• Proceedings of the Korean Environmental Sciences Society Conference
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• 2006.05a
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• pp.380-381
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• 2006

정보과학기술의 발달 등으로 미래도시는 많은 변화가 예상되며, 이로 인한 여러 가지 부정적인 영향도 예측되고 있어 개인적이고 비인간적인 사회출현도 우려된다. 그러나 지금까지의 도시발달과 흐름을 살펴볼 때 급격한 사회변화에 대한 역기능에 대해 방어수단을 마련하고자 근린체계가 잘 조성된 쾌적하고, 안전하며, 그리고 무엇보다도 좀 더 인간적인 모습을 갖추기 위한 다양한 노력이 시도될 것이다. 향후 미래도시에서는 보다 인간적이고 커뮤니티가 활성화된 도시를 구축하기 위해 공원녹지도 중요 수단의 하나가 될 것으로 보인다. 미래도시 유형의 하나인 V-CITY의 발전방향을 예측하고 살펴봄으로써 공원녹지의 바람직한 발전방향을 마련해야 할 것이다.

• Broadcasting and Media Magazine
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• v.4 no.3
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• pp.9-18
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• 1999

최근 급격한 유무선 통신기술의 발달로 인한 미디어 산업의 환경변화에 따른 국내외 현상을 바탕으로, 가능한 객관성 있는 정성적, 정량적 데이터에 근거를 두고 미래의 변화를 예측하고자 함이 본문의 취지이다. 본문에서 기술한 내용에서는 국가, 사회의 다양한 문화 및 제도 변화에 따른 영향 변수는 고려하지 않았다. 순수하게 경제적, 기술적인 환경 변화에 의한 미래의 변화를 예측 해보는데 중점을 두었다. 미디어 산업의 미래는 방송, 통신, 인터넷 각 분야가 독립적으로 존재하면서 상호작용을 통해 각각의 형태를 변화시키게 된다는 것이다.

• 전기의세계
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• v.40 no.5
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• pp.18-26
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• 1991

전력수요예측의 기본목적은 미래에 예상되는 전력수요를 정확히 예측함으로써 이를 충족시킬 수 있는 전원 및 계통설비의 적기 확보와 아울러, 보다 저렴한 비용으로 전력을 공급할 수 있게 하는데 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.765-773
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• 2009

Currently Telematics traffic information services have been various because we can collect real-time traffic information through Intelligent Transport System. In this paper, we proposed and implemented a short-term traffic information prediction model for giving to guarantee the traffic information with high quality in the near future. A Short-term prediction model is for forecasting traffic flows of each segment in the near future. Our prediction model gives an average speed on the each segment from 5 minutes later to 60 minutes later. We designed a Bayesian network for each segment with some casual nodes which makes an impact to the road situation in the future and found out its joint probability density function on the supposition of GMM(Gaussian Mixture Model) using EM(Expectation Maximization) algorithm with training real-time traffic data. To validate the precision of our prediction model we had conducted various experiments with real-time traffic data and computed RMSE(Root Mean Square Error) between a real speed and its prediction speed. As the result, our model gave 4.5, 4.8, 5.2 as an average value of RMSE about 10, 30, 60 minutes later, respectively.

• Journal of Technology Innovation
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• v.18 no.1
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• pp.53-74
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• 2010

The creation and acceptance of new technologies has been speeding up dramatically in modern times. There are also significant uncertainties about the future shape of markets, governance and social values that will have an important impact on organizations and their capacity to meet their objectives. These rapid technological and social change and uncertainties make the upsurge of interest in technology foresight, giving rise to its emergence as a global concept and policy tool. A wide range of future methods are available for technology foresight. Selection of methods will depend upon several factors, most notably available and the time financial resources, and the objectives of the exercise. Although Delphi has been widely used for many years, scenario becomes very popular in recent years. The use of scenarios can take better account of the complexity and unpredictability of the economic, social and political environments. Scenarios tell the stories describing paths to different futures, which help organizations make better decisions today. In this study, the scenario method was employed to draw the images of the future of renewable energy. Renewable energy grows dramatically in recent years. However, there is still considerable uncertainty with regard to the potential of renewable energy due to environment regulation, energy costs, and political and economic developments in the main supplier countries for oil and natural gas. Scenario can help us to identify the risks and opportunities when we develop the renewable energy, and to prepare for them. The scenario method is expected to be more utilized in the national technology foresight.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.303-303
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• 2011

효율적인 수자원 관리를 위해서는 미래 수문자료의 예측치에 대한 구간을 추정하여 미래에 관측될 자료에 대한 정보를 얻는 문제는 어렵지만 중요한 부분에 해당한다. 특히 중장기 유량예측은 입력변수의 불확실성이 크므로 확률론적 방법을 적용한 예측이 유리하다. 본 연구에서는 SSARR 모형을 이용하여 현재 유역의 상태에 과거에 재현되었던 강우를 결합한 앙상블 유출시나리오를 생성하였다. 그리고 대청댐 월 유입량에 대한 확률론적 예측방안을 제시하기위하여 과거 시나리오의 관측 ESP(Ensemble Streamflow Prediction)확률 및 Croley방법, PDF-Ratio방법을 한국의 기상예측정보 실정에 맞는 가중치 부여방안으로 적용하여 분석하였다. 2010년도 상반기를 기준으로 각 분석 기법별 정확성을 검증한 결과 Croley, PDF-Ratio 등 기상전망을 가중치로 부여한 확률론적 예측기법의 효용성을 확인하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.192-192
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• 2020

취약성 분석의 결과로 폭설에 의한 기후노출은 현재에는 강원권이 가장 취약한 것으로 나타났다. 그러나 미래에는 강원권, 충청권, 호남권을 연결하는 축으로 취약지역이 확대될 것으로 전망된다. 본 연구에서는 다양한 머신러닝 기법을 이용하여 대설피해 예측을 실시하였다. 머신러닝 기법으로는 로지스틱회귀모형, 서포트벡터 머신, 의사결정트리 모형을 적용하였다. 종속변수로 대설피해액 자료를 이용하였고, 독립변수로 기상관측자료, 사회·경제적 요소를 사용하였다. 결과적으로 기존에 사용했던 다중회귀모형과 머신러닝 기법으로 예측한 예측력을 비교 및 분석하였고, 예측력이 가장 높은 머신러닝 기법을 제시하였다. 본 연구에서 대설피해 예측을 위해 사용된 예측력이 가장 높은 기법을 활용하여 대설피해를 예측한다면, 미래에 전국적으로 확대될 대설피해에 대해 효과적으로 대비할 수 있을 것으로 기대된다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.147-156
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• 2013

Each field of modern society, industrialization and the development of science and technology are rapidly changing. However, as a side effect of rapid social change has caused various problems. Crime of the side effects of rapid social change is a big problem. In this paper, a model for predicting crime and Markov chains applied to the crime, predictive modeling is proposed. Markov chain modeling of the existing one with the overall status of the case determined the probability of predicting the future, but this paper predict the events to increase the probability of occurrence probability of the prediction and the recent state of the entire state was divided by the probability of the prediction. And the whole state and the probability of the prediction and the recent state by applying the average of the prediction probability and the probability of the prediction model were implemented. Data was applied to the incidence of crime. As a result, the entire state applies only when the probability of the prediction than the entire state and the last state is calculated by dividing the probability value. And that means when applied to predict the probability, close to the crime was concluded that prediction.

• Journal of Korea Spatial Information System Society
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• v.8 no.1 s.16
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• pp.17-25
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• 2006

TPR*-tree is the most widely-used index structure for effectively predicting the future positions of moving objects. The TPR*-tree, however, has the problem that both of the dead space in a bounding region and the overlap among hounding legions become larger as the prediction time in the future gets farther. This makes more nodes within the TPR*-tree accessed in query processing time, which incurs the performance degradation. In this paper, we examine the performance problem quantitatively with a series of experiments. First, we show how the performance deteriorates as a prediction time gets farther, and also show how the updates of positions of moving objects alleviates this problem. Our contribution would help provide Important clues to devise strategies improving the performance of TPR*-trees further.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.233-241
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• 2014

In this paper, it predicts green technology in the future with "Co-word" which is patent analysis, "technology road-map, life cycle graph of patent activation and trend analysis. Analysis result shows that it would help environment preservation because development of ITS green technology makes carbon emission effectiveness and ITS green technology is especially expected to develop in fuel saving field. In addition, fuel saving field is predicted to be advance more practically technology field with convergence with IT.