• Title/Summary/Keyword: Fuzzy evaluation

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A two-step interval risk assessment method for water inrush during seaside tunnel excavation

  • Zhou, Binghua;Xue, Yiguo;Li, Zhiqiang;Gao, Haidong;Su, Maoxin;Qiu, Daohong;Kong, Fanmeng
    • Geomechanics and Engineering
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    • v.28 no.6
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    • pp.573-584
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    • 2022
  • Water inrush may occur during seaside urban tunnel excavation. Various factors affect the water inrush, and the water inrush mechanism is complex. In this study, nine evaluation indices having potential effects on water inrush were analysed. Specifically, the geographic and geomorphic conditions, unfavourable geology, distance from the tunnel to sea, strength of the surrounding rock, groundwater level, tidal action, cyclical footage, grouting pressure, and grouting reinforced region were analysed. Furthermore, a two-step interval risk assessment method for water inrush management during seaside urban tunnel excavation was developed by a multi-index system and interval risk assessment comprised of an interval analytic hierarchy process, fuzzy comprehensive evaluation, and relative superiority analysis. The novel assessment method was applied to the Haicang Tunnel successfully. A preliminary interval risk assessment method for water inrush was performed based on engineering geological conditions. As a result, the risk level fell into a risk level IV, which represents a section with high risk. Subsequently, a secondary interval risk assessment method was performed based on engineering geological conditions and construction conditions. The risk level of water inrush is reduced to a risk level II. The results agreed with the current tunnel situation, which verified the reliability of this approach.

On the optimum design of reinforcement systems for old masonry railway tunnels

  • Ghyasvand, Soheil;Fahimifar, Ahamd;Nejad, Fereidoon Moghadas
    • Geomechanics and Engineering
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    • v.28 no.2
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    • pp.145-155
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    • 2022
  • Safety is a most important parameters in underground railway transportation; Also stability of underground tunnel is very important in tunneling engineering. Design of a reliable support system requires an evaluation of both ground demand and support capacity. Iran's traditional railway tunnels are mainly supported with masonry structures or unsupported in high quality rock masses. A decrease in rock mass quality due to changes in groundwater regime creep and fatigue in rock and similar phenomena causes tunnel safety to decrease during time. The case study is an old tunnel in Iran, called "Keshvar"; it is more than 50 years old railway organization. In operating this Tunnel, until the several problems came up based on stability and leaking water. The goal of study is evaluation of the various reinforcement systems for supporting of the tunnel. The optimal selection of the reinforcement system is examined using TOPSIS Fuzzy method in light of the looming and available uncertainties. Several factors such as; the tunnel span, maintenance, drainage, sealing, ventilation, cost and safety were based to choose the method and system of designing. Therefore, by identifying these parameters, an optimal reinforcement system was selected and introduced. Based on optimization system for analysis, it is revealed that the systematic rock bolts and shotcrete protection had a most appropriate result for these kind of tunnel in Iran.

Data-Driven Approaches for Evaluating Countries in the International Construction Market

  • Lee, Kang-Wook;Han, Seung H.
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.496-500
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    • 2015
  • International construction projects are inherently more risky than domestic projects with multi-dimensional uncertainties that require complementary risk management at both the country and project levels. However, despite a growing need for systematic country evaluations, most studies have focused on project-level decisions and lack country-based approaches for firms in the construction industry. Accordingly, this study suggests data-driven approaches for evaluating countries using two quantitative models. The first is a two-stage country segmentation model that not only screens negative countries based on country attractiveness (macro-segmentation) but also identifies promising countries based on the level of past project performance in a given country (micro-segmentation). The second is a multi-criteria country segmentation model that combines a firm's business objective with the country evaluation process based on Kraljic's matrix and fuzzy preference relations (FPR). These models utilize not only secondary data from internationally reputable institutions but also performance data on Korean firms from 1990 to 2014 to evaluate 29 countries. The proposed approaches enable firms to enhance their decision-making capacity for evaluating and selecting countries at the early stage of corporate strategy development.

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A Music Recommendation System based on Fuzzy Inference with User Emotion and Environments (사용자 감정 및 환경을 고려한 퍼지추론 기반 음악추천 시스템)

  • 임성수;조성배
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10b
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    • pp.541-543
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    • 2004
  • 인터넷의 대중화로 인하여 인터넷상에 많은 음악 정보가 존재하게 되었다. 이에 따라서 사용자에게 음악 정보를 손쉽게 접근할 수 있게 해주는 서비스뿐만 아니라, 사용자에게 적절한 음악을 추천해주는 서비스의 중요성도 증가하고 있다. 본 논문에서는 사용자의 상황을 인식하고 사용자와의 대화를 통해서 적절한 음악을 추천해주는 인공 DJ를 제안한다 인공 DJ는 센서로부터 실내 온도, 습도, 조도, 소음을 입력받고, 인터넷을 통하여 날씨 정보를 입력받고, 사용자의 감정추론을 위하여 사용자가 입력하는 문장을 분석하여 Activation-Evaluation Space상에서 사용자의 감정을 표시함으로써 사용자의 주변 상황을 인식하고, 사용자의 성향을 파악하여 IF-THEN 규칙을 만들어 대수학적 연산자(algebraic operator)를 통한 퍼지 추론 방법을 이용하여 적절한 음악을 추천한다. 피험자 10명을 대상으로 실시한 설문조사 결과 제안하는 방법이 유용함을 알 수 있었다.

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Saliency Score-Based Visualization for Data Quality Evaluation

  • Kim, Yong Ki;Lee, Keon Myung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.4
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    • pp.289-294
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    • 2015
  • Data analysts explore collections of data to search for valuable information using various techniques and tricks. Garbage in, garbage out is a well-recognized idiom that emphasizes the importance of the quality of data in data analysis. It is therefore crucial to validate the data quality in the early stage of data analysis, and an effective method of evaluating the quality of data is hence required. In this paper, a method to visually characterize the quality of data using the notion of a saliency score is introduced. The saliency score is a measure comprising five indexes that captures certain aspects of data quality. Some experiment results are presented to show the applicability of proposed method.

Adaptive Image Segmentation Based on Histogram Transition Zone Analysis

  • Acuna, Rafael Guillermo Gonzalez;Mery, Domingo;Klette, Reinhard
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.4
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    • pp.299-307
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    • 2016
  • While segmenting "complex" images (with multiple objects, many details, etc.) we experienced a need to explore new ways for time-efficient and meaningful image segmentation. In this paper we propose a new technique for image segmentation which has only one variable for controlling the expected number of segments. The algorithm focuses on the treatment of pixels in transition zones between various label distributions. Results of the proposed algorithm (e.g. on the Berkeley image segmentation dataset) are comparable to those of GMM or HMM-EM segmentation, but are achieved with significantly reduced computation time.

Features of an Error Correction Memory to Enhance Technical Texts Authoring in LELIE

  • SAINT-DIZIER, Patrick
    • International Journal of Knowledge Content Development & Technology
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    • v.5 no.2
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    • pp.75-101
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    • 2015
  • In this paper, we investigate the notion of error correction memory applied to technical texts. The main purpose is to introduce flexibility and context sensitivity in the detection and the correction of errors related to Constrained Natural Language (CNL) principles. This is realized by enhancing error detection paired with relatively generic correction patterns and contextual correction recommendations. Patterns are induced from previous corrections made by technical writers for a given type of text. The impact of such an error correction memory is also investigated from the point of view of the technical writer's cognitive activity. The notion of error correction memory is developed within the framework of the LELIE project an experiment is carried out on the case of fuzzy lexical items and negation, which are both major problems in technical writing. Language processing and knowledge representation aspects are developed together with evaluation directions.

Development of New Management Prediction Support System based on Non-stochastic Model

  • Kaino, Toshihiro;Hirota, Kaoru;Mitsuta, Akimichi;Miura, Yasuyuki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.7-10
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    • 2003
  • In the field of financial technology, it is the U.S. initiative, and Japan is obliged to flattery in many respect. Currently Japan is in a too much defenseless situation that the economic structure is based on U.S. theory, In the conventional stochastic theory, it is also face that the prediction sometimes does not hit in the actual problem because it assumes a known probability distribution, none of which illustrates the real situation. A new research and development of management prediction support system is proposed based on fuzzy measures, that deals with the ambiguous, subjective evaluation by the people living in the real world well. Especially, the system will support venture, small and medium companies.

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Improved Post-Filtering Method Using Context Compensation

  • Kim, Be-Deu-Ro;Lee, Jee-Hyong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.2
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    • pp.119-124
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    • 2016
  • According to the expansion of smartphone penetration and development of wearable device, personal context information can be easily collected. To use this information, the context aware recommender system has been actively studied. The key issue in this field is how to deal with the context information, as users are influenced by different contexts while rating items. But measuring the similarity among contexts is not a trivial task. To solve this problem, we propose context aware post-filtering to apply the context compensation. To be specific, we calculate the compensation for different context information by measuring their average. After reflecting the compensation of the rating data, the mechanism recommends the items to the user. Based on the item recommendation list, we recover the rating score considering the context information. To verify the effectiveness of the proposed method, we use the real movie rating dataset. Experimental evaluation shows that our proposed method outperforms several state-of-the-art approaches.

Establishment of Matlab-based MCDA Interactive Model for the Sensitivity of the Preferred Alternatives to the Number of Criteria (Matlab기반의 다중의사결정 기준 변화에 따른 민감도 분석)

  • Lim, Kwang-Suop;Lee, Dong-Ryul;Lee, Chang-Hae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.297-301
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    • 2009
  • The impact of adding additional Multi-Criteria Decision Analysis (MCDA) criteria is demonstrated because current research shows MCDA for flood damage has been applied using only a few criteria but for better results the MCDA approach needs to apply more criteria for evaluating the alternatives. By adding additional criteria into MCDA, the capability to make the best alternatives more diverse and show the decision maker more differences in the scores of the alternatives to allow the decision maker to discriminate is significantly improved. The target region for a demonstration application of the methodology was the Suyoung River Basin in Korea. The 1991 Gladys flood event and five different return periods were used as a case study to demonstrate the proposed methodology of evaluation of various flood damage reduction alternatives.

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