• Title/Summary/Keyword: Valid Model

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A Study on the Evaluation of an Expert System에s Performance : Lens Model Analysis (전문가시스템의 성능평가에 관한 연구 : 렌즈모델분석)

  • 김충영
    • Journal of Information Technology Applications and Management
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    • v.11 no.1
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    • pp.117-135
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    • 2004
  • Since human decision making behavior is likely to follow nonlinear strategy, it is conjectured that the human decision making behavior can be modeled better by nonlinear models than by linear models. All that linear models can do is to approximate rather than model the decision behavior. This study attempts to test this conjecture by analyzing human decision making behavior and combining the results of the analysis with predictive performance of both linear models and nonlinear models. In this way, this study can examine the relationship between the predictive performance of models and the existence of valid nonlinear strategy in decision making behavior. This study finds that the existence of nonlinear strategy in decision making behavior is highly correlated with the validity of the decision (or the human experts). The second finding concerns the significant correlations between the model performance and the existence of valid nonlinear strategy which is detected by Lens Model. The third finding is that as stronger the valid nonlinear strategy becomes, the better nonlinear models predict significantly than linear models. The results of this study bring an important concept, validity of nonlinear strategy, to modeling human experts. The inclusion of the concept indicates that the prior analysis of human judgement may lead to the selection of proper modeling algorithm. In addition, lens Model Analysis is proved to be useful in examining the valid nonlinearity in human decision behavior.

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Development of Machine Learning based Flood Depth and Location Prediction Model (머신러닝을 이용한 침수 깊이와 위치예측 모델 개발)

  • Ji-Wook Kang;Jong-Hyeok Park;Soo-Hee Han;Kyung-Jun Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.1
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    • pp.91-98
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    • 2023
  • With the increasing flood damage by frequently localized heavy rains, flood prediction research are being conducted to prevent flooding damage in advance. In this paper, we present a machine-learning scheme for developing a flooding depth and location prediction model using real-time rainfall data. This scheme proposes a dataset configuration method using the data as input, which can robustly configure various rainfall distribution patterns and train the model with less memory. These data are composed of two: valid total data and valid local. The one data that has a significant effect on flooding predicted the flooding location well but tended to have different values for predicting specific rainfall patterns. The other data that means the flood area partially affects flooding refers to valid local data. The valid local data was well learned for the fixed point method, but the flooding location was not accurately indicated for the arbitrary point method. Through this study, it is expected that a lot of damage can be prevented by predicting the depth and location of flooding in a real-time manner.

A Study on Temporal Data Models and Aggregate Functions (시간지원 데이터 모델 및 집계함수에 관한 연구)

  • Lee, In-Hong;Moon, Hong-Jin;Cho, Dong-Young;Lee, Wan-Kwon;Cho, Hyun-Joon
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.12
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    • pp.2947-2959
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    • 1997
  • Temporal data model is able to handle the time varying information, which is to add temporal attributes to conventional data model. The temporal data model is classified into three models depending upon supporting time dimension, that are the valid time model to support valid time, the transaction time model to support transaction model, and the bitemporal data model to support valid time and transaction time. Most temporal data models are designed to process the temporal data by extending the relational model. There are two types or temporal data model, which are the tuple timestamping and the attribute timestamping depending on time dimension. In this research, a concepts of temporal data model, the time dimension, types of thc data model, and a consideration for the data model design are discussed Also, temporal data models in terms of the time dimension are compared. And the aggregate function model of valid time model is proposed, and then logical analysis for its computing consts has been done.

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Extracting a Regular Triangular Net for Offsetting (옵셋팅을 위한 정규 삼각망 추출)

  • Jung W.H.;Jeong C.S.;Shin H.Y.;Choi B.K.
    • Korean Journal of Computational Design and Engineering
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    • v.9 no.3
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    • pp.203-211
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    • 2004
  • In this paper, we present a method of extracting a regular 2-manifold triangular net from a triangular net including degenerate and self-intersected triangles. This method can be applied to obtaining an offset model without degenerate and self-intersected triangles. Then this offset model can be used to generate CL curves and extract machining features for CAPP The robust and efficient algorithm to detect valid triangles by growing regions from an initial valid triangle is presented. The main advantage of the algorithm is that detection of valid triangles is performed only in valid regions and their adjacent selfintersections, and omitted in the rest regions (invalid regions). This advantage increases robustness of the algorithm. As well as a k-d tree bucketing method is used to detect self-intersections efficiently.

Nonlinear Models and Linear Models in Expert-Modeling A Lens Model Analysis (전문가 모델링에서 비선형모형과 선형모형 : 렌즈모형분석)

  • 김충녕
    • Journal of Intelligence and Information Systems
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    • v.1 no.2
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    • pp.1-16
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    • 1995
  • The field of human judgment and decision making provides useful methodologies for examining the human decision making process and substantive results. One of the methodologies is a lens model analysis which can examine valid nonlinearity in the human decision making process. Using the method, valid nonlinearity in human decision behavior can be successfully detected. Two linear(statistical) models of human experts and two nonlinear models of human experts are compared in terms of predictive accuracy (predictive validity). The results indicate that nonlinear models can capture factors(valid nonlinearity) that contribute to the expert's predictive accuracy, but not factors (inconsistency) that detract from their predictive accuracy. Then, it is argued that nonlinear models cab be more accurate than linear models, or as accurate as human experts, especially when human experts employ valid nonlinear strategies in decision making.

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A Timing Constraint Search Technique for a TMO based Real-time Process

  • Jeong, Yoon-Seok;Kim, Tae-Wan;Han, Sun-Young;Chang, Chun-Hyon
    • Journal of Information Processing Systems
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    • v.2 no.1
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    • pp.1-5
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    • 2006
  • Finding a valid timing constraint is one of the most important issues in the real-time monitoring area. To get the valid timing constraint, a developer executes a real-time process and changes the constraint on a regular basis. This is an exhaustive and time-consuming process. To improve this approach, we propose a timing constraint search technique. This technique uses two load models and one condition proposed in this paper to support the developer in determining the valid timing constraint range in an easy and systematic manner.

A Study on EOQ Model Involving Estimate Errors (수요, 주문 및 재고비용이 불확실한 상황에서의 EOQ모형에 관한 연구)

  • Kim, Gyu-Tae;Hwang, Hark-Chin;Kim, Chang-Hyun
    • IE interfaces
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    • v.17 no.1
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    • pp.78-83
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    • 2004
  • We consider the sensitivity of average inventory cost rate when true values of the parameters in the EOQ model are unknown over known ranges. In particular, in the case that the valid range on the true economic lot size are known, we provide a formula for estimating the lot size under minimax criterion. Moreover, to estimate the valid range, we apply the propagation of errors technique. Then, we present a scheme to find a (valid) lot size, based on the estimated range of the true lot size from the propagation of errors technique.

Analysis of EOQ Model Involving Estimate Errors (수요, 주문 및 재고비용이 불확실한 상황에서의 EOQ 모형분석)

  • Kim Gyutae;Hwang Hark-Chin;Kim Jong Rae
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2003.05a
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    • pp.1028-1034
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    • 2003
  • We consider the sensitivity of average inventory cost rate when true values of the parameters In the EOQ model are unknown over known ranges. In particular, In the case that the valid range on the true economic lot size are known. we provide a formula for estimating the lot size under minimax criterion. Moreover, to estimate the valid range, we apply the propagation of errors technique. Then, we present a scheme to find a (valid) lot size. based on the estimated range of the true lot size from the propagation or errors technique.

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Pencil Curve Computation for Clean-up Machining (잔삭 가공을 위한 펜슬커브 생성)

  • Park T.J.;Park S.C.
    • Korean Journal of Computational Design and Engineering
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    • v.11 no.1
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    • pp.20-26
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    • 2006
  • This paper presents a procedure to compute pencil curves from a triangular mesh which is offset with the radius of a given ball-end mill. An offset triangular mesh has numerous self-intersections caused by an abundance of invalid triangles, which do not contribute to the valid CL-surface. Conceptually, we can obtain valid pencil curves by combining all intersections tying on the outer skin of the offset triangular mesh, i.e., the valid CL-surface. The underlying concept of the proposed algorithm is that visible intersections are always valid for pencil curves, because visible intersections lie on the outer skin of the offset model. To obtain the visibility of intersections efficiently, the proposed algorithm uses a graphics board, which performs hidden surface removal on up to a million polygons per second.

A Methodology and Reliability for Selecting the Optimal Model among Ten Models of Crushing Machine with Various Constraints (다양한 제약조건을 갖는 열개의 파쇄장비 모델들 중 최적 모델 선정을 위한 방법과 신뢰성)

  • Leem Young Moon;Hwang Young Seob
    • Journal of the Korea Safety Management & Science
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    • v.7 no.1
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    • pp.159-166
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    • 2005
  • It is not difficult to see the road repairing. There are many and various machines which crush road surface. The efficiency and power of the machine depend on crushing head-shape, crushing interval, crushing load, crushing stress, machine's dropping height and roller's kind. The objective of this study is to select the optimal model among ten models of crushing machine with constraints such as crushing depth, variation, and crushed particle size. And then this paper provides the valid theoretical base on selected model. The data for this study are chosen from the site of construction in Kangnung during three months (2004. 6. 1${\~}$2004. 8. 31). The provided methodology in this paper will be fruitful not only for the selection of crushing machine but also for the aspects of construction period, cost, work efficacy according to the condition from the various sites of construction.