• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.301-307
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• 2022

Energy consumption has grown alongside dramatic population increases. Statistics show that buildings in particular utilize a significant amount of energy, worldwide. Because of this, building energy prediction is crucial to best optimize utilities' energy plans and also create a predictive model for consumers. To improve energy prediction performance, this paper proposes a ResNet-LSTM model that combines residual networks (ResNets) and long short-term memory (LSTM) for energy consumption prediction. ResNets are utilized to extract complex and rich features, while LSTM has the ability to learn temporal correlation; the dense layer is used as a regression to forecast energy consumption. To make our model more robust, we employed Huber loss during the optimization process. Huber loss obtains high efficiency by handling minor errors quadratically. It also takes the absolute error for large errors to increase robustness. This makes our model less sensitive to outlier data. Our proposed system was trained on historical data to forecast energy consumption for different time series. To evaluate our proposed model, we compared our model's performance with several popular machine learning and deep learning methods such as linear regression, neural networks, decision tree, and convolutional neural networks, etc. The results show that our proposed model predicted energy consumption most accurately.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.19-27
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• 2022

Across the world, 'housing' comprises a significant portion of wealth and assets. For this reason, fluctuations in real estate prices are highly sensitive issues to individual households. In Korea, housing prices have steadily increased over the years, and thus many Koreans view the real estate market as an effective channel for their investments. However, if one purchases a real estate property for the purpose of investing, then there are several risks involved when prices begin to fluctuate. The purpose of this study is to design a real estate price 'return rate' prediction model to help mitigate the risks involved with real estate investments and promote reasonable real estate purchases. Various approaches are explored to develop a model capable of predicting real estate prices based on an understanding of the immovability of the real estate market. This study employs the LSTM method, which is based on artificial intelligence and deep learning, to predict real estate prices and validate the model. LSTM networks are based on recurrent neural networks (RNN) but add cell states (which act as a type of conveyer belt) to the hidden states. LSTM networks are able to obtain cell states and hidden states in a recursive manner. Data on the actual trading prices of apartments in autonomous districts between January 2006 and December 2019 are collected from the Actual Trading Price Disclosure System of the Ministry of Land, Infrastructure and Transport (MOLIT). Additionally, basic data on apartments and commercial buildings are collected from the Public Data Portal and Seoul Metropolitan Government's data portal. The collected actual trading price data are scaled to monthly average trading amounts, and each data entry is pre-processed according to address to produce 168 data entries. An LSTM model for return rate prediction is prepared based on a time series dataset where the training period is set as April 2015~August 2017 (29 months), the validation period is set as September 2017~September 2018 (13 months), and the test period is set as December 2018~December 2019 (13 months). The results of the return rate prediction study are as follows. First, the model achieved a prediction similarity level of almost 76%. After collecting time series data and preparing the final prediction model, it was confirmed that 76% of models could be achieved. All in all, the results demonstrate the reliability of the LSTM-based model for return rate prediction.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.2
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• pp.1-9
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• 2005

This study was performed to analyze time series landuse pattern of urban areas and the change of the areas by using remotely sensed multiple sensors. The results were as follows. First, according to the result of time series analysis, most agricultural land has been changed into built-up areas by development work such as the land development or land readjustment project, arrangement of science parks or military facilities, and location of public establishment like government buildings. Second, if the expansion of built-up areas maintains the present scale and speed, it seems that a lot of parts of land would be changed into built-up areas, especially centering around agricultural land, so it is necessary to establish the plan for urban space. Third, I have synthetically collected the data of the project of urban development and systematically monitored the process of in expansion the built-up areas up to now (from the past). I hereby could lay the foundation that makes us scientifically forecast the direction of expansion in the built-up areas by the urban development in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.1-16
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• 2022

Areas developed through land reclamation projects have huge economic advantages in terms of supplying lands that can be used for farmlands, urban areas and etc., however have relatively small areas of grasslands and densely located buildings compared to inland cities. Hence, an urban heat island is occurring in these areas due to this characteristic, and in particular, the urban heat island in Cheongna International City is getting serious. In this study, the urban heat island in Cheongna International City was evaluated and analyzed by classified into the three periods after the reclamation project: farmland(2001-2008), development(2009-2013) and artificial grassland(2014-2020). The land cover map and Landsat time-series imagery were utilized for measuring the differences of the land surface temperatures between the urbanized areas and the grassland/forest areas in Cheongna International City. The statistical results showed that the differences in the land surface temperature between these areas were calculated to be at most 0℃ during the period of farmland, at most 3.60℃ during the period of development, and at most 2.51℃ during the period of grassland. This study proved that the urban heat island phenomenon increased when the urbanized areas increased, and the urban heat island phenomenon decreased when the artificial grassland areas increased in Cheongna International City where the reclamation project was carried out. The statistical results derived through this research can be used as the reference data for identifying the urban heat island problem in urban planning and establishing the reduction plan.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.527-534
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• 2011

This paper describes an analysis of topographical changes to the Eulsuk-Island at the Nakdong River Estuary using a long-term dataset of high resolution aerial images from 1983 to 2007. Ground control surveying was performed at some feature points using GPS(Global Positioning System) to accomplish AT(Aerial Triangulation) for past aerial images. Even if some still existing feature points appeared on old aerial images were used as GCPs(Ground Control Points) for past aerial images in AT, its accuracy reached at 1m level. Since then, a quantitative analysis of topographical changes was conducted on digital orthophotos produced by a series of aerial images taken by different years. The change volume of total area, construction, vegetation, buildings and roads could be extracted per each period in study area. The total area decreased from 1983 to 1992, but it has not almost changed since 1992. According to the continuous development, the area of vegetation has steadily decreased, while that of buildings and roads has generally increased. The result of this study can provide us with invaluable base data for further topographical change monitoring in Eulsuk-Island and Nakdong River estuary caused by continuous development in this area.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.89-96
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• 2015

Location-based social media data have high potential to be used in various area such as big data, location based services and so on. In this study, we applied a series of analysis methodology to figure out how the important keywords in location-based social media are spatially distributed by analyzing text information. For this purpose, we collected tweet data with geo-tag in Gangnam district and its environs in Seoul for a month of August 2013. From this tweet data, principle keywords are extracted. Among these, keywords of three categories such as food, entertainment and work and study are selected and classified by category. The spatial clustering is conducted to the tweet data which contains keywords in each category. Clusters of each category are compared with buildings and benchmark POIs in the same position. As a result of comparison, clusters of food category showed high consistency with commercial areas of large scale. Clusters of entertainment category corresponded with theaters and sports complex. Clusters of work and study showed high consistency with areas where private institutes and office buildings are concentrated.

• Fire Science and Engineering
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• v.32 no.1
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• pp.33-39
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• 2018

When the fire in the high-rise building was not extinguished in its early stage and propagated over its origin, safe egress becomes one of the most important factor to minimize the casualties. Recently fire protection for high-rise building has been reinforced after experiencing the series of disastrous fires. But, we still find many high-rise buildings do not comply with those reinforcement. And also there is a possibility of failure of reinforced fire protection system. Under these situation safe egress guide would be the final layer of protection. In this study existing egress methods were identified and evaluated. According the result of study, priority in egress should be given to the tenants on the floor of fire origin and floors exposed to the risk of fire. Then, the rest of the tenants can be evacuated simultaneously. Floors exposed in fire risk shall be determined by fire tests and/or fire simulations. But, the result of fire monitoring shall override preliminary estimations. Egress time for each algorithm was estimated by egress simulation and the result was compared. There was a little difference in egress time between total egress and phased egress, and a big difference between using stairs only and using elevators and stairs together. to a constant thickness between layers constituting a firefighter's protective clothing should be considered in the future.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.6
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• pp.67-73
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• 2017

Recently, the demand for large diameter piles has been rapidly increased in order to secure the allowable bearing capacity of pile foundation due to the increase of large structures such as high rise buildings. In this study, to improve the shear capacity of a conventional PHC pile, a large diameter composite PHC pile strengthened by in-filled concrete and shear reinforcement was manufactured. All the piles were tested according to the shear strength test method of Korean Standard. As a result of the shear test, the F-type piles which are produced without shear reinforcement occurred abrupt horizontal cracks after flexural and inclined shear cracks occurred. On the contrary, the FT-type piles which are produced with shear reinforcement exhibited stable flexural and inclined shear cracks uniformly over the entire pile without abrupt horizontal cracks. Furthermore, the maximum load of the large diameter composite PHC pile improved to 2.9 times in the F series, and more than 3.3 times in the FT series compared to the conventional PHC pile. This result indicated that FT-type piles had excellent composite behavior due to the shear reinforcement and effectively prevented the unstable growth of inclined shear cracks.

• Tunnel and Underground Space
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• v.24 no.5
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• pp.354-365
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• 2014

The horizontal response spectra using the observed ground motions from 15 Fukuoka earthquake series, including main earthquake (2005/03/20; Mw=6.5), were analysed and then were compared to both the seismic design response spectra (Regulatory Guide 1.60), applied to the domestic nuclear power plants, and the Korean Standard Design Response Spectrum for general structures and buildings (1997). 178 horizontal ground motions, without considering soil types, were used for normalization with respect to the peak acceleration value of each ground motion. The results showed that response spectrum have strong dependency on epicentral distance. The results also showed that the horizontal response spectra revealed higher values for frequency bands at two frequency bands (about 8 - 10 and 16- 20 Hz) than Regulatory Guide 1.60. The results were also compared to the Korean Standard Building Design Spectrum for the 3 different soil types and showed that thehorizontal response spectra revealed higher values for almost all period bands than the Korean Standard Response Spectrum (500 yrs; Return Period; Seismic province 1; SE soil conditions). Through the qualitative improvements and quantitative enhancement of the observed ground motions, the diversity of the observed ground motions should be considered more significantly to improve the certainty of response spectrum.

• Structural Engineering and Mechanics
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• v.61 no.4
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• pp.527-538
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• 2017

The evaluation of the loss-of-support conditions of frictional beam-to-column connections using simplified numerical models describing the transverse response of a portal-like structure is presented in this paper considering the effects of the seismic-hazard disaggregation. Real earthquake time histories selected from European Strong-motion Database (ESD) are used to show the effects of the seismic-hazard disaggregation on the beam loss-of-support conditions. Seismic events are classified according to different values of magnitudes, epicentral distances and soil conditions (stiff or soft soil) highlighting the importance of considering the characteristics of the seismic input in the assessment of the loss-of-support conditions of frictional beam-to-column connections. A rigid and an elastic model of a frame of a precast industrial building (2-DoF portal-like model) are presented and adopted to find the minimum required friction coefficient to avoid sliding. Then, the mean value of the minimum required friction coefficient with an epicentral distance bin of 10 km is calculated and fitted with a linear function depending on the logarithm of the epicentral distance. A complete parametric analysis varying the horizontal and vertical period of vibration of the structure is performed. Results show that the loss-of-support condition is strongly influenced by magnitude, epicentral distance and soil conditions determining the frequency content of the earthquake time histories and the correlation between the maxima of the horizontal and vertical components. Moreover, as expected, dynamic characteristics of the structure have also a strong influence. Finally, the effect of the column nonlinear behavior (i.e. formation of plastic hinges at the base) is analyzed showing that the connection and the column are a series system where the maximum force is limited by the element having the minimum strength. Two different longitudinal reinforcement ratios are analyzed demonstrating that the column strength variation changes the system response.