• Title/Summary/Keyword: Entropy Weight

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Evaluation of Agricultural Drought Disaster Vulnerability Using Analytic Hierarchy Process (AHP) and Entropy Weighting Method (계층화분석 및 엔트로피 가중치 산정 방법에 따른 농업가뭄재해 취약성 평가)

  • Mun, Young-Sik;Nam, Won-Ho;Yang, Mi-Hye;Shin, Ji-Hyeon;Jeon, Min-Gi;Kim, Taegon;Lee, Seung-Yong;Lee, Kwang-Ya
    • Journal of The Korean Society of Agricultural Engineers
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    • v.63 no.3
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    • pp.13-26
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    • 2021
  • Recent drought events in the South Korea and the magnitude of drought losses indicate the continuing vulnerability of the agricultural drought. Various studies have been performed on drought hazard assessment at the regional scales, but until recently, drought management has been response oriented with little attention to mitigation and preparedness. A vulnerability assessment is introduced in order to preemptively respond to agricultural drought and to predict the occurrence of drought. This paper presents a method for spatial, Geographic Information Systems-based assessment of agricultural drought vulnerability in South Korea. It was hypothesized that the key 14 items that define agricultural drought vulnerability were meteorological, agricultural reservoir, social, and adaptability factors. Also, this study is to analyze agricultural drought vulnerability by comparing vulnerability assessment according to weighting method. The weight of the evaluation elements is expressed through the Analytic Hierarchy Process (AHP), which includes subjective elements such as surveys, and the Entropy method using attribute information of the evaluation items. The agricultural drought vulnerability map was created through development of a numerical weighting scheme to evaluate the drought potential of the classes within each factor. This vulnerability assessment is calculated the vulnerability index based on the weight, and analyze the vulnerable map from 2015 to 2019. The identification of agricultural drought vulnerability is an essential step in addressing the issue of drought vulnerability in the South Korea and can lead to mitigation-oriented drought management and supports government policymaking.

Stability evaluation for the excavation face of shield tunnel across the Yangtze River by multi-factor analysis

  • Xue, Yiguo;Li, Xin;Qiu, Daohong;Ma, Xinmin;Kong, Fanmeng;Qu, Chuanqi;Zhao, Ying
    • Geomechanics and Engineering
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    • v.19 no.3
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    • pp.283-293
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    • 2019
  • Evaluating the stability of the excavation face of the cross-river shield tunnel with good accuracy is considered as a nonlinear and multivariable complex issue. Understanding the stability evaluation method of the shield tunnel excavation face is vital to operate and control the shield machine during shield tunneling. Considering the instability mechanism of the excavation face of the cross-river shield and the characteristics of this engineering, seven evaluation indexes of the stability of the excavation face were selected, i.e., the over-span ratio, buried depth of the tunnel, groundwater condition, soil permeability, internal friction angle, soil cohesion and advancing speed. The weight of each evaluation index was obtained by using the analytic hierarchy process and the entropy weight method. The evaluation model of the cross-river shield construction excavation face stability is established based on the idea point method. The feasibility of the evaluation model was verified by the engineering application in a cross-river shield tunnel project in China. Results obtained via the evaluation model are in good agreement with the actual construction situation. The proposed evaluation method is demonstrated as a promising and innovative method for the stability evaluation and safety construction of the cross-river shield tunnel engineerings.

An Analysis of Quality Efficiency of Loan Consultants in a Bank using Shannon's Entropy and PCA-DEA Model (Entropy와 PCA-DEA 모형을 이용한 은행 대출상담사의 서비스 품질 효율성 분석)

  • Choi, Jang Ki;Kim, Kyeongtaek;Suh, Jae Joon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.3
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    • pp.7-17
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    • 2017
  • Loan consultants assist clients with loan application processing and loan decisions. Their duties may include contacting people to ask if they want a loan, meeting with loan applicants and explaining different loan options. We studied the efficiency of service quality of loan consultants contracted to a bank in Korea. They do not work as a team, but do work independently. Since he/she is not an employee of the bank, the consultant is paid solely in proportion to how much he/she sell loans. In this study, a consultant is considered as a decision making unit (DMU) in the DEA (Data Envelopment Analysis) model. We use a principal component analysis-data envelopment analysis (PCA-DEA) model integrated with Shannon's Entropy to evaluate quality efficiency of the consultants. We adopt a three-stage process to calculate the efficiency of service quality of the consultants. In the first stage, we use PCA to obtain 6 synthetic indicators, including 4 input indicators and 2 output indicators, from survey results in which questionnaire items are constructed on the basis of SERVQUAL model. In the second stage, 3 DEA models allowing negative values are used to calculate the relative efficiency of each DMU. In the third stage, the weight of each result is calculated on the basis of Shannon's Entropy theory, and then we generate a comprehensive efficiency score using it. An example illustrates the proposed process of evaluating the relative quality efficiency of the loan consultants and how to use the efficiency to improve the service quality of the consultants.

Comparative Evaluation of User Similarity Weight for Improving Prediction Accuracy in Personalized Recommender System (개인화 추천 시스템의 예측 정확도 향상을 위한 사용자 유사도 가중치에 대한 비교 평가)

  • Jung Kyung-Yong;Lee Jung-Hyun
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.42 no.6
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    • pp.63-74
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    • 2005
  • In Electronic Commerce, the latest most of the personalized recommender systems have applied to the collaborative filtering technique. This method calculates the weight of similarity among users who have a similar preference degree in order to predict and recommend the item which hits to propensity of users. In this case, we commonly use Pearson Correlation Coefficient. However, this method is feasible to calculate a correlation if only there are the items that two users evaluated a preference degree in common. Accordingly, the accuracy of prediction falls. The weight of similarity can affect not only the case which predicts the item which hits to propensity of users, but also the performance of the personalized recommender system. In this study, we verify the improvement of the prediction accuracy through an experiment after observing the rule of the weight of similarity applying Vector similarity, Entropy, Inverse user frequency, and Default voting of Information Retrieval field. The result shows that the method combining the weight of similarity using the Entropy with Default voting got the most efficient performance.

Lake Vulnerability Assessment (호소의 취약성 평가)

  • Kim, Eung-Seok;Yoon, Ki-Yong;Lee, Seung-Hyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.11
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    • pp.6877-6883
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    • 2014
  • The continuous social development has led to increasing pollution in lakes. This study proposed the LVRI (Lake Vulnerability Resilience Indicator) based on the vulnerability assessment of climate change for an environmental risk assessment in lakes sufferign water pollution in an integrated aspect of the characteristics in lake watersheds. A total of 11 representative assessment factors were selected and constructed for 6 lake basins in the Geum River Watershed to calculate the exposure, sensitivity and adaptation indicators in a vulnerability assessment classification system. The weight coefficients for assessment factors of the LVRI were also calculated using the Entropy method. This study also compared the rank results of the lake environmental risk with/without the weight coefficients of assessment factors for the practical application of the proposed lake environmental risk assessment method. The lake environmental risk results estimated in this study can be used for long-term water quality analysis and management in lakes.

Supply Chain Collaboration Degree of Manufacturing Enterprises Using Matter-Element Method

  • Xiao, Qiang;Yao, Shuangshuang;Qiang, Mengjun
    • Journal of Information Processing Systems
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    • v.17 no.5
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    • pp.918-932
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    • 2021
  • Evaluation of the collaboration of the upstream and downstream enterprises in the manufacturing supply chain is important to improve their synergistic effect. From the supply chain perspective, this study establishes the evaluation model of the manufacturing enterprise collaboration on the basis of fuzzy entropy according to synergistic theory. Downstream enterprises carry out coordinated capital, business, and information flows as subsystems and research enterprises as composite systems. From the three subsystems, the collaboration evaluation index is selected as the order parameter. The compound fuzzy matter-element matrix is established by using its improved algorithm. Subordinate membership and standard deviation fuzzy matter-element matrixes are constructed. Index weight is determined using the entropy weight method. The closeness of each matter element is then calculated. Through a representative of the home appliance industry, namely, Gree Electric Appliances Inc. of Zhuhai, empirical analysis of data in 2011-2017 from the company and its upstream and downstream enterprise collaboration shows a good trend, but the coordinated development has not reached stability. Gree Electric Appliances Inc. of Zhuhai need to strengthen the synergy with upstream and downstream enterprises in terms of cash, business, and information flows to enhance competitiveness. Experimental results show that this method can provide precise suggestions for enterprises, improve the degree of collaboration, and accelerate the development and upgrading of the manufacturing industry.

Latent Semantic Analysis Approach for Document Summarization Based on Word Embeddings

  • Al-Sabahi, Kamal;Zuping, Zhang;Kang, Yang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.254-276
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    • 2019
  • Since the amount of information on the internet is growing rapidly, it is not easy for a user to find relevant information for his/her query. To tackle this issue, the researchers are paying much attention to Document Summarization. The key point in any successful document summarizer is a good document representation. The traditional approaches based on word overlapping mostly fail to produce that kind of representation. Word embedding has shown good performance allowing words to match on a semantic level. Naively concatenating word embeddings makes common words dominant which in turn diminish the representation quality. In this paper, we employ word embeddings to improve the weighting schemes for calculating the Latent Semantic Analysis input matrix. Two embedding-based weighting schemes are proposed and then combined to calculate the values of this matrix. They are modified versions of the augment weight and the entropy frequency that combine the strength of traditional weighting schemes and word embedding. The proposed approach is evaluated on three English datasets, DUC 2002, DUC 2004 and Multilingual 2015 Single-document Summarization. Experimental results on the three datasets show that the proposed model achieved competitive performance compared to the state-of-the-art leading to a conclusion that it provides a better document representation and a better document summary as a result.

Research on the Coupling Coordination Relationship between Regional Information Technology Level and Economic Development

  • Li, Jin-yang;kim, Hyung-Ho;Yang, Jun-Won
    • International journal of advanced smart convergence
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    • v.11 no.2
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    • pp.153-162
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    • 2022
  • The impact of the information technology industry on economic development is becoming increasingly important. In this study, we take China's provincial-level regions from 2015 to 2020 as the research object, comprehensively evaluates the level of their information technology systems by the entropy weight method, and then measures the coupling coordination relationship between the information technology system and the economic development system by the coupling coordination degree model. As a result, we found that the income of the information technology industry, the investment of talents and science research have the most important influence on the level of the information technology system. During the research period, with increasing values, the coupling degree of the two systems was at a high level. Affected by development strategies, diffusion effects and industrial relocation, the coupling degree in the central and western regions has shown a rapid growth trend. The coordination degree of the two systems is relatively low, and 83.9% of the provinces are in the medium-low coordination stage. The information technology industry has obviously promoted economic development. Besides, relevant policies should be introduced to effectively support and guide the high-quality development of the information technology industry and promote the high-level coordinated development of the two systems.

Optimal Associative Neighborhood Mining using Representative Attribute (대표 속성을 이용한 최적 연관 이웃 마이닝)

  • Jung Kyung-Yong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.43 no.4 s.310
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    • pp.50-57
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    • 2006
  • In Electronic Commerce, the latest most of the personalized recommender systems have applied to the collaborative filtering technique. This method calculates the weight of similarity among users who have a similar preference degree in order to predict and recommend the item which hits to propensity of users. In this case, we commonly use Pearson Correlation Coefficient. However, this method is feasible to calculate a correlation if only there are the items that two users evaluated a preference degree in common. Accordingly, the accuracy of prediction falls. The weight of similarity can affect not only the case which predicts the item which hits to propensity of users, but also the performance of the personalized recommender system. In this study, we verify the improvement of the prediction accuracy through an experiment after observing the rule of the weight of similarity applying Vector similarity, Entropy, Inverse user frequency, and Default voting of Information Retrieval field. The result shows that the method combining the weight of similarity using the Entropy with Default voting got the most efficient performance.

HANDLING MISSING VALUES IN FUZZY c-MEANS

  • Miyamoto, Sadaaki;Takata, Osamu;Unayahara, Kazutaka
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.139-142
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    • 1998
  • Missing values in data for fuzzy c-menas clustering is discussed. Two basic methods of fuzzy c-means, i.e., the standard fuzzy c-means and the entropy method are considered and three options of handling missing values are proposed, among which one is to define a new distance between data with missing values, second is to alter a weight in the new distance, and the third is to fill the missing values by an appropriate numbers. Experimental Results are shown.

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