• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.78-88
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• 2012

AVIs on the road are installed for (1) security (2) and for traffic, and they are various managed by (1) police department, (2) local government, (3) national highway management, (4) Korean highway corporation. But although the collected data of the plate number, the travel time, the picture of the car are same, they are used in purposes of its installation because the managements are different and the data are difficult to be connected with each other. For this reason, this study is to appraise the application for creating traffic information by integrating these data, and to suggest the introduction of spatial detection system which integrated security-traffic AVI DB for the purpose of reliability improvement of center's velocity. The estimating sections of link travel information seems to be expanded, and the error rate between the center's velocity and the experimental value will be reduced if integrated DB of traffic and security AVIs is used for creating traffic information. Also, the crime prevention and arrest rate is expected to rise in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.665-670
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• 2014

A SVM is a kind of binary classifier in order to find optimal hyperplane which separates training data into two groups. Due to its remarkable performance, the SVM is applied in various fields such as inductive inference, binary classification or making predictions. Also it is a representative black box model; there are plenty of actively discussed researches about analyzing trained SVM classifier. This paper conducts a study on a method that is automatically detecting the line-shaped echoes, sun strobe echo and radial interference echo, using the SVM algorithm because the line-shaped echoes appear relatively often and disturb weather forecasting process. Using a spatial clustering method and corrected reflectivity data in the weather radar, the training data is made up with mean reflectivity, size, appearance, centroid altitude and so forth. With actual occurrence cases of the line-shaped echoes, the trained SVM classifier is verified, and analyzed its characteristics using the decision tree method.

• Geophysics and Geophysical Exploration
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• v.7 no.2
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• pp.109-116
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• 2004

Petroleum reservoir characterization is a process for quantitatively describing various reservoir properties in spatial variability using all the available field data. Porosity and permeability are the two fundamental reservoir properties which relate to the amount of fluid contained in a reservoir and its ability to flow. These properties have a significant impact on petroleum fields operations and reservoir management. In un-cored intervals and well of heterogeneous formation, porosity and permeability estimation from conventional well logs has a difficult and complex problem to solve by conventional statistical methods. This paper suggests an intelligent technique using fuzzy logic and neural network to determine reservoir properties from well logs. Fuzzy curve analysis based on fuzzy logics is used for selecting the best related well logs with core porosity and permeability data. Neural network is used as a nonlinear regression method to develop transformation between the selected well logs and core analysis data. The intelligent technique is demonstrated with an application to the well data in offshore Korea. The results show that this technique can make more accurate and reliable properties estimation compared with previously used methods. The intelligent technique can be utilized a powerful tool for reservoir characterization from well logs in oil and natural gas development projects.

• Spatial Information Research
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• v.18 no.5
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• pp.83-92
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• 2010

Recently, as the Geospatial Web is combined with the Semantic Web in order to keep pace with the recent trends of information technology emphasizing interoperability, intelligence and individualization, the Geo Semantic Web was proposed, which is an intelligent geographical information Web service technology that can provide users with suitable information by connecting and integrating various types of spatial information and extensive aspatial information on the Web efficiently. For the Geo Semantic Web service, we need to develop Geo Ontology processing technologies that enable computers to process knowledge and information scattered around in the Web environment automatically. However, standards for Geo Ontology processing technologies have nod been established yet, and standardization organizations and various groups and agencies are conducting relevant studies. This paper analyzed various base theories and technologies related to Geo Ontology and developed a Geo Semantic Web system. The Geo Semantic Web system comprises Query Processing Manager that analyzes and processes Geo Semantic queries and manages sessions, Ontology Manager that generates and queries Geo Ontology and extracts spatial/aspatial data, and Clients. Finally, this paper proved the utility of the Geo Semantic Web system by applying it to a hypothetical scenario where Geo Semantic queries are required.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.38-47
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• 2014

Ministry of Land, Infrastructure and Transport (MOLIT) Affairs of Korean government improved RSMS to be linked with GIS data and now we have research foundation. In case of expressway and rural national highway, there is a referenced place-name for direction road sign, but there is no reference in urban road and is only a guideline. Direction signs in urban could not have consistent place-name and it is vary difficult to select the proper place-name. Based on the change of analysis environment and perception of road sign - related problem, This study is aimed to suggest how to deduce the spatial impact zone of place-name from DB and GIS in RSMS of Changwon City. The results indicated that there is a spatial difference between place-names according to whether is near or far on the road sign. It is expected that this method would be effectively used in case of new road sign and so the process to select the place-name would be simple.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.165-172
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• 2010

In clinical data minig, choosing the optimal subset of features is such important, not only to reduce the computational complexity but also to improve the usefulness of the model constructed from the given data. Moreover the threshold values (i.e., cut-off points) of selected features are used in a clinical decision criteria of experts for differential diagnosis of diseases. In this paper, we propose a fuzzy discretization approach, which is evaluated by measuring the degree of separation of redundant attribute values in overlapping region, based on spatial distribution of data with continuous attributes. The weighted average of the redundant attribute values is then used to determine the threshold value for each feature and rough set theory is utilized to select a subset of relevant features from the overall features. To verify the validity of the proposed method, we compared experimental results, which applied to classification problem using 668 patients with a chief complaint of dyspnea, based on three discretization methods (i.e., equal-width, equal-frequency, and entropy-based) and proposed discretization method. From the experimental results, we confirm that the discretization methods with fuzzy partition give better results in two evaluation measures, average classification accuracy and G-mean, than those with hard partition.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.415-422
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• 2013

The contents development for the Internet and cyber tour has been attempted in a number of areas. 3D topography of the spatial environment, land planning and land information contents as a 3D tour of the future ubiquitous city safe for tourism due to the implementation of information made available major area. Domestic service, and in urban areas of the country where land and precise spatial information in order to shoot satellites and aircraft in the area you want to mount the camera on a variety of photo images taken by conducting 3D spatial that is required is able to obtain the information. Geo spatial information in a variety of direct or indirect acquisition of the initial spatial data into a database for accurate collection, storage, editing, manipulation and application technology changes in the future by establishing a database of 3D spatial by securing content organization ubiquitous tourist to take advantage of new tourism industry was greatly. As a result of this study for future tourism using geo spatial information and analysis of 3D modeling by intelligent land information indirectly, with quite a few stereo site experience and a variety of tourist spatial acquisition and utilization of information could prove.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.49-63
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• 2019

Crowdedness management at subway platforms is essential to improve services, including the prevention of train delays and ensuring passenger safety. Establishing effective crowdedness mitigation measures for platforms requires accurate estimation of the congestion level. There are temporal and spatial constraints since crowdedness on subway platforms is assessed at certain locations every 1-2 years by hand counting. However, smart cards generate real-time big data 24 hours a day and could be used in estimating congestion. This study proposes a model based on data from transit cards to estimate crowdedness dynamically. Crowdedness was defined as demand, which can be translated into passengers dynamically moving along a subway network. The trajectory of an individual passenger can be identified through this model. Passenger flow that concentrates or disperses at a platform is also calculated every minute. Lastly, the platform congestion level is estimated based on effective waiting areas for each platform structure.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.15-26
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• 1999

A horticultural field database system is constructed for the intelligent farm management using GIS. The database system include both spatial and attribute data of the GIS that can be used as useful information for the farmers every year. The result of the research is summarized as follow; First, the system provides the position, attributes and spatial data of the horticultural farm through AML. Second, the user interface that composed of a basic function menu and application menu is easy to use. Third, the method which applicated overlay and analysis would be need to manage farming data in this horticultural farm and to develop a dynamic decision support system interfaced with GIS.