• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.1
• /
• pp.73-80
• /
• 2018

In motorway traffic flow control, the conventional way based on real-time response has been changed into advanced way based on proactive response. Future traffic conditions over multiple time intervals are crucial input data for advanced motorway traffic flow control. It is necessary to overcome the uncertainty of the future state in order for forecasting multiple-period traffic volumes, as the number of uncertainty concurrently increase when the forecasting horizon expands. In this vein, multi-interval forecasting of traffic volumes requires a viable approach to conquer future uncertainties successfully. In this paper, a forecasting model is proposed which effectively addresses the uncertainties of future state based on the behaviors of temporal evolution of traffic volume states that intrinsically exits in the big past data. The model selects the past states from the big past data based on the state evolution of current traffic volumes, and then the selected past states are employed for estimating future states. The model was also designed to be suitable for data management systems in practice. Test results demonstrated that the model can effectively overcome the uncertainties over multiple time periods and can generate very reliable predictions in term of prediction accuracy. Hence, it is indicated that the model can be mounted and utilized on advanced data management systems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.31 no.4
• /
• pp.259-267
• /
• 2013

GIS-based web map service is all the more accessible to the public. Among others, location query services are most frequently utilized, which are currently restricted to only one keyword search. Although there increases the demand for the service for querying multiple keywords corresponding to sequential activities(banking, having lunch, watching movie, and other activities) in various locations POI, such service is yet to be provided. The objective of the paper is to develop the k-IPS algorithm for quickly and accurately querying multiple POIs that internet users input and locating the search outcomes on a web map. The algorithm is developed by utilizing hierarchical tree structure of $R^*$-tree indexing technique to produce overlapped geometric regions. By using recursive $R^*$-tree index based spatial join process, the performance of the current spatial join operation was improved. The performance of the algorithm is tested by applying 2, 3, and 4 multiple POIs for spatial query selected from 159 keyword set. About 90% of the test outcomes are produced within 0.1 second. The algorithm proposed in this paper is expected to be utilized for providing a variety of location-based query services, of which demand increases to conveniently support for citizens' daily activities.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.2
• /
• pp.3-9
• /
• 2015

Since changes in land use in urban space cause traffic volume and it is closely related to traffic accidents. Therefore, an analysis on the causes of traffic accidents is judged to be an essential factor to establish the measure to reduce traffic accidents. In this regard, the analysis was conducted on the clustering by using the nearest neighbor indexes with regard to the occurrence frequencies of commercial and residential zone based on traffic accident data of the past five years (2009-2013) with the target of local small-medium sized city, Jinju-si. The analysis results, obtained in this study, are as follows: the occurrence frequency of traffic accidents was the highest in spring and the lowest in winter respectively. The clustering of traffic accident occurrence at nighttime was stronger than at daytime. In addition, terms of the analysis on the clustering of traffic accident according to land use, changes according to the seasons was not significant in commercial areas, while clustering density in winter tended to become significantly lower in residential areas. The analysis results of traffic accident types showed that the side-right angle collision of cars was the highest in frequency occurrence, and widespread in both commercial areas and residential areas. These results can provide us with important information to identify the occurrence pattern of traffic accidents in the structure of urban space, and it is expected that they will be appropriately utilized to establish measures to reduce traffic accidents.

• Korean Journal of Construction Engineering and Management
• /
• v.11 no.4
• /
• pp.22-31
• /
• 2010

Because the estimated cost at early stage has great influence on decisions of project owner, the importance of early cost estimation is increasing. However, it depends on experience and knowledge of the estimator mainly due to shortage of information. Those tendency developed into case-based reasoning(CBR) method which solves new problems by adapting previous solution to similar past problems. The performance of CBR model is affected by attribute weight, so that its accurate determination is necessary. Previous research utilizes mathematical method or subjective judgement of estimator. In order to improve the problem of previous research, this suggests CBR schematic cost estimation method using genetic algorithm to determine attribute weight. The cost model employs nearest neighbor retrieval for selecting past case. And it estimates the cost of new cases based on cost information of extracted cases. As the result of validation for 17 testing cases, 3.57% of error rate is calculated. This rate is superior to accuracy rate proposed by AACE and the method to determine attribute weight using multiple regression analysis and feature counting. The CBR cost estimation method improve the accuracy by introducing genetic algorithm for attribute weight. Moreover, this makes user understand the problem-solving process easier than other artificial intelligence method, and find solution within short time through case retrieval algorithm.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.8
• /
• pp.535-542
• /
• 2013

Since case-based reasoning(CBR) has many advantages, it has been used for supporting decision making in various areas including medical checkup, production planning, customer classification, and so on. However, there are several factors to be set by heuristics when designing effective CBR systems. Among these factors, this study addresses the issue of selecting appropriate neighbors in case retrieval step. As the criterion for selecting appropriate neighbors, conventional studies have used the preset number of neighbors to combine(i.e. k of k-nearest neighbor), or the relative portion of the maximum similarity. However, this study proposes to use the absolute similarity threshold varying from 0 to 1, as the criterion for selecting appropriate neighbors to combine. In this case, too small similarity threshold value may make the model rarely produce the solution. To avoid this, we propose to adopt the coverage, which implies the ratio of the cases in which solutions are produced over the total number of the training cases, and to set it as the constraint when optimizing the similarity threshold. To validate the usefulness of the proposed model, we applied it to a real-world target marketing case of an online shopping mall in Korea. As a result, we found that the proposed model might significantly improve the performance of CBR.

• Proceedings of the Korean Vacuum Society Conference
• /
• 1999.07a
• /
• pp.190-190
• /
• 1999

박막 표면에 대한 경원소 분석법인 탄성 되튐 반도법을 개발하여 수소, 탄소, 질소등 분석에 이용하고 있다. 이때 입사 입자로 Cl 9.6MeV를 이용하였는데, 표적 표면에 탄소막이 흡착되는 현상을 발견하였다. cold trap 및 cold finger를 사용하여 진공도를 개선하므로서, 탄소막 흡착의 한 원인으로 알려져 잇는 chamber 주변의 진공도 변화를 시켜보았다. 하지만 전혀 탄소막이 생기지 않는 10-10torr 이하 진공을 만드는 것은 많은 비용과 장비를 필요로 하는 상당히 힘든 작업이어서, 이차적으로 탄소막이 표적 표면에 달라 붙게 하는 원인으로 추정되는 이차 전자의 발생을 고에너지 이온빔으로 조사하였다. 일반적으로 이차전자의 발생은 이온빔과 표적과의 충돌에 의한 고체 표면으로부터의 전자방출 현상으로 오래전부터 연구되어져 왔다. 여기에는 두가지 다른 구조가 존재하는 것으로 알려져 있다. 그 중 하나는 입사 입자의 전하와 표적 표면사이 작용하는 potential 에너지가 표적 표면의 일함수(재가 function) 보다 클 때에 일어나는 potential emission이다. 즉 표적 궤도에 존재하는 전자와 입사 이온빔 사이의 potential 이 표적의 전자를 들뜨게 만들고, 이 potential의 크기가표적의 표면 장벽 potential 보다 충분히 클 뜸 전자가 방출하는 현상을 말한다. 다른 또 하나의 방출구조로는 입사 이온이 표적 표면의 원자와의 충돌에 의해 직접저인 에너지 전달을 통한 전자 방출을 말하는데, 이를 kienetic emission(이하 KE)이라 한다. 본 연구에서는 Tandem Van de graaff 가속기로 고에너지 이온빔을 만들어 Au에 충돌시키므로서 kinetic emission을 통하여 Au에서 발생한는 이차전자의 방출 수율 및 에너지를 측정하였다.장구조로 전체 성장 양식을 예견할 수 있다. 일반적인 경향은 Ep가 커질수록 fractal 성장형태가 되며, Ed가 적을수록 cluster 밀도가 작아지나, 같은 Ed+Ep에 대해서는 동일한 크기의 팔 넓이(수평 수직 방향 cluster 두께)를 가진다. 따라서 실험으로부터 얻은 cluster의 팔 넓이로부터 Ed+Ep 값을 결정할 수 있고, cluster 밀도와 fractal 차원으로부터 각각 Ed와 Ep값을 분리하여 얻을 수 있다. 또한 다층 성장에 대한 거칠기(roughness) 값으로부터 Es값도 구할 수 있다. 양방향 대칭성을 갖지 않은 fcc(110) 표면과 같은 경우, 형태는 다양하지만 동일한 방법으로 추정이 가능하다. (110) 표면의 경우 nearest neighbor 원자가 한 축으로 형성되고 따라서 이 축과 이것과 수직인 축에 대한 상호작용이나 분산 장벽 모두가 비대칭적이다. 따라서 분산 장벽도 x-축, y-축 방향에 따라 분리하여 Edx, E요, Epx, Epy 등과 같이 방향에 따라 다르게 고려해야 한다. 이러한 비대칭적인 분산 장벽을 고려하여 KMC 시뮬레이션을 수행하면 수평축과 수직축의 분산 장벽의 비에 따라 cluster의 두께비가 달라지는 성장을 볼 수 있었고, 한 축 방향으로의 팔 넓이는 fcc(100) 표면의 경우 동일한 Ed+Ep값에 대응하는 팔 넓이와 거의 동일한 결과가 나타나는 것을 볼 수 있다. 따라서 이러한 비대칭적인 모양을 가지는 성장의 경우도 cluster 밀도, cluster 모양, cluster의 양 축 방향 길이 비, 양 축 방향의 평균 팔 넓이로부터 각 축 방향의 분산 장벽을 얻어낼 수 있을 것으로 보인다. 기대할 수 있는 여러 장점들을 보고하고자 한다.성이 우수한 시편일수록 grain의 크기가 큰 것으로 나타났고 결정성이 우수한 시편의 경우에서는 XR

• The KIPS Transactions:PartD
• /
• v.14D no.7
• /
• pp.707-718
• /
• 2007

Recently, much studies for providing mobile users with suitable and useful content services, LBS(Location Based Service) corresponding to the change of users' location, are actively going on. First and foremost, this is basically owing to the progress of location management technologies such as GPS, mobile communication technology and the spread of personal devices like PDA and the cellular phones. Besides, the research scope of LBS has been changed from vehicle tracking and navigation services to intelligent and personalized services considering the changing information of conditions or environment where the users' are located. For example, it inputs the information such as heavy traffic, pollution, and accidents. The query languages which effectively search the stored vehicle and environment information have been studied depending on the increase of the information utilization. However, most of existing moving object query languages are not enough to provide a recommendation service for a user, because they can not be tested and evaluated in real world and did not consider changed environment information. In order to retrieve not only a vehicle location and environment condition but also use them, we suggest a moving object query language for recommendation service and implement a moving object query process system for supporting a query language. It can process a nearest neighbor query for recommendation service which considers various attributes such as a vehicle's location and direction, environment information. It can be applied to location based service application which utilizes the recommended factors based on environmental conditions.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.10
• /
• pp.2615-2628
• /
• 1997

In this paper, a new codebook design algorithm is proposed. It uses a DCT map based on two-dimensional discrete cosine of transform (2D DCT) and finite state vector quantizer (FSVQ) when the vector quantizer is designed for image transmission. We make the map by dividing input image according to edge quantity, then by the map, the significant features of training image are extracted by using the 2D DCT. A master codebook of FSVQ is generated by partitioning the training set using binary tree based on tree-structure. The state codebook is constructed from the master codebook, and then the index of input image is searched at not master codebook but state codebook. And, because the coding of index is important part for high speed digital transmission, it converts fixed length codes to variable length codes in terms of entropy coding rule. The huffman coding assigns transmission codes to codes of codebook. This paper proposes single-side growing huffman tree to speed up huffman code generation process of huffman tree. Compared with the pairwise nearest neighbor (PNN) and classified VQ (CVQ) algorithm, about Einstein and Bridge image, the new algorithm shows better picture quality with 2.04 dB and 2.48 dB differences as to PNN, 1.75 dB and 0.99 dB differences as to CVQ respectively.

• The KIPS Transactions:PartB
• /
• v.9B no.5
• /
• pp.625-634
• /
• 2002

In this paper, we conducted various experiments with Bayesian networks in order to analyze clinical data of infertility patients. With these experiments, we tried to find out inter-dependencies among important factors playing the key role in clinical pregnancy, and to compare 3 different kinds of Bayesian network classifiers (including NBN, BAN, GBN) in terms of classification performance. As a result of experiments, we found the fact that the most important features playing the key role in clinical pregnancy (Clin) are indication (IND), stimulation, age of female partner (FA), number of ova (ICT), and use of Wallace (ETM), and then discovered inter-dependencies among these features. And we made sure that BAN and GBN, which are more general Bayesian network classifiers permitting inter-dependencies among features, show higher performance than NBN. By comparing Bayesian classifiers based on probabilistic representation and reasoning with other classifiers such as decision trees and k-nearest neighbor methods, we found that the former show higher performance than the latter due to inherent characteristics of clinical domain. finally, we suggested a feature reduction method in which all features except only some ones within Markov blanket of the class node are removed, and investigated by experiments whether such feature reduction can increase the performance of Bayesian classifiers.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.6
• /
• pp.706-714
• /
• 2012

The Korea Meteorological Administration provided the recent four-years records of weather dataset for our very short-term heavy rainfall prediction. We divided the dataset into three parts: train, validation and test set. Through feature selection, we select only important features among 72 features to avoid significant increase of solution space that arises when growing exponentially with the dimensionality. We used a differential evolution algorithm and two classifiers as the fitness function of evolutionary computation to select more accurate feature subset. One of the classifiers is Support Vector Machine (SVM) that shows high performance, and the other is k-Nearest Neighbor (k-NN) that is fast in general. The test results of SVM were more prominent than those of k-NN in our experiments. Also we processed the weather data using undersampling and normalization techniques. The test results of our differential evolution algorithm performed about five times better than those using all features and about 1.36 times better than those using a genetic algorithm, which is the best known. Running times when using a genetic algorithm were about twenty times longer than those when using a differential evolution algorithm.