• Title/Summary/Keyword: Knowledge propagation analysis

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A prediction of the rock mass rating of tunnelling area using artificial neural networks (인공신경망을 이용한 터널구간의 암반분류 예측)

  • Han, Myung-Sik;Yang, In-Jae;Kim, Kwang-Myung
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.4 no.4
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    • pp.277-286
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    • 2002
  • Most of the problems in dealing with the tunnel construction are the uncertainties and complexities of the stress conditions and rock strengths in ahead of the tunnel excavation. The limitations on the investigation technology, inaccessibility of borehole test in mountain area and public hatred also restrict our knowledge on the geologic conditions on the mountainous tunneling area. Nevertheless an extensive and superior geophysical exploration data is possibly acquired deep within the mountain area, with up to the tunnel locations in the case of alternative design or turn-key base projects. An appealing claim in the use of artificial neural networks (ANN) is that they give a more trustworthy results on our data based on identifying relevant input variables such as a little geotechnical information and biological learning principles. In this study, error back-propagation algorithm that is one of the teaching techniques of ANN is applied to presupposition on Rock Mass Ratings (RMR) for unknown tunnel area. In order to verify the applicability of this model, a 4km railway tunnel's field data are verified and used as input parameters for the prediction of RMR, with the learned pattern by error back propagation logics. ANN is one of basic methods in solving the geotechnical uncertainties and helpful in solving the problems with data consistency, but needs some modification on the technical problems and we hope our study to be developed in the future design work.

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Evaluating Applicability of SRTM DEM (Shuttle Radar Topography Mission Digital Elevation Model) in Hydrologic Analysis: A Case Study of Geum River and Daedong River Areas (수문인자추출에서의 SRTM DEM (Shuttle Radar Topography Mission Digital Elevation Model) 적용성 평가: 대동강 및 금강 지역 사례연구)

  • Her, Younggu;Yoo, Seung-Hwan
    • Journal of The Korean Society of Agricultural Engineers
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    • v.55 no.6
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    • pp.101-112
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    • 2013
  • Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) offers opportunities to make advances in many research areas including hydrology by providing near-global scale elevation measurements at a uniform resolution. Its wide coverage and complimentary online access especially benefits researchers requiring topographic information of hard-to-access areas. However, SRTM DEM also contains inherent errors, which are subject to propagation with its manipulation into analysis outputs. Sensitivity of hydrologic analysis to the errors has not been fully understood yet. This study investigated their impact on estimation of hydrologic derivatives such as slope, stream network, and watershed boundary using Monte Carlo simulation and spatial moving average techniques. Different amount of the errors and their spatial auto-correlation structure were considered in the study. Two sub-watersheds of Geum and Deadong River areas located in South and North Korea, respectively, were selected as the study areas. The results demonstrated that the spatial presentations of stream networks and watershed boundaries and their length and area estimations could be greatly affected by the SRTM DEM errors, in particular relatively flat areas. In the Deadong River area, artifacts of the SRTM DEM created sinks even after the filling process and then closed drainage basin and short stream lines, which are not the case in the reality. These findings provided an evidence that SRTM DEM alone may not enough to accurately figure out the hydrologic feature of a watershed, suggesting need of local knowledge and complementary data.

Bankruptcy Type Prediction Using A Hybrid Artificial Neural Networks Model (하이브리드 인공신경망 모형을 이용한 부도 유형 예측)

  • Jo, Nam-ok;Kim, Hyun-jung;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
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    • v.21 no.3
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    • pp.79-99
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    • 2015
  • The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

Nonlocal strain gradient 3D elasticity theory for anisotropic spherical nanoparticles

  • Karami, Behrouz;Janghorban, Maziar;Tounsi, Abdelouahed
    • Steel and Composite Structures
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    • v.27 no.2
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    • pp.201-216
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    • 2018
  • In this paper, three-dimensional (3D) elasticity theory in conjunction with nonlocal strain gradient theory (NSGT) is developed for mechanical analysis of anisotropic nanoparticles. The present model incorporates two scale coefficients to examine the mechanical characteristics much accurately. All the elastic constants are considered and assumed to be the functions of (r, ${\theta}$, ${\varphi}$), so all kind of anisotropic structures can be modeled. Moreover, all types of functionally graded spherical structures can be investigated. To justify our model, our results for the radial vibration of spherical nanoparticles are compared with experimental results available in the literature and great agreement is achieved. Next, several examples of the radial vibration and wave propagation in spherical nanoparticles including nonlocal strain gradient parameters are presented for more than 10 different anisotropic nanoparticles. From the best knowledge of authors, it is the first time that 3D elasticity theory and NSGT are used together with no approximation to derive the governing equations in the spherical coordinate. Moreover, up to now, the NSGT has not been used for spherical anisotropic nanoparticles. It is also the first time that all the 36 elastic constants as functions of (r, ${\theta}$, ${\varphi}$) are considered for anisotropic and functionally graded nanostructures including size effects. According to the lack of any common approximations in the displacement field or in elastic constant, present theory can be assumed as a benchmark for future works.

Sensitivity Analysis of Uncertainty Sources in Flood Inundation Mapping by using the First Order Approximation Method (FOA를 이용한 홍수범람도 구축에서 불확실성 요소의 민감도 분석)

  • Jung, Younghun;Park, Jeryang;Yeo, Kyu Dong;Lee, Seung Oh
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.6
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    • pp.2293-2302
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    • 2013
  • Flood inundation map has been used as a fundamental information in flood risk management. However, there are various sources of uncertainty in flood inundation mapping, which can be another risk in preventing damage from flood. Therefore, it is necessary to remove or reduce uncertainty sources to improve the accuracy of flood inundation maps. However, the entire removal of uncertainty source may be impossible and inefficient due to limitations of knowledge and finance. Sensitivity analysis of uncertainty sources allows an efficient flood risk management by considering various conditions in flood inundation mapping because an uncertainty source under different conditions may propagate in different ways. The objectives of this study are (1) to perform sensitivity analysis of uncertainty sources by different conditions on flood inundation map using the FOA method and (2) to find a major contributor to a propagated uncertainty in the flood inundation map in Flatrock at Columbus, U.S.A. Result of this study illustrates that an uncertainty in a variable is differently propagated to flood inundation map by combination with other uncertainty sources. Moreover, elevation error was found to be the most sensitive to uncertainty in the flood inundation map of the study reach.

Analysis of Research on Non-Timber Forest Plants - Based on the Articles Published in the Journal of Korean Forest Society from 1962 to 2013 - (산림과학분야의 산림특용자원식물의 연구 - 한국임학회지에 게재된 논문을 중심으로 -)

  • Lee, Hyunseok;Yi, Jaeseon;An, Chanhoon;Lee, Jeonghoon
    • Journal of Korean Society of Forest Science
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    • v.104 no.3
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    • pp.337-351
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    • 2015
  • The articles, published in the Journal of Korean Forest Society from Volume 1 (1962) to Volume 102 (2013), were investigated for the research trend analysis about forest plants for special purposes, i.e., edible plants, medicinal plants, feed resources, landscape plants, fiber plants, industrial usage, bee plants, bioenergy/phytoremediation uses, dye materials, and rare/endangered/endemic plants. These research articles were classified again based on the contents of research into following categories - habitat environment, ecology, physiology, propagation, silviculture (including planting and tending), genetics and breeding, identification, pest and disease control, animal-related research, components analysis and extracts, vegetation survey, biotechnology, management, recreation and forest healing, and research review. Among the total 2,433 articles published, 611 (25.1%) were related to plants for special usage or purposes. The highest frequency (14.9%) in publications was found in the field of silviculture followed by physiology, propagation, identification, and genetics and breeding, respectively. On the bases of usage, edible plants showed higher frequency (26.5%) than others, followed by industrial purpose, bioenergy/phytoremediation usage, landscape plants, medicinal plants, and rare/endangered/endemic plants. Populus plant species was the most popular in research, showing 62 articles; and Castanea crenata 36; Pinus koraiensis 35; Robinia pseudoacacia 20; Ginko biloba 17, etc. Based on the survey and analysis, the following points are suggested: 1) improved evaluation of forest plants as non-wood resources, 2) expanding research topics on the basis of production, management, and utilization of non-wood forest resources, 3) management of database of forest plant information and encouragement needed to strengthen cooperative researches satisfying the needs of other industrial and scientific areas, and 4) encouraging to promote traditional knowledge based research on forest plants.

Study on Vegetation Analysis for Indicators Development of Agro-ecosystem Habitat Quality (농업생태계의 서식지 질 지표 개발을 위한 식생분석)

  • Park, Kwang-Lai;Kang, Bang-Hun;Choi, Jae-Woong;Kim, Chang-Hwan
    • Korean Journal of Soil Science and Fertilizer
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    • v.43 no.6
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    • pp.1040-1046
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    • 2010
  • This research is composed of a series of survey of existing plants species by classifying biotope type of agro-ecosystem of Guksoo village area of Yangpyeong County, to collect and analyze basic data of vegetation analysis for indicators development of agro-ecosystem habitat quality. From the observation area, we found total 141 kinds of tracheophytes (53 Family 114 Genus 124 Species 16 Variety 1 Breed) and they are 3.36% of total Korean tracheophytes (4,191 kinds). Among those 141 tracheophytes, there are 23 kinds of naturalized plants (11 Family 20 Genus 20 Species 2 Variety) and they are 8.61% of total Korean naturalized plants (267 kinds). Among those 141 tracheophytes, they include 0.71% of pteridophyte, 0.71% of gymnosperm, 98.58% of angiosperm. So, most of them are angiosperm. When we classify them according to plant life form characteristics, dormant/diapause type plants include 45 species (31.91%) of annual plant (Th), 19 species (13.48%) of Th (w), 17species (12.06%) of hemicryptophyte (H). Regarding propagation type, as for the Radicoid form, there are 99 species (70.21%) of crumb structure plant, 13 species (9.22%) of $R_4$, 12 species (8.51%) of $R_{2.3}$ are the crumb structure does not make any connection on the ground or under ground. As for the Disseminule form of propagation type, there are 62 species (43.97%) of Gravity dispersal type $D_4$), 23 species (16.31%) of Wind dispersal type ($D_1$), 21 species (14.89%) of $D_{1.4}$. According to this survey of plant distribution rate by plant life form characteristics, we may acquire many knowledge about species composition of sociability, cluster's reaction against environmental elements, space usage and possible species competition in community. It may be very useful basic data for habitat preservation to keep and promote biological diversity.

Growth Characteristics of One-year-old Container Seedlings of Pinus densiflora by Irrigation Level (관수수준에 따른 소나무 용기묘 1년생의 생장 특성)

  • Cha, Young-Geun;Choi, Kyu-Seong;Song, Ki-Seon;Sung, Hwan-In;Kim, Jong-Jin
    • Journal of Bio-Environment Control
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    • v.26 no.3
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    • pp.167-174
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    • 2017
  • To identify the appropriate irrigation level for Pinus densiflora, a common reforestation species in Korea, we investigated their growth response characteristics according to different irrigation treatment levels for producing container seedlings with relatively high growth rate for higher survival rate when planted at the reforestation site. The container seedlings including control seedlings (no irrigation was applied) were grown in 104-cell trays were irrigated for 8 weeks from 15 weeks after seeding, at intervals of 1, 2, 3, 5, 7, 10, and 15 days. Analysis of the height growth, root collar diameter growth, and dry matter production of the container seedlings according to irrigation showed that the highest growth reaction was observed for the irrigation interval of 1 day. A shorter irrigation cycle resulted in better growth of the container seedlings, but overall, longer total root length were observed with an irrigation cycle of 3 days compared with cycles of 1 or 2 days. Quality index (QI) was the highest for the irrigation interval of 1 day, and tended to decrease with increase in the irrigation interval. Thus, it was determined that irrigation at intervals of 1-2 days was appropriate for growing Pinus densiflora container seedlings.

The hybrid of artificial neural networks and case-based reasoning for intelligent diagnosis system (인공 신경경망과 사례기반추론을 혼합한 지능형 진단 시스템)

  • Lee, Gil-Jae;Kim, Chang-Joo;Ahn, Byung-Ryul;Kim, Moon-Hyun
    • The KIPS Transactions:PartB
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    • v.15B no.1
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    • pp.45-52
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    • 2008
  • As the recent development of the IT services, there is a urgent need of effective diagnosis system to present appropriate solution for the complicated problems of breakdown control, a cause analysis of breakdown and others. So we propose an intelligent diagnosis system that integrates the case-based reasoning and the artificial neural network to improve the system performance and to achieve optimal diagnosis. The case-based reasoning is a reasoning method that resolves the problems presented in current time through the past cases (experience). And it enables to make efficient reasoning by means of less complicated knowledge acquisition process, especially in the domain where it is difficult to extract formal rules. However, reasoning by using the case-based reasoning alone in diagnosis problem domain causes a problem of suggesting multiple causes on a given symptom. Since the suggested multiple causes of given symptom has the same weight, the unnecessary causes are also examined as well. In order to resolve such problems, the back-propagation learning algorithm of the artificial neural network is used to train the pairs of the causes and associated symptoms and find out the cause with the highest weight for occurrence to make more clarified and reliable diagnosis.

A Symbolic Characteristic of Mimetic Words in Published Cartoon: Focusing on Works of Heo, Young Man (허영만의 작품에서 나타난 효과태의 상징어적 특징과 활용)

  • O, Yul Seok;Yoon, Ki Heon
    • Cartoon and Animation Studies
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    • s.30
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    • pp.169-199
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    • 2013
  • In various directions of cartoon, vertical stroll direction is opposite to the page direction of existing published cartoon with the popularity of webtoon and established new genre. Lots of studies on published cartoon focus on the cut direction by page, but webtoon doesn't have any concept of page. The pivot of cartoon oriented people is changed from paper to computer monitor as times go by, characteristics of media are changed and media is gradually diversified. Like the strengthening of mobile caused by smart phone's popularity, tablet PC's propagation in public education, etc. cartoon is included to the environment of media which is rapidly changed. In this situation, one of cartoon's unchanged important identities can be the direction made by harmony between picture and text. This thesis analyzed symbolic characteristics and effective value of hyogwatae, mimetic words of cartoon, focusing on works of Heo, Young Man. Hyogwatae just delivers not only sound but also shape, feeling, status, etc. and has significant characteristics by invoking the imaginary structure of literature. Strengths of modern Korean, various linguistic expressions and syllabic systems, let people feel minute feeling of language and difference of emotion and remember the memory through the direct and indirect experiences, so it makes it nuance. Because of the characteristics, representative works of Heo, Young Man have commercialization and writer characteristics, have communicated with people for a long time and have plentiful knowledge of Korean cartoon. The characteristics of hyogwatae in Heo, Young Man's cartoon make a lot of effects for the expression and delivery of cartoon more than the general expectation. When conducting the study focusing on the symbolic process of language, uncertainty and vague standard of judgement caused by the wide factors of study on the direction of general cartoon could be endured. And, through the Heo, Young Man's deep analysis on hyogwatae's direction, readers enjoy the process while inferring actually and intellectually between pictures and sentences. In the process, the equipment stimulating imagination more than pictures, effects and dialogues is hyogwatae. It's reader's equipment of active participation and its strength is symbolic structure.