• Title/Summary/Keyword: Evidential Reasoning

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Multiresponse Surfaces Optimization Based on Evidential Reasoning Theory

  • He, Zhen;Zhang, Yuxuan
    • International Journal of Quality Innovation
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    • v.5 no.1
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    • pp.43-51
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    • 2004
  • During process design or process optimization, it is quite common for experimenters to find optimum operating conditions for several responses simultaneously. The traditional multiresponse surfaces optimization methods do not consider the uncertain relationship among these responses sufficiently. For this reason, the authors propose an optimization method based on evidential reasoning theory by Dempster and Shafer. By maximizing the basic probability assignment function, which indicates the degree of belief that certain operating condition is the solution of this multiresponse surfaces optimization problem, the desirable operating condition can be found.

Design of Problem Solving Primitives for Efficient Evidential Reasoning

  • Lee, Gye Sung
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.3
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    • pp.49-58
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    • 2019
  • Efficient evidential reasoning is an important issue in the development of advanced knowledge based systems. Efficiency is closely related to the design of problems solving methods adopted in the system. The explicit modeling of problem-solving structures is suggested for efficient and effective reasoning. It is pointed out that the problem-solving method framework is often too coarse-grained and too abstract to specify the detailed design and implementation of a reasoning system. Therefore, as a key step in developing a new reasoning scheme based on properties of the problem, the problem-solving method framework is expanded by introducing finer grained problem-solving primitives and defining an overall control structure in terms of these primitives. Once the individual components of the control structure are defined in terms of problem solving primitives, the overall control algorithm for the reasoning system can be represented in terms of a finite state diagram.

Evaluating the effectiveness of ERS for vessel oil spills using fuzzy evidential reasoning

  • Wang, H.Y.;Ren, J.;Yang, J.Q.;Wang, J.
    • Ocean Systems Engineering
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    • v.5 no.3
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    • pp.161-179
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    • 2015
  • An emergency response system (ERS) for vessel oil spills is a complex and dynamic system comprising a number of subsystems and activities. Failures may occur during the emergency response operations, this has negative impacts on the effectiveness of the ERS. Of the classes of problems in analyzing failures, the lack of quantitative data is fundamental. In fact, most of the empirical data collected via questionnaire survey is subjective in nature and is inevitably associated with uncertainties caused by the human being's inability to provide complete judgement. In addition, incomplete information and/or vagueness of the meaning about the failures add difficulties in evaluating the effectiveness of the system. Therefore this paper proposes a framework to evaluate the ERS effectiveness by using the combination of fuzzy reasoning and evidential synthesis approaches. Based on analyzing the procedure of ERS for oil spills, the failures in the system could be identified, using Analytic Hierarchy Process(AHP)to determine the relative weight of identified failures. Fuzzy reasoning combined with evidential synthesis is applied to evaluate the effectiveness of ERS for oil spills under uncertainties last. The proposed method is capable of dealing with uncertainties in data including ignorance and vagueness which traditional methods cannot effectively handle. A case study is used to illustrate the application of the proposed method.

A Study on the Explanation Scheme using Problem Solving Primitives

  • Lee, Gye Sung
    • International Journal of Advanced Culture Technology
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    • v.7 no.3
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    • pp.158-165
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    • 2019
  • Knowledge based system includes tools for constructing, testing, validating and refining the system along with user interfaces. An important issue in the design of a complete knowledge based system is the ability to produce explanations. Explanations are not just a series of rules involved in reasoning track. More detailed and explicit form of explanations is required not only for reliable reasoning but also for maintainability of the knowledge based system. This requires the explanation mechanisms to extend from knowledge oriented analysis to task oriented explanations. The explicit modeling of problem solving structures is suggested for explanation generation as well as for efficient and effective reasoning. Unlike other explanation scheme such as feedback explanation, the detailed, smaller and explicit representation of problem solving constructs can provide the system with capability of quality explanation. As a key step to development for explanation scheme, the problem solving methods are broken down into a finer grained problem solving primitives. The system records all the steps with problem solving primitives and knowledge involved in the reasoning. These are used to validate the conclusion of the consultation through explanations. The system provides user interfaces and uses specific templates for generating explanation text.

Rule-based Detection of Vehicles in Traffic Scenes (교통영상에서의 규칙에 기반한 차량영역 검출기법)

  • Park, Young-Tae
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.3
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    • pp.31-40
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    • 2000
  • A robust scheme of locating and counting the number of vehicles m urban traffic scenes, a core component of vision-based traffic monitoring systems, is presented The method is based on the evidential reasoning, where vehicle evidences m the background subtraction Image are obtained by a new locally optimum thresholding, and the evidences are merged by three heuristic rules using the geometric constraints The locally optimum thresholding guarantees the separation of bright and dark evidences of vehicles even when the vehicles are overlapped or when the vehicles have similar color to the background Experimental results on diverse traffic scenes show that the detection performance is very robust to the operating conditions such as the camera location and the weather The method may be applied even when vehicle movement is not observed since a static Image IS processed without the use of frame difference.

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Real-Time Eye Tracking Using IR Stereo Camera for Indoor and Outdoor Environments

  • Lim, Sungsoo;Lee, Daeho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.8
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    • pp.3965-3983
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    • 2017
  • We propose a novel eye tracking method that can estimate 3D world coordinates using an infrared (IR) stereo camera for indoor and outdoor environments. This method first detects dark evidences such as eyes, eyebrows and mouths by fast multi-level thresholding. Among these evidences, eye pair evidences are detected by evidential reasoning and geometrical rules. For robust accuracy, two classifiers based on multiple layer perceptron (MLP) using gradient local binary patterns (GLBPs) verify whether the detected evidences are real eye pairs or not. Finally, the 3D world coordinates of detected eyes are calculated by region-based stereo matching. Compared with other eye detection methods, the proposed method can detect the eyes of people wearing sunglasses due to the use of the IR spectrum. Especially, when people are in dark environments such as driving at nighttime, driving in an indoor carpark, or passing through a tunnel, human eyes can be robustly detected because we use active IR illuminators. In the experimental results, it is shown that the proposed method can detect eye pairs with high performance in real-time under variable illumination conditions. Therefore, the proposed method can contribute to human-computer interactions (HCIs) and intelligent transportation systems (ITSs) applications such as gaze tracking, windshield head-up display and drowsiness detection.

FUZZY HYPERCUBES: A New Inference Machines

  • Kang, Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.2 no.2
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    • pp.34-41
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    • 1992
  • A robust and reliable learning and reasoning mechanism is addressed based upon fuzzy set theory and fuzzy associative memories. The mechanism stores a priori an initial knowledge base via approximate learning and utilizes this information for decision-making systems via fuzzy inferencing. We called this fuzzy computer architecture a 'fuzzy hypercube' processing all the rules in one clock period in parallel. Fuzzy hypercubes can be applied to control of a class of complex and highly nonlinear systems which suffer from vagueness uncertainty. Moreover, evidential aspects of a fuzzy hypercube are treated to assess the degree of certainty or reliability together with parameter sensitivity.

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Fusion of Sonar and Laser Sensor for Mobile Robot Environment Recognition

  • Kim, Kyung-Hoon;Cho, Hyung-Suck
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.91.3-91
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    • 2001
  • A sensor fusion scheme for mobile robot environment recognition that incorporates range data and contour data is proposed. Ultrasonic sensor provides coarse spatial description but guarantees open space with no obstacle within sonic cone with relatively high belief. Laser structured light system provides detailed contour description of environment but prone to light noise and is easily affected by surface reflectivity. Overall fusion process is composed of two stages: Noise elimination and belief updates. Dempster Shafer´s evidential reasoning is applied at each stage. Open space estimation from sonar range measurements brings elimination of noisy lines from laser sensor. Comparing actual sonar data to the simulated sonar data enables ...

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Obstacle Detection in Nighttime Traffic Scenes using IR Images (IR 영상을 이용한 교통영상에서의 야간장애물 검지 기법)

  • 박동렬;박영태
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.633-636
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    • 1999
  • We present a robust scheme of detecting obstacles such as vehicles, human beings, and other artificial structures that may cause serious traffic accidents in the nighttime driving. Obstacle regions are detected by the evidential reasoning rules that combine the isolated regions obtained by the phase-directed edge-linking and the hot evidence information. Preliminary experimental results show that the performance is robust to nighttime infrared scenes having various types of obstacles

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A Design Decision Support Framework for Evaluation of Design Options in Passenger Ship Engine Room (여객선 기관실의 설계 옵션 평가를 위한 결정 지원 프레임 워크)

  • Kim, Soo Woong
    • Journal of the Korean Society of Mechanical Technology
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    • v.13 no.2
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    • pp.9-19
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    • 2011
  • Most real world design evaluation and risk-based decision support combine quantitative and qualitative (linguistic) variables. Decision making based on conventional mathematics that combines qualitative and quantitative concepts always exhibit difficulty in modelling actual problems. The successful selection process for choosing a design/procurement proposal is based on a high degree of technical integrity, safety levels and low costs in construction, corrective measures, maintenance, operation, inspection and preventive measures. In this paper, a design decision support framework using a composite structure methodology grounded in approximate reasoning approach and evidential reasoning method is suggested for design evaluation of machinery space of a ship engine room at the initial stages. An illustrative example is used to demonstrate the application of the proposed framework.