• Title/Summary/Keyword: Application Classification

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Classification of the Analytic Hierarchy Process Approaches by Application Circumstances

  • Yoon, Min-Suk;Kinoshita, Eizo
    • Management Science and Financial Engineering
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    • v.16 no.1
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    • pp.17-46
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    • 2010
  • This paper studies six different AHP (Analytic Hierarchy Process) approaches and suggests that the features of the approaches are classified by application circumstances in order to contribute to the applicability and quality usage of the AHP. Our study investigates the hierarchical principles and characteristics of the AHP, and historical debates on the AHP evaluation in which the six approaches have been involved. One of six approaches is an ANP (Analytic Network Process) application that is directly connected to AHP usage. The application differences among the six approaches are validated with a plain example. Then, the four circumstances of AHP applications are classified by two dimensions: the first dimension is whether or not the importance (weights) of criteria is independent of restrictively setting alternatives, and the second dimension is whether or not preference (priorities) of alternatives is independent of adding alternative(s) to or removing alternative(s) from the considering set of alternatives. Then featuring way of weighting criteria is classified. We suggest the distinguishing manners and describe the implications of the AHP application. Finally, we discuss rank reversal and multiplicative AHP.

Implementation of a Particle Swarm Optimization-based Classification Algorithm for Analyzing DNA Chip Data

  • Han, Xiaoyue;Lee, Min-Soo
    • Genomics & Informatics
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    • v.9 no.3
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    • pp.134-135
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    • 2011
  • DNA chips are used for experiments on genes and provide useful information that could be further analyzed. Using the data extracted from the DNA chips to find useful patterns or information has become a very important issue. In this paper, we explain the application developed for classifying DNA chip data using a classification method based on the Particle Swarm Optimization (PSO) algorithm. Considering that DNA chip data is extremely large and has a fuzzy characteristic, an algorithm that imitates the ecosystem such as the PSO algorithm is suitable to be used for analyzing such data. The application enables researchers to customize the PSO algorithm parameters and see detail results of the classification rules.

A Study on the Application of Combined Interpolation and Terrain Classification in Digital Terrain Model (수치지형모형에 있어 지형의 분석과 조합보관법의 적용에 관한 연구)

  • Yeu, Bock-Mo;Park, Woon-Yong;Kwon, Hyon;Mun, Du-Yeoul
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.8 no.2
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    • pp.53-61
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    • 1990
  • In this study, terrain classification was done by using the quantitative classification parameter and suitable interpolation method was applied to improve the accuracy of digital terrain models and to increase its practical applications. A study area was classified into three groups using the quantitative classification parameters and an interpolation equation suitable for each group was used for economical application of the interpolation method. The accuracy of digital terrain models was improved in case of large grid intervals by applying combined interpolation method suitable for each terrain group.

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A Geostatisitical Study Using Qualitative Information for Multiple Rock Classification II. Application (다분적 암반분류를 위한 정성적 자료의 지구통계학적 연구- II. 응용)

  • 유광호
    • Geotechnical Engineering
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    • v.14 no.1
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    • pp.29-36
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    • 1998
  • The application of a multiple rock classification method, which is a generalization of a binary rock classification, is studied in this paper. In particular, this paper shows how to incorporate qualitative data through a case study. The method suggested in this paper can be effectively used for a systematic multiple rock classification such as RMR system developed by Bieniawski. It will be very useful for rock classifications. In addition, it is known that the expected cost of errors can be atopted to indicate how well a investigation plan is made.

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Land cover classification using LiDAR intensity data and neural network

  • Minh, Nguyen Quang;Hien, La Phu
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.4
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    • pp.429-438
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    • 2011
  • LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3 D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data. In Vietnam, the LiDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.

An Analysis of the Application Framework of the Business Reference Model to Records Classification Schemes in Korean Central Government Agencies (기록분류를 위한 정부기능분류체계의 적용 구조 및 운용 분석 - 중앙행정기관을 중심으로 -)

  • Seol, Moon-Won
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.24 no.4
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    • pp.23-51
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    • 2013
  • The purpose of the study is to examine the potentialities and limits of Business Reference Model (BRM) as records classification schemes in Korean central state institutions. The analysis is based on the data collected through focus group interviews of three times, in which six records professionals from central government agencies participate. This paper begins with inquiring the framework of records classification based BRM, required by Public Records Management Act. It explores the types of benefit of BRM application to government records classification. Based on the collected data from the interviews, it investigates how records are aggregated, and how transaction level (Danwi-Gwaje) of BRM is applied in the course of records aggregation.

Design of Distributed Processing Framework Based on H-RTGL One-class Classifier for Big Data (빅데이터를 위한 H-RTGL 기반 단일 분류기 분산 처리 프레임워크 설계)

  • Kim, Do Gyun;Choi, Jin Young
    • Journal of Korean Society for Quality Management
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    • v.48 no.4
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    • pp.553-566
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    • 2020
  • Purpose: The purpose of this study was to design a framework for generating one-class classification algorithm based on Hyper-Rectangle(H-RTGL) in a distributed environment connected by network. Methods: At first, we devised one-class classifier based on H-RTGL which can be performed by distributed computing nodes considering model and data parallelism. Then, we also designed facilitating components for execution of distributed processing. In the end, we validate both effectiveness and efficiency of the classifier obtained from the proposed framework by a numerical experiment using data set obtained from UCI machine learning repository. Results: We designed distributed processing framework capable of one-class classification based on H-RTGL in distributed environment consisting of physically separated computing nodes. It includes components for implementation of model and data parallelism, which enables distributed generation of classifier. From a numerical experiment, we could observe that there was no significant change of classification performance assessed by statistical test and elapsed time was reduced due to application of distributed processing in dataset with considerable size. Conclusion: Based on such result, we can conclude that application of distributed processing for generating classifier can preserve classification performance and it can improve the efficiency of classification algorithms. In addition, we suggested an idea for future research directions of this paper as well as limitation of our work.

Comparative Analysis on Recommended Levels of Illumination in Korea·China·Japan: Focused on Recommended Levels of Illumination for Housing (한중일의 조도기준 비교분석 : 주택조도기준을 중심으로)

  • Song, DaeSun;Kang, HyeKyung;Jo, YoungMi;An, Okhee
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.28 no.4
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    • pp.1-8
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    • 2014
  • This study compared the recommended levels of illumination for housing. KS Recommended Levels of Illumination (KS A 3011) in Korea, Recommended Levels of Illumination (GB 50034-2004) in China and Recommended Levels of Illumination (JIS Z 9110) in Japan are compared. The results are as below. First, recommended levels of illumination used in Korea China Japan are suggested by different locations and activities. However, classification for application scope is set differently. There are 10 areas for classification used in Korea, 5 areas in China, and 13 areas in China. When medium levels for classification are included as classification level, total of 15 areas are used for classification in China. Second, when considering there are 15 areas of application scope in China for recommended levels of illumination, there are 7 areas that are commonly used in Korea China Japan. 7 areas include stadium, factories, hospitals, office, shopping center, houses and hospitals. Third, working surface is considered as the height for recommended levels of illumination in Korea China Japan. Korea and Japan consider all working positions, standing and sitting position, when deciding the height. However, China only considers the standing position. Fourth, application scope for recommended levels of illumination for housing are classified in 16 areas in Korea, 5 in China and 18 in Japan. Thus, the application scope for recommended levels of illumination in housing in Korea is similar to Japan. However, there are only 5 areas used in China such as living room, bedroom, dining room, kitchen and sanitary room. Fifth, recommended levels of illumination is classified in 3 levels such as Lowest-Moderate-Highest while China and Japan only have standard recommended levels of illumination. Sixth, when observing recommended levels of illumination by type of activities, Japan classified the activities in greatest detail followed by Korea and then China. Seventh, Recommended levels of illumination differs by each country.

Hybrid Learning Architectures for Advanced Data Mining:An Application to Binary Classification for Fraud Management (개선된 데이터마이닝을 위한 혼합 학습구조의 제시)

  • Kim, Steven H.;Shin, Sung-Woo
    • Journal of Information Technology Application
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    • v.1
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    • pp.173-211
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    • 1999
  • The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

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A Study on the Preliminary Classification System for the Development of the Application Model of Closed School Facilities - Focused on the Comparison of Public Design Indicators with Pre-research - (폐교시설의 활용모형 개발을 위한 예비 분류체계 도출 연구 - 선행연구와 공공 디자인지표의 비교를 중심으로 -)

  • Kim, Jae-young;Lee, Jong-kuk
    • Youth Facilities and Environment
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    • v.17 no.1
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    • pp.131-141
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    • 2019
  • The purpose of this study is to derive and type utilization indexes by comparing public design indicators with preceding studies related to closed school facilities, and to derive preliminary classification systems through a correlation review between indicators. Pre-research was conducted in the scope of academic papers, academic journals, research reports, and special act for promoting the utilization of closed school assets. Public design indicators were set in the scope of domestic design guidelines, the Seoul city public design assessment system, the 'Good Building' designation system, and the UK Design Quality Index (DQI). and the design review of the British architects. First of all, the research method looked at laws, procedures and utilization of closed schools, and reviewed the preceding study and domestic and international public design indicators sequentially. Next, the association was reviewed through a comparison between the preceding study and the public design indicators, and a preliminary classification system for the use of closed schools was derived from this.