• Proceedings of the KIEE Conference
• /
• 2005.11b
• /
• pp.162-164
• /
• 2005

This paper presents an hour-ahead System Marginal Price (SMP) forecasting framework based on a neural network. Recently, the deregulation in power industries has impacted on the power system operational problems. The bidding strategy of market participants in energy market is highly dependent on the short-term price levels. Therefore, short-term SMP forecasting is a very important issue to market participants to maximize their profits. and to market operator who may wish to operate the electricity market in a stable sense. The proposed hybrid neural network is composed of tow parts. First part of this scheme is pattern classification to input data using Kohonen Self-Organizing Map (SOM) and the second part is SMP forecasting using back-propagation neural network that has three layers. This paper compares the forecasting results using classified input data and unclassified input data. The proposed technique is trained, validated and tested with historical date of Korea Power Exchange (KPX) in 2002.

• Spatial Information Research
• /
• v.8 no.1
• /
• pp.101-116
• /
• 2000

Seoul Metropolitan Government(SMG) as well as the other local governments should have a role in managing groundwater according to the Groundwater Law. As a guidance of the management and control of groundwater use, this study emphasizes the necessity of the construction of 1 ; 5,000 hydrogeological maps and proposes possble usages of the maps. As expected to be a part of the groundwater GIS database constructed by SMG, the maps can be used as base maps to facilitate the whole processes related to the groundwater development and preservation. For the purpose of the construction of the 1 ; 5,000 hydrogelogical GIS database, we develop the classification system of the hydro-geological entities and their attributes.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.12 no.4
• /
• pp.516-523
• /
• 2009

Recently, the applications of unmanned robots are increasing in various fields including surveillance and reconnaissance, planet exploration and disaster relief. To perform their missions with success, the robots should be able to evaluate terrain's characteristics quantitatively and identify traversable regions to progress toward a goal using mounted sensors. Recently, the authors have proposed techniques that extract terrain information and analyze traversability for off-road navigation of an unmanned robot. In this paper, we examine the use of 3D world models(terrain maps) to classify obstacle and safe terrain for increasing the reliability of the proposed techniques. A world model is divided into several patches and each patch is classified as belonging either to an obstacle or a non-obstacle using three types of metrics. The effectiveness of the proposed method is verified on real terrain maps.

• IEIE Transactions on Smart Processing and Computing
• /
• v.6 no.4
• /
• pp.229-236
• /
• 2017

This paper presents an efficient object-based color image-retrieval algorithm that is suitable for the classification and retrieval of images from small to mid-scale datasets, such as images in PCs, tablets, phones, and cameras. The proposed method first finds salient regions by using regional feature vectors, and also finds several dominant colors in each region. Then, each salient region is partitioned into small sub-blocks, which are assigned 1 or 0 with respect to the number of pixels corresponding to a dominant color in the sub-block. This gives a binary map for the dominant color, and this process is repeated for the predefined number of dominant colors. Finally, we have several binary maps, each of which corresponds to a dominant color in a salient region. Hence, the binary maps represent the spatial distribution of the dominant colors in the salient region, and the union (OR operation) of the maps can describe the approximate shapes of salient objects. Also proposed in this paper is a matching method that uses these binary maps and which needs very few computations, because most operations are binary. Experiments on widely used color image databases show that the proposed method performs better than state-of-the-art and previous color-based methods.

• Journal of Ecology and Environment
• /
• v.35 no.3
• /
• pp.167-175
• /
• 2012

Coastal sand dune systems are particularly fragile and threaten the environment. However, these systems provide fundamental ecosystem services to the nearby urban areas, acting, for example, as protective buffers against erosion. In this paper, we attempt to classify the biotope types of coastal sand dune ecosystems and select an index for the assessment of the conservation value. The types of biotopes are categorized based on the vegetation map; floras are examined in order to research the effects of hinterlands on coastal sand dunes. In addition, a naturalization rate and an urbanization index for each biotope type in hinterlands are analyzed. In the ecosystem of coastal sand dunes, the urbanization index and naturalization rate shows a higher value in sand dunes with areas of road, residential, and idle land in farm villages, rice fields, and fields. On the contrary, a lower value in the urbanization index and naturalization rate is present when typical biotope types, such as sand dune vegetation and natural Pinus thunbergii forests, are widely distributed. Based on these results, urbanization index and naturalization rate should be used as critical indices for the assessment of the ecosystem of costal sand dunes.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.11
• /
• pp.2875-2882
• /
• 2000

Typically, the ultrasonic sensors can be used in navigation systems for modeling of the enviornment, obstacle avoidance, and map building. In this paper, we tried to approach an object classification method using the range data of the ultrasonic sensors. A characterization of the sonar scan is described that allows the differentiation of planes, corners, edges, cylindrical and rectangular pillars by processing the scanned data from three sonars. To use the data from the ultrasonic sensors as input to the neural networks, we have introduced a clustering, threshold, and bit operation algorithm for the obtained raw data, After repeated training of the neural network, the performance of the proposed method was obtained through experiments. Also, the recognition ranges of the proposed method were investigated. As a result of experiments, we found that the proposed method successfully recognized the objects within the accuracy of 78%.

• Korean Institute of Interior Design Journal
• /
• v.13 no.6
• /
• pp.132-139
• /
• 2004

This study is to a question in argument that existing theses about a trait spatial configuration of exhibition space were analyzed without appropriateness verification of analysis characteristics. Firstly, through theoretical studies of established thesis, validity twenty analysis characteristics was chosen by making an investigation into existing analysis characteristics. Secondly, through a subject of our investigation, forty-two exhibition space of nineteen museums and art museum at home and abroad, a distribution map of exhibition space was analyzed by multivariate analysis. As a result of this study : 1) Nine analysis characteristics which extracted through multivariate analysis was the principal analysis characteristics. 2) A scale was important characteristic for the classification of museum therefore a degree of space perception was ought to compare every one of similar scale museum. 3) When comparing a trait of spatial configuration at exhibition space, these characteristics came into effect on middle sized museums. 4) It was visually confirmed a trait of spatial configuration of each group between museum and art museum

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.7 no.1
• /
• pp.116-127
• /
• 2004

The objectives of this study are to build up the concept of Environment-Oriented Land Suitability Assessment(EOLSA) and to develop the EOLSA mapping system by applying the EOLSA criteria to the case study area. In order to draw out the EOLSA critera, this study adopted the Delphi method including the experts' awareness survey to urban planners as well as environmental researchers in May and June 2001. As a result, the concept of EPLSA was defined as a process of land use planning to scientifically assess the physical and environmental value of land and to classify conservation aptitude into several grades for the sustainable management of environmental resources. With an outcome of applying the EOLSA criteria with five degrees to the Seoul Metropolitan Area (SMA), Grade I, indicating the highest conservation value, accounted for 57.76% of the SMA. Then, Grade II reached up to 15.06%, Grade III 3.12%, Grade IV 15.92%, and Grade V, the lowest conservation value, 7.99% respectively. And also, the case analysis showed that the share of Grade I area was the highest in Gapyong county and Yangpyong county, Pochon county, Yeonchon county, Yongin city in the order and the lowest in Kwangmyong city, Osan city, Kunpo city, Kuri city, and Buchon city.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.16 no.1
• /
• pp.139-147
• /
• 1998

The national topographic basedata should meet a variety of user requirements. To generate, maintain and handle the national topographic basedata in economic and effective way, the nationally supported research works on data model, structure and feature classification system should be intensively undertaken by government agency, research institute and university. This paper presents the technical definitions of conceptual and logical model for proposed data model representing digital map data. The key aspects of the proposed data model are flexibility for accommodating user requirements as well as step-by-step approach for modification as necessary m recent future. Conclusively, the proposed data model is a transitional data model between simple graphical model and object oriented data model.

• Proceedings of the KSRS Conference
• /
• 1998.09a
• /
• pp.128-133
• /
• 1998

To assess the flood damages and to provide necessary information for preventing future catastrophe, it is necessary to appraise the inundated area with more accurate and rapid manner. This study attempts to evaluate the potential of satellite synthetic aperture radar (SAR) data for mapping of flood inundated area in southern part of Korea. JERS L-band SAR data obtained during the summer of 1997 were used to delineate the inundated areas. In addition, Landsat TM data were also used for analyzing the land cover condition before the flooding. Once the two data sets were co-registered, each data was separately classified. The water surface areas extracted from the SAR data and the land cover map generated using the TM data were overlaid to determine the flood inundated areas. Although manual interpretation of water surfaces from the SAR image seems rather simple, the computer classification of water body requires clear understanding of radar backscattering behavior on the earth's surfaces. It was found that some surface features, such as rice fields, runaway, and tidal flat, have very similar radar backscatter to water surface. Even though satellite SAR data have a great advantage over optical remote sensor data for obtaining imagery on time and would provide valuable information to analyze flood, it should be cautious to separate the exact areas of flood inundation from the similar features.