• 제목/요약/키워드: Industrial Classification System

검색결과 569건 처리시간 0.026초

Modeling and Design of Intelligent Agent System

  • Kim, Dae-Su;Kim, Chang-Suk;Rim, Kee-Wook
    • International Journal of Control, Automation, and Systems
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    • 제1권2호
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    • pp.257-261
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    • 2003
  • In this study, we investigated the modeling and design of an Intelligent Agent System (IAS). To achieve this goal, we introduced several kinds of agents that exhibit intelligent features. These are the main agent, management agent, watcher agent, report agent and application agent. We applied the intelligent agent concept to two different application fields, i.e. the intelligent agent system for pattern classification and the intelligent agent system for bank asset management modeling.

Neural and MTS Algorithms for Feature Selection

  • Su, Chao-Ton;Li, Te-Sheng
    • International Journal of Quality Innovation
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    • 제3권2호
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    • pp.113-131
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    • 2002
  • The relationships among multi-dimensional data (such as medical examination data) with ambiguity and variation are difficult to explore. The traditional approach to building a data classification system requires the formulation of rules by which the input data can be analyzed. The formulation of such rules is very difficult with large sets of input data. This paper first describes two classification approaches using back-propagation (BP) neural network and Mahalanobis distance (MD) classifier, and then proposes two classification approaches for multi-dimensional feature selection. The first one proposed is a feature selection procedure from the trained back-propagation (BP) neural network. The basic idea of this procedure is to compare the multiplication weights between input and hidden layer and hidden and output layer. In order to simplify the structure, only the multiplication weights of large absolute values are used. The second approach is Mahalanobis-Taguchi system (MTS) originally suggested by Dr. Taguchi. The MTS performs Taguchi's fractional factorial design based on the Mahalanobis distance as a performance metric. We combine the automatic thresholding with MD: it can deal with a reduced model, which is the focus of this paper In this work, two case studies will be used as examples to compare and discuss the complete and reduced models employing BP neural network and MD classifier. The implementation results show that proposed approaches are effective and powerful for the classification.

도로 및 하천분야 BIM 속성분류체계 개발방안 연구 (A Study on the Development of BIM Property Classification System in Road and River Field)

  • 남정용;김민정
    • 한국산학기술학회논문지
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    • 제20권2호
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    • pp.773-784
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    • 2019
  • 최근 4차 산업혁명기술 발전이 부각되면서 이와 연계한 BIM정보기술로써 BIM 정보체계가 토목분야까지 확산되고 있는 추세이다. 국토교통부는 2020년부터 신속하고 광범위하게 BIM 정보체계를 건설 분야에 도입하려는 다각적인 기술정책을 발표하고 있다. 보통 SOC분야의 시설물은 형상이 정형화되지 않고, 복잡한 정보로 구성되어 있어 표준체계 없이 BIM 구현이 어렵다. 이런 문제점을 효과적으로 극복하기 위해서 BIM 표준분류체계의 개발이 시급하다. 본 연구에서는 국내외 유관 선행연구와 기존의 정보체계 및 실무기준 등을 조사 분석하여, 기 개발된 도로 및 하천분야 객체분류체계와 연계되도록 BIM 속성분류체계를 개발하였다. BIM 속성분류체계는 도로 및 하천분야의 단위시설, 시설물요소, 시설유형, 객체구성, 부품구성 등 객체 구성수준에 대응하는 사업, 시설, 시설부위 및 구성객체의 속성정보를 개발하였다. 또한 다양한 SOC 분야에 BIM 객체분류체계와 속성분류체계를 확장 적용하기 위한 방안과 시설별로 공간정보를 구성하는 방안도 제시하였다. 이 연구의 결과를 도로의 포장시설과 교량시설물에 시범 적용하여 효과적이고 체계적으로 시설물을 구성하고 정보를 구축하며 검색조회 가능여부를 검증하였다. 본 연구개발에 의한 객체분류체계와 속성분류체계에 의한 BIM 표준분류체계 개발로 향후 체계적이고 편리한 모델링과 정보체계의 구축여건이 마련되어 건설IT 발전에 기여할 것이다.

품질비용의 항목분류와 산출방법에 관한 연구 (A Study on the Classification of Ietms concerned Quality Cost and the Method of Calculation)

  • 강지호
    • 산업경영시스템학회지
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    • 제18권35호
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    • pp.17-24
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    • 1995
  • The classification of quality costs by item is essencial to sum up the entire quality cost but the reality of classifying the quality cost by the firm is facing with difficulty in terms of grouping the concerned items. Meanwhile, the classification of items and calculating method of quality costs should be prepared in adcance with a certain standards and or regulations to figure out the accurate quality costs successfuly. This case study provides the contents of quality costs calulated by item and the method of calculation in detail which is applicable to automobile component industry md, also introduce how to set up the computing system of quality costs.

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진동 아날로그 신호 기반의 이상상황 탐지를 위한 기계학습 모형의 성능지표 향상 (Improving the Performance of Machine Learning Models for Anomaly Detection based on Vibration Analog Signals)

  • 김재훈;엄상천;박철순
    • 산업경영시스템학회지
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    • 제47권2호
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    • pp.1-9
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    • 2024
  • New motor development requires high-speed load testing using dynamo equipment to calculate the efficiency of the motor. Abnormal noise and vibration may occur in the test equipment rotating at high speed due to misalignment of the connecting shaft or looseness of the fixation, which may lead to safety accidents. In this study, three single-axis vibration sensors for X, Y, and Z axes were attached on the surface of the test motor to measure the vibration value of vibration. Analog data collected from these sensors was used in classification models for anomaly detection. Since the classification accuracy was around only 93%, commonly used hyperparameter optimization techniques such as Grid search, Random search, and Bayesian Optimization were applied to increase accuracy. In addition, Response Surface Method based on Design of Experiment was also used for hyperparameter optimization. However, it was found that there were limits to improving accuracy with these methods. The reason is that the sampling data from an analog signal does not reflect the patterns hidden in the signal. Therefore, in order to find pattern information of the sampling data, we obtained descriptive statistics such as mean, variance, skewness, kurtosis, and percentiles of the analog data, and applied them to the classification models. Classification models using descriptive statistics showed excellent performance improvement. The developed model can be used as a monitoring system that detects abnormal conditions of the motor test.

Separation and Recovery of Rare Earth Elements from Phosphor Sludge of Waste Fluorescent Lamp by Pneumatic Classification and Sulfuric Acidic Leaching

  • Takahashi, Touru;Takano, Aketomi;Saitoh, Takayuki;Nagano, Nobuhiro;Hirai, Shinji;Shimakage, Kazuyoshi
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2001년도 The 6th International Symposium of East Asian Resources Recycling Technology
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    • pp.421-426
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    • 2001
  • The pneumatic classification and acidic leaching behaviors of phosphor sludge have been examined to establish the recycling system of rare earth components contained in waste fluorescent lamp. At first, separation characteristic of rare earth components and calcium phosphate in phosphor sludge was investigated by pneumatic classification. After pneumatic classification of phosphor sludge, rare earth components were leached in various acidic solutions and sodium hydroxide solution. For recovery of soluble component in leaching solution, rare earth components were separated as hydroxide and oxalate precipitations. The experimental results obtained are summarized as follows: (1) In classification process, rare earth components in phosphor sludge were concentrated to 29.3% from 13.3%, and its yield was 32.9%. (2) In leaching process, sulfuric acid solution was more effective one as a leaching solvent of rare earth component than other solutions. Y and Eu components in phosphor sludge were dissolved in sulfuric acid solution of 1.5 k㏖/㎥, and other rare earth components were rarely dissolved in leaching solution. Leaching degrees of Y and Eu were respectively 92% and 98% in the following optimum leaching conditions; sulfuric acid concentration is 1.5 k㏖/㎥ , leaching temperature 343 K, leaching time 3.6 ks and pulp concentration 30 kg/㎥. (3) Y and Eu components of phosphor sludge contained in waste fluorescent lamp were, effectively recovered by three processes of pneumatic classification, sulfuric acid leaching and oxalate precipitation methods. Their recovery was finally about 65 %, and its purity was 98.2%.

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목표 속성을 고려한 연관규칙과 분류 기법 (Directed Association Rules Mining and Classification)

  • 한경록;김재련
    • 산업경영시스템학회지
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    • 제24권63호
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    • pp.23-31
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    • 2001
  • Data mining can be either directed or undirected. One way of thinking about it is that we use undirected data mining to recognize relationship in the data and directed data mining to explain those relationships once they have been found. Several data mining techniques have received considerable research attention. In this paper, we propose an algorithm for discovering association rules as directed data mining and applying them to classification. In the first phase, we find frequent closed itemsets and association rules. After this phase, we construct the decision trees using discovered association rules. The algorithm can be applicable to customer relationship management.

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제조시스템의 유연성 정의 및 분류에 관한 연구 (Flexibility : Definition and Classification in Manufacturing Systems)

  • 이창섭;하정진
    • 산업경영시스템학회지
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    • 제14권24호
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    • pp.155-161
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    • 1991
  • Flexibility has become a key objectives in the design of manufacturing systems and a critical measure of total manufacturing performance. The need for flexibility is increasing due to some environmental change such as changing technical characteristics of the products and the changing nature of market demands. Most importantly, flexibility embodies competitive value for a manufacturer. Although the importance of flexibility has stressed in the various research, very few attempts have been made to synthesize the literature dealing with definitions and measure of flexibility. It is this issue that have motivated us to search for the definition and classification of flexibility.

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연역적이고 국부적인 영문자의 폰트 분류법 ($\emph{A Priori}$ and the Local Font Classification)

  • 정민철
    • 한국산학기술학회논문지
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    • 제3권4호
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    • pp.245-250
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    • 2002
  • 본 연구에서는 영문 단어로부터 폰트를 분류하기 위해 연역적이고 국부적인 폰트 분류 방법을 제안한다. 이는 문자 인식 전에 한 단어의 폰트를 분류하는 것을 말한다. 폰트 분류를 위해 활자 특성인 Ascender, Descender와 Serif가 사용된다. 입력 단어로부터 Ascender, Descender 와 Serif가 추출되어 경사도 특징 벡터가 추출되고, 그 특징 벡터는 인공 신경망에 의해 입력 단어에 대한 폰트 스타일, 폰트 그룹, 폰트 이름이 분류된다. 제안된 연역적이고 국부적인 폰트 분류 방법은 폰트 정보가 문자 분할기와 문자 인식기에 사용될 수 있게 한다. 나아가, 특정 폰트에 따른 Mono-Font 문자 분할기와 Mono-Font 문자 인식기로 구성되는 OCR 시스템을 구성할 수 있는 것을 가능하게 한다.

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