to reduce peak load current error which is generated in application load correlation equation. The characteristic of electric load which customers are using is classified by customer's working electric energy (kWh) and ratio of cooling equipment possession. For the input data of fuzzy model, we used to kWh on April which represents basic load and kWh which is increased from April to August. The April kWh is used to classify into large, medium, small customer. Also, the increased kWh is used to know information of cooling equipment possession. For the output value of fuzzy model, we can determined peak load current limit in application load correlation equation.

  • PDF

A Study on the Theoretical Structure Modeling using ISM & FSM (ISM과 FSM을 이용한 이론적 구조모형화에 대한 연구)

  • 조성훈;정민용
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.21 no.47
    • /
    • pp.219-232
    • /
    • 1998
  • A lot of difficulties exist in analyzing the structure of a system owing to the complex and organic relations in the systems we face in reality. Focuses have been put on the research of optimal solution in a defined structure, however, on the assumption that the structure of the system has been already defined. With the grasping of the structure as the most prior condition, ISM(Interpretive Structural Modeling) and FSM(Fuzzy Structural Modeling) are suggested as solutions in this paper. ISM uses the systematic application of some elementary notions of graph theory and boolean algebra, FSM uses Fuzzy conception for representing relationship between elements. In FSM, the entries in the relation matrix are taken to value on the interval [0,1] by virtue of a fuzzy binary relation. Numeric examples are used as the actual application as follows.

  • PDF

Adaptive Fuzzy IMM Algorithm for Position Tracking of Maneuvering Target (기동표적의 위치추적을 위한 적응 퍼지 IMM 알고리즘)

  • Kim, Hyun-Sik
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • v.17 no.7
    • /
    • pp.855-861
    • /
    • 2007
  • In real system application, the IMM-based position tracking algorithm requires robust performance, less computing resources and easy design procedure with respect to the uncertain target maneuvering, To solve these problems, an adaptive fuzzy interacting multiple model (AFIMM) algorithm, which is based on the well-defined basis sub-models and well-adjusted mode transition probabilities (MTPs), is proposed. Simulation results show that the proposed algorithm effectively solves the problems in the real system application of the IMM-based position tracking algorithm.

Application of Fuzzy Theory and Analytic Hierarchy Process(AHP) for Developing Occupational Stress Index

  • Jung, Hwa Shik
    • Journal of the Ergonomics Society of Korea
    • /
    • v.17 no.2
    • /
    • pp.33-48
    • /
    • 1998
  • This paper illustrates the application of Fuzzy Theory and Analytic Hierarchy Process(AHP) for developing Occupational Stress Index(OSI). The purpose of the OSI development is for future prediction and problem solving of prevailing occupational stress. In developing OSI, the concept of fuzzy set theory was introduced to determine the existence and level of perceived occupational stress instead of actually measuring the strain parameters. The AHP is adopted to collect different weighting factors, since there exist various perceptions and responses to the occupational stress by different individuals. The validation study revealed that the OSI is a reliable predictor of work-related accident and illness and the physiological health of employees. Creating preventive measures, such as early detection of stress, proper placement and promotion of employees, and job enlargement will be possible by using this OSI effectively.

  • PDF

Fuzzy c-Logistic Regression Model in the Presence of Noise Cluster

  • Alanzado, Arnold C.;Miyamoto, Sadaaki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 2003.09a
    • /
    • pp.431-434
    • /
    • 2003
  • In this paper we introduce a modified objective function for fuzzy c-means clustering with logistic regression model in the presence of noise cluster. The logistic regression model is commonly used to describe the effect of one or several explanatory variables on a binary response variable. In real application there is very often no sharp boundary between clusters so that fuzzy clustering is often better suited for the data.

  • PDF

A Study on the Stability Assessment and Application of Rock Slope (암반사면의 안정성 평가 및 적용에 관한 연구)

  • 안종필;박주원;오수동
    • Proceedings of the Korean Geotechical Society Conference
    • /
    • 1999.10a
    • /
    • pp.177-184
    • /
    • 1999
  • In general tile evaluation process of rock slope stability is an ambiguous system which is made up of ideas subjected to practical experience of an expert. This paper aims to propose more effective methods that helps engineers to evaluate the stability of rock slope by using RMR(Rock Mass Rating for the Geomechanics Classification) and Stereo-graphic Projection and Fuzzy Approximate Reasoning Concept. the result of this paper is that a rational evaluation of rock slope stability and countermeasures can be achieved thorough RMR. and Stereo-graphic Projection and Fuzzy Approximate Reasoning Concept.

  • PDF