• 품질경영학회지
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• 제51권3호
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• pp.363-379
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• 2023

Purpose: The main objective of this research is to construct an AI-based Composite Supplementary Index (ACSI) model to achieve accurate predictions of the Composite Index of Business Indicators. By incorporating various economic indicators as independent variables, the ACSI model enables the prediction and analysis of both the leading index (CLI) and coincident index (CCI). Methods: This study proposes an AI-based Composite Supplementary Index (ACSI) model that leverages diverse economic indicators as independent variables to forecast leading and coincident economic indicators. To evaluate the model's performance, advanced machine learning techniques including MLP, RNN, LSTM, and GRU were employed. Furthermore, the study explores the potential of employing deep learning models to train the weights associated with the independent variables that constitute the composite supplementary index. Results: The experimental results demonstrate the superior accuracy of the proposed composite supple- mentary index model in predicting leading and coincident economic indicators. Consequently, this model proves to be highly effective in forecasting economic cycles. Conclusion: In conclusion, the developed AI-based Composite Supplementary Index (ACSI) model successfully predicts the Composite Index of Business Indicators. Apart from its utility in management, economics, and investment domains, this model serves as a valuable indicator supporting policy-making and decision-making processes related to the economy.

• Asia pacific journal of information systems
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• 제11권4호
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• pp.99-111
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• 2001

The prediction of stock price index is a very difficult problem because of the complexity of stock market data. It has been studied by a number of researchers since they strongly affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network(BPN). Finally, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

• 디지털산업정보학회논문지
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• 제18권3호
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• pp.75-82
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• 2022

The purpose of the Consumer sentiment index survey is to determine the consumer's economic situation and consumption spending plan, and it is used as basic data for diagnosing economic phenomena and forecasting the future economic direction. The purpose of this paper is to analyze and predict the future Consumer sentiment index using the ARMA model based on the past consumer index. Consumer sentiment index is determined according to consumer trends, so it can reflect consumer realities. The consumer sentiment index is greatly influenced by economic indicators such as the base interest rate and consumer price index, as well as various external economic factors. If the consumer sentiment index, which fluctuates greatly due to consumer economic conditions, can be predicted, it will be useful information for households, businesses, and policy authorities. This study predicted the Consumer sentiment index for the next 3 years (36 months in total) by using time series analysis using the ARMA model. As a result of the analysis, it shows a characteristic of repeating an increase or a decrease every month according to the consumer trend. This study provides empirical results of prediction of Consumer sentiment index through statistical techniques, and has a contribution to raising the need for policy authorities to prepare flexible operating policies in line with economic trends.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 추계학술대회 논문집
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• pp.1657-1667
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• 2007

This study propose a model for railway safety evaluation with which the safety of whole railway system can be evaluated. The evaluation model is to generate a safety index which quantitatively represent the degree of railway safety. Safety index is proposed a function of three indexes; an accident index, safety management index, and safety culture index. This paper describes the first result from the study on the safety target which will be a key starting point toward the development of safety evaluation model. It is recommended that the safety target be composed of several sub-targets that are apportioned to constituent components. It is concluded that the classification of safety target influence on deciding components or attributes that constitute each sub-indexes; an accident index, safety management index, and safety culture index. Based on this study, a railway safety evaluation model will be developed in the next study.

• 정보화연구
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• 제10권2호
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• pp.237-249
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• 2013

그간 우리나라에서는 한국은행, 삼성경제연구소, 대한상의 등에서 기업가정신 측정모델을 발표한 바 있으나, 각 기관의 임의적인 측정모델 개발 및 단편적인 조사로 인해, 우리나라 기업가정신 측정 및 이해에 혼선이 초래되었다. 아울러, 기업가정신지수에 대한 국내외 비교연구의 부재로 글로벌 기업가정신지수 모델 수립이 현실적으로 어려웠다. 이에 본 연구에서는 무엇보다 기존 기업가정신 지수 관련 국내외 연구에 대한 선행연구분석과 이를 기초로 한 기업가정신 지수 모델, 즉, 기업가정신의 객관적 측정과 국제적 비교를 가능하게 하는 공통지표를 제시했다. 무엇보다 기존 연구 내용 및 장단점을 체계적으로 정리, 향후 기업가정신 지수의 방향성을 제안했다.

• 정보화정책
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• 제24권1호
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• pp.48-78
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• 2017

본 연구에서는 공공데이터 개방수준에 미치는 요인을 알아보는 것은 물론 사회자본의 조절효과와 매개효과를 알아보기 위해 총 26개국을 대상으로 공공데이터 개방지수인 ODB와 OUR Index에 대한 다중회귀분석 및 경로분석을 진행하였다. 다중회귀분석결과 종속변수 ODB를 기준으로 할 때 독립변수만을 투입한 모델 1에서는 전자정부, SW시장규모, 정부효과성이 유의미한 정적인 영향을 보였다. 독립변수, 조절변수를 투입한 모델 2에서는 전자정부, SW시장규모, 사회자본이 유의미한 정적인 영향을 보였다. 독립변수, 조절변수, 상호작용항이 투입된 모델 3에서는 전자정부, 사회자본이 유의미한 정적인 영향을 보였다. 종속변수 OUR Index를 기준으로 할 때 모델 1, 모델2에서 전자정부만이 유의미한 정적인 영향을 보였다. 독립변수, 조절변수, 상호작용항이 투입된 모델 3에서는 전자정부, SW시장규모${\times}$사회자본이 유의미한 정적인 영향을 보였다. 경로분석에서는 종속변수 ODB의 대안모형에 대해서 정부효과성만이 사회자본과 완전매개효과를 나타냈다.

• 한국안전학회지
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• 제27권4호
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• pp.108-114
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• 2012

Traffic Accident Merging Index(TAMI) is developed for TMACS(Traffic Safety Information Management Complex System). TAMI is calculated by combining 'Severity Index' and 'Frequency'. This paper suggest the accurate TAMI prediction model by time series forecasting. Preventing the traffic accident by accurately predicting it in advance can greatly improve road traffic safety. Searches the model which minimizes the error of 230 local self-governing groups. TAMI of 2007~2009 years data predicts TAMI of 2010. And TAMI of 2010 compares an actual index and a prediction index. And the error is minimized the constant where selects. Exponential Smoothing model was selected. And smoothing constant was decided with 0.59. TAMI Forecasting model provides traffic next year safety information of the local government.

• Communications for Statistical Applications and Methods
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• 제26권1호
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• pp.69-78
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• 2019

A structured model with both single-index and varying coefficients is a powerful tool in modeling high dimensional data. It has been widely used because the single-index can overcome the curse of dimensionality and varying coefficients can allow nonlinear interaction effects in the model. For high dimensional index vectors, variable selection becomes an important question in the model building process. In this paper, we propose an efficient estimation and a variable selection method based on a smoothing spline approach in a partially linear single-index-coefficient regression model. We also propose an efficient algorithm for simultaneously estimating the coefficient functions in a data-adaptive lower-dimensional approximation space and selecting significant variables in the index with the adaptive LASSO penalty. The empirical performance of the proposed method is illustrated with simulated and real data examples.

• 상하수도학회지
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• 제19권5호
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• pp.632-638
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• 2005

Membrane fouling index such as Silt Density Index (SDI) and Modified Fouling Index (MFI) is an important parameter in design of the integrated RO/NF membrane processes for drinking water treatment. In this study, the effect of particle, membrane and feed water characteristics on membrane fouling index were investigated systematically. Higher fouling index values were observed when filtering suspensions with smaller particle size and higher feed particle concentration. Larger membrane resistance due to smaller pore size resulted in an increased membrane fouling index. The variations of feed water hardness and TDS concentrations did not show any impact on fouling index, suggesting that there were no significant colloidal interactions among particles and thus the porosity of particle cake layer accumulated on the membrane surface could be assumed to be 0.36 according to random packing density. Based on the experimental observations, fundamental membrane fouling index model was developed using Happel Cell. The effect of primary model parameters including particle size ($a_p$), particle concentration ($C_o$), membrane resistance ($R_m$), were accurately assessed without any fitting parameters, and the prediction of membrane fouling index such as MFI exhibited very good agreement with the experimental results.

• 한국과학교육학회지
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• 제15권1호
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• pp.1-5
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• 1995

One of the problem of science education in terms of its status as a unique discipline is the tendency of qualitative, rather than quantitative, arguments and judgements on research activities. In this study, a model called "Diamond Model" and an index formula for the balance of researches are suggested for achieving more pictoricaI and quantitative understandings on the distribution of researches in science education. Diamond Model is consisted of two dimensions corresponding to two main long-debated issues in science education, i.e. the dimension of cognitive-affective and the dimension of concept-process. In Diamond Model the geometrical symmetry represents the the balance of researches. An index formula for the balance was developed in order to ensure that the value of the index is between 0 to 1 and the numerical values of the index corresponds to the geometrical symmetry of the diamond. Then, in order to check their utility, the model and the index formula were applied to analyze the research papers appeared in JKARSE for the last 10 years.