• 제목/요약/키워드: ranking model

검색결과 395건 처리시간 0.026초

Seismic induced damageability evaluation of steel buildings: a Fuzzy-TOPSIS method

  • Shahriar, Anjuman;Modirzadeh, Mehdi;Sadiq, Rehan;Tesfamariam, Solomon
    • Earthquakes and Structures
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    • 제3권5호
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    • pp.695-717
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    • 2012
  • Seismic resiliency of new buildings has improved over the years due to better seismic codes and design practices. However, there is still large number of vulnerable and seismically deficient buildings. It is not economically feasible to retrofit and upgrade all vulnerable buildings, thus there is a need for rapid screening tool. Many factors contribute to the damageability of buildings; this makes seismic evaluation a complex multi-criteria decision making problem. Many of these factors are noncommensurable and involve subjectivity in evaluation that highlights the use of fuzzy-based method. In this paper, a risk-based framework earlier proposed by Tesfamariam and Saatcioglu (2008a) is extended using Fuzzy-TOPSIS method and applied to develop an evaluation and ranking scheme for steel buildings. The ranking is based on damageability that can help decision makers interpret the results and take appropriate decision actions. Finally, the application of conceptual model is demonstrated through a case study of 1994 Northridge earthquake data on seismic damage of steel buildings.

Study on Influencing Factors of Camera Balance in MOBA Games - Focused on (MOBA 게임 카메라 밸런스 개선을 위한 영향요소 분석 - 중심으로)

  • LI, JING;Cho, Dong-Min
    • Journal of Korea Multimedia Society
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    • 제23권12호
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    • pp.1565-1575
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    • 2020
  • This study examines the game balance of the MOBA game genre, which was selected as a model item for the Asian Games. The "bird-eye view" was used for a more efficient representation of 3D modeling. Based on that, statistical analysis was conducted to present appropriate game camera settings and camera balance to match the competitive structure of the MOBA game. A review of the game camera settings reveals that 64° to 70° is the angle that minimizes the difference in vision between the two-player teams the most. Through a one-way ANOVA analysis, we found that the user ranking level and SVB value are closely related. Therefore, the factor of the regression equation using the SVB value must have a user ranking level. As a result of the optimized camera focus analysis of , the camera setting methods were classified into 3 types. For main action games, the recommended camera angle is 64°~66°, and the recommended camera focus is 11.2 mm~19.3 mm. For action and strategy games, the camera angle is 66°~68°, camera focus - 19.3 mm~27.3 mm. And lastly, for the main strategy game, the recommended camera angle is 68°~70°, and the camera focus is 27.3 mm~35.3 mm.

A Study on Brand Image Analysis of Gaming Business Corporation using KoBERT and Twitter Data

  • Kim, Hyunji
    • Journal of Korea Game Society
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    • 제21권6호
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    • pp.75-86
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    • 2021
  • Brand image refers to how customers, stakeholders and the market see and recognize the brand. A positive brand image leads to continuous purchases, but a negative brand image is directly linked to consumers' buying behavior, such as stopping purchases, so from the corporate perspective, it needs to be quickly and accurately identified. Currently, methods of investigating brand images include surveys and SNS surveys, which have limited number of samples and are time-consuming and costly. Therefore, in this study, we are going to conduct an emotional analysis of text data on social media by utilizing the machine learning based KoBERT model, and then suggest how to use it for game corporate brand image analysis and verify its performance. The result has proved some degree of usability showing the same ranking within five brands when compared with the BRI Korea's brand reputation ranking.

Relevancy contemplation in medical data analytics and ranking of feature selection algorithms

  • P. Antony Seba;J. V. Bibal Benifa
    • ETRI Journal
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    • 제45권3호
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    • pp.448-461
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    • 2023
  • This article performs a detailed data scrutiny on a chronic kidney disease (CKD) dataset to select efficient instances and relevant features. Data relevancy is investigated using feature extraction, hybrid outlier detection, and handling of missing values. Data instances that do not influence the target are removed using data envelopment analysis to enable reduction of rows. Column reduction is achieved by ranking the attributes through feature selection methodologies, namely, extra-trees classifier, recursive feature elimination, chi-squared test, analysis of variance, and mutual information. These methodologies are ranked via Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) using weight optimization to identify the optimal features for model building from the CKD dataset to facilitate better prediction while diagnosing the severity of the disease. An efficient hybrid ensemble and novel similarity-based classifiers are built using the pruned dataset, and the results are thereafter compared with random forest, AdaBoost, naive Bayes, k-nearest neighbors, and support vector machines. The hybrid ensemble classifier yields a better prediction accuracy of 98.31% for the features selected by extra tree classifier (ETC), which is ranked as the best by TOPSIS.

Keywords and Spatial Based Indexing for Searching the Things on Web

  • Faheem, Muhammad R.;Anees, Tayyaba;Hussain, Muzammil
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권5호
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    • pp.1489-1515
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    • 2022
  • The number of interconnected real-world devices such as sensors, actuators, and physical devices has increased with the advancement of technology. Due to this advancement, users face difficulties searching for the location of these devices, and the central issue is the findability of Things. In the WoT environment, keyword-based and geospatial searching approaches are used to locate these devices anywhere and on the web interface. A few static methods of indexing and ranking are discussed in the literature, but they are not suitable for finding devices dynamically. The authors have proposed a mechanism for dynamic and efficient searching of the devices in this paper. Indexing and ranking approaches can improve dynamic searching in different ways. The present paper has focused on indexing for improving dynamic searching and has indexed the Things Description in Solr. This paper presents the Things Description according to the model of W3C JSON-LD along with the open-access APIs. Search efficiency can be analyzed with query response timings, and the accuracy of response timings is critical for search results. Therefore, in this paper, the authors have evaluated their approach by analyzing the search query response timings and the accuracy of their search results. This study utilized different indexing approaches such as key-words-based, spatial, and hybrid. Results indicate that response time and accuracy are better with the hybrid approach than with keyword-based and spatial indexing approaches.

Re-Ranking Retrieval Model Using Similarity Transformation Based on Gene Algorithm (유전자 알고리즘 기반 유사도 변환을 이용한 순위 재조정 검색 모델)

  • 이재훈;이성주
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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    • pp.331-334
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    • 2005
  • 정보$\cdot$통신과학의 발달로 다양한 영역에서 수많은 정보들이 발생하고 있다. 그 결과 사용자의 요구에 무분별한 응답을 제시하는 검색 모델도 발생하였다. 본 논문은 정보들 사이의 유사도를 변환하고 순위를 재조정하여 더욱 적합한 정보를 상위 순위에 제시함으로써 사용자 요구에 더욱 적합한 정보를 획득할 수 있는 모델에 대해 연구하였다.

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On Auxiliary Linear Programming Problems for Fuzzy Goal Programming (퍼지목표계획(目標計劃) 모형(模型)의 보조문제화(補助問題化))

  • Park, Sang-Gyu
    • Journal of Korean Society for Quality Management
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    • 제20권1호
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    • pp.101-106
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    • 1992
  • In this paper fuzzy goal programming problems with fuzzy constraints and fuzzy coefficients in both matrix and right hand side of the constraints set are considered. Because of fuzzy coefficients in both members of each constraint ranking methods for fuzzy numbers are considered. An additive model to solve fuzzy goal programming problems is formulated. The diversity of each methods provides a lot of different models of auxiliary linear programming problems from which fuzzy solutions to the fuzzy goal programming problem can be obtained.

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Effect Model Simulator에 의한 Rapid Risk Ranking Index 개발

  • 김형석;김윤화;김인원;고재욱
    • Proceedings of the Korean Institute of Industrial Safety Conference
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    • 한국안전학회 1998년도 추계 학술논문발표회 논문집
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    • pp.121-124
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    • 1998
  • 화학공업은 고도의 기술집약적 장치산업이며 가연성 및 반응성이 높은 물질을 고온, 고압하에서 사용ㆍ저장하고 있기 때문에 화재 및 폭발사고의 가능성이 항상 잠재하고 있다. 특히, 화학공장에서 사용하는 대부분의 물질이 BLEVE (Boiling Liquid Expanding Vapor Expansion)와 VCE(Vapor Cloud Explosion)를 유발할 수 있는 가연성 물질이므로 사회적 문제를 야기할 수 있는 중대재해가 발생할 수 있다. (중략)

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A Study on the Win-Loss Prediction Analysis of Korean Professional Baseball by Artificial Intelligence Model (인공지능 모델에 따른 한국 프로야구의 승패 예측 분석에 관한 연구)

  • Kim, Tae-Hun;Lim, Seong-Won;Koh, Jin-Gwang;Lee, Jae-Hak
    • The Journal of Bigdata
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    • 제5권2호
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    • pp.77-84
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    • 2020
  • In this study, we conducted a study on the win-loss predicton analysis of korean professional baseball by artificial intelligence models. Based on the model, we predicted the winner as well as each team's final rank in the league. Additionally, we developed a website for viewers' understanding. In each game's first, third, and fifth inning, we analyze to select the best model that performs the highest accuracy and minimizes errors. Based on the result, we generate the rankings. We used the predicted data started from May 5, the season's opening day, to August 30, 2020 to generate the rankings. In the games which Kia Tigers did not play, however, we used actual games' results in the data. KNN and AdaBoost selected the most optimized machine learning model. As a result, we observe a decreasing trend of the predicted results' ranking error as the season progresses. The deep learning model recorded 89% of the model accuracy. It provides the same result of decreasing ranking error trends of the predicted results that we observe in the machine learning model. We estimate that this study's result applies to future KBO predictions as well as other fields. We expect broadcasting enhancements by posting the predicted winning percentage per inning which is generated by AI algorism. We expect this will bring new interest to the KBO fans. Furthermore, the prediction generated at each inning would provide insights to teams so that they can analyze data and come up with successful strategies.

A Model of Natural Language Information Retrieval Using Main Keywords and Sub-keywords (주 키워드와 부 키워드를 이용한 자연언어 정보 검색 모델)

  • Kang, Hyun-Kyu;Park, Se-Young
    • The Transactions of the Korea Information Processing Society
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    • 제4권12호
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    • pp.3052-3062
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    • 1997
  • An Information Retrieval (IR) is to retrieve relevant information that satisfies user's information needs. However a major role of IR systems is not just the generation of sets of relevant documents, but to help determine which documents are most likely to be relevant to the given requirements. Various attempts have been made in the recent past to use syntactic analysis methods for the generation of complex construction that are essential for content identification in various automatic text analysis systems. Unfortunately, it is known that methods based on syntactic understanding alone are not sufficiently powerful to Produce complete analyses of arbitrary text samples. In this paper, we present a document ranking method based on two-level ranking. The first level is used to retrieve the documents, and the second level to reorder the retrieved documents. The main keywords used in the first level can be defined as nouns and/or compound nouns that possess good document discrimination powers. The sub-keywords used in the second level can be also defined as adjectives, adverbs, and/or verbs that are not main keywords, and function words. An empirical study was conducted from a Korean encyclopedia with 23,113 entries and 161 Korean natural language queries collected by end users. 850% of the natural language queries contained sub-keywords. The two-level document ranking methods provides significant improvement in retrieval effectiveness over traditional ranking methods.

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