• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.35-48
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• 2023

In this study, we introduced the development status and the government policy of the Chinese automobile industry under the rapidly changing global economic environment. We conducted a consumer trend survey on automobile purchases by consumers in China. Despite the Chinese government's strong national emission control policy and stricter standards for manufacturing and selling internal combustion engine vehicles, 59.6% of respondents saying they would choose an internal combustion engine vehicle when purchasing a vehicle in the future for various reasons. It was confirmed that there is a significant gap between government policies and consumer perceptions. In addition, we have discovered the recent declining trend of automobile sales in China, and used the monthly sales volume from January 2010 to December 2020 as training set, and the sales volume from January 2021 to November 2022 as a test set. We proposed and evaluated a time-series model for predicting future automobile demand in China. Then, we showed the monthly sales forecast for 2023 when each model was applied.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.1-13
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• 2023

This study forecasted the manpower demand of eco-friendly smart shipbuilding, whose importance and weight are increasing according to the environmental regulations of the IMO and the spread of the 4th industrial revolution technology. It predicted the shipbuilding industry manpower by applying various models of trend analysis and time series analysis based on data from 2000 to 2020 of Statistics Korea. It was found that the prediction applying geometric mean had the smallest gap among the trend and time series analysis methods in comparing between forecast results and actual data for the past 5 years. Therefore, the demand for manpower in the shipbuilding industry was predicted by using the geometric mean method. In addition, the manpower demand of smart eco-friendly ships wast forecasted by using the 2018 and 2020 manpower survey results of the Ministry of Trade, Industry and Energy and reflecting the trend of manpower increase in the shipbuilding industry. The result of forecasting showed that 62,001 person in 2025 and 85,035 people in 2030. This study is expected to contribute to the adjustment of manpower supply and demand and the training professional manpower in the future by increasing the accuracy of forecasting for high value-added eco-friendly smart ships.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1959-1964
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• 2015

Purpose: To investigate the distribution of liver cancer mortality as well as its developing trend from 1991 to 2012, forecast the future five-year trend, and provide a basis for the comprehensive prevention and management. Materials and Methods: Mortality data for liver cancer in China from 1991 to 2012 were used to describe characteristics and distribution of liver cancer mortality. Trend surface analysis was used to study the geographical distribution of liver cancer mortality. Curve estimation, time series modeling, gray modeling (GM) and joinpoint regression were used to predict and forecast future trends. Results: The mortality rate of liver cancer has constantly increased in China since 1991. Rates in rural areas are higher than in urban areas, and in males are higher than in females. In addition, our data predicted that the trend will continue to increase in the next 5 years. The age-specific mortality of liver cancer increases with age and peaks in the group of 80-84 years old. Geographical analysis showed the liver mortality rate was higher in the southeast provinces, such as Jiangsu, Zhejiang and Guangdong, and southwest regions like Guangxi Province. Conclusions: The standardized mortality rate of liver cancer in China has consistently increased from 1991 to 2012, and the upward trend is predicted to continue in the future. Much better prevention and management of liver cancer is needed in high mortality areas (the southwestern and southeastern parts of China) and high mortality age groups (80- to 84-year-olds), especially in rural areas.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6391-6396
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• 2015

Background: To analyze cervical cancer mortality trends in China from 1991-2013 and forecast the mortality distribution in future five years (2014-2018), and provide clues for prevention and treatment. Materials and Methods: Mortality data for cervical cancer in China from 1991 to 2013 were used to describe the epidemiological characteristics and distribution, including the trend of the standardized mortality rate, urban-rural differences, and age variation. Trend-surface analysis was used to analyze the geographical distribution of mortality. Curve estimation, time series, gray modeling, and joinpoint regression were performed to predict and forecast mortality trends. Results: In recent years, the mortality rate of cervical cancer has increased, and there is also a steady increase in the incidence from 2003 to 2013 in China. Mortality rates in rural areas are higher than in urban areas. The mortality dramatically increases in the 40+ yr age group, reaching a peak in the >85 yr age group. In addition, geographical analysis showed that the cervical cancer mortality increased from the southwest to west-central and from the southeast to northeast of the country. Conclusions: The incidence rate and the mortality rate are increasing from 1991 to 2013, and the predictions show this will continue in the future. Thus, implementation of prevention and management programs for cervical cancer are necessary in China, especially for rural areas, young women in urban areas, and high risk regions (the west-central).

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5829-5834
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• 2015

Objective: To describe and analyze the epidemiological characteristics of lung cancer mortality in China from 1991 to 2013, forecast the future five-year trend and provide scientific evidence for prevention and management of lung cancer. Materials and Methods: Mortality data for lung cancer in China from 1991 to 2013 were used to describe epidemiological characteristics. Trend surface analysis was applied to analyze the geographical distribution of lung cancer. Four models, curve estimation, time series modeling, gray modeling (GM) and joinpoint regression, were performed to forecast the trend for the future. Results: Since 1991 the mortality rate of lung cancer increased yearly. The rate for males was higher than that for females and rates in urban areas were higher than in rural areas. In addition, our results showed that the trend will continue to increase in the ensuing 5 years. The mortality rate increased from age 45-50 and peaked in the group of 85 years old. Geographical analysis indicated that people living in northeast China provinces and the coastal provinces in eastern China had a higher mortality rate for lung cancer than those living in the centre or western Chinese provinces. Conclusions: The standardized mortality rate of lung cancer has constantly increased from 1991 to 2013, and been predicted to continue in the ensuing 5 years. Further efforts should be concentrated on education of the general public to increase prevention and early detection. Much better prevention and management is needed in high mortality areas (northeastern and eastern parts of China) and high risk populations (45-50-year-olds).

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.2
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• pp.122-130
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• 2014

Seasonal variations and long term linear trends of SST (Sea Surface Temperature) at Yeosu Coast ($127^{\circ}37.73^{\prime}E$, $34^{\circ}37.60^{\prime}N$) in Korea were studied performing the harmonic analysis and the regression analysis of the monthly mean SST data of 46 years (1965-2010) collected by the Fisheries Research and Development Institute in Korea. The mean SST and the amplitude of annual SST variation show $15.6^{\circ}C$ and $9.0^{\circ}C$ respectively. The phase of annual SST variation is $236^{\circ}$. The maximum SST at Yeosu Coast occurs around August 26. Climatic changes in annual mean SST have had significant increasing tendency with increase rate $0.0305^{\circ}C/Year$. The warming trend in recent 30 years (1981-2010) is more pronounced than that in the last 30 years (1966-1995) and the increasing tendency of winter SST dominates that of the annual SST. The time series model that could be used to forecast the SST on a monthly basis was developed applying Box-Jenkins methodology. $ARIMA(1,0,0)(2,1,0)_{12}$ was suggested for forecasting the monthly mean SST at Yeosu Coast in Korea. Mean absolute percentage error to measure the accuracy of forecasted values was 8.3%.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.139-149
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• 2013

As the importance of technology forecasting while countries and companies manage the R&D project is growing bigger, the methodology of technology forecasting has been diversified. One of the forecasting method is patent analysis. This research proposes quick forecasting process of emerging technology based on keyword approach using text mining. The forecasting process is following: First, the term-document matrix is extracted from patent documents by using text mining. Second, emerging technology keyword are extracted by analyzing the importance of word from utilizing mean values and standard deviation values of the term and the emerging trend of word discovered from time series information of the term. Next, association between terms is measured by using cosine similarity. finally, the keyword of emerging technology is selected in consequence of the synthesized result and we forecast the emerging technology according to the results. The technology forecasting process described in this paper can be applied to developing computerized technology forecasting system integrated with various results of other patent analysis for decision maker of company and country.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.10
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• pp.126-133
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• 2007

This paper proposes information technology based data mining to forecast short term power demand. A time-series analyses have been applied to power demand forecasting, but this method needs not only heavy computational calculation but also large amount of coefficient data. Therefore, it is hard to analyze data in fast way. To overcome time consuming process, the author take advantage of universally easily available information technology based data-mining technique to analyze patterns of days and special days(holidays, etc.). This technique consists of two steps, one is constructing decision tree, the other is estimating and forecasting power flow using decision tree analysis. To validate the efficiency, the author compares the estimated demand with real demand from the Korea Power Exchange.

• Korea Real Estate Review
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• v.27 no.3
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• pp.41-50
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• 2017

Previous studies, especially that by Lee (2014), showed how time series volatility models can be applied to the house price series. As the regional housing market trends, however, have shown significant differences of late, analysis with national data may have limited practical implications. This study applied volatility models in analyzing and forecasting regional house prices. The estimation of the AR(1)-ARCH(1), AR(1)-GARCH(1,1), and AR(1)-EGARCH(1,1,1) models confirmed the ARCH and/or GARCH effects in the regional house price series. The RMSEs of out-of-sample forecasts were then compared to identify the best-fitting model for each region. The monthly rates of house price changes in the second half of 2017 were then presented as an example of how the results of this study can be applied in practice.

• Fire Science and Engineering
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• v.30 no.6
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• pp.92-98
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• 2016

This study evaluated thermal image real-time estimation and fire alarm using by a CCD camera, which has been a seamless feature-point analysis method, according to the angle and position and image fusion by a vector coordinate point set-up of equal shape. The system has higher accuracy, fixing data value of temperature sensing and fire image of 0~255, and sensor output-value of 0~5,000. The operation time of a flame specimen within 500 m, 1000 m, and 1500 m from the test report specimen took 7 s, 26 s, and 62 s, respectively, and image creation was proven. A diagnosis of fire accident was designated to 3 steps: Caution/Alarm/Fire. Therefore, a series of process and the transmission of SNS were identified. A light bulb and fluorescent bulb were also tested for a false alarm test, but no false alarm occurred. The possibility that an unwanted alarm will be reduced was verified through a forecast of the fire progress or real-time estimation of a thermal image by the change in the image of a time-based flame and an analysis of the diffusion velocity.