• Journal of the Korea Institute of Building Construction
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• v.16 no.5
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• pp.437-445
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• 2016

Since typhoon is a critical meteorological disaster, some advanced countries have developed typhoon damage prediction models. However, although South Korea is vulnerable to typhoons, there is still shortage of study in typhoon damage prediction model reflecting the vulnerability of domestic building and features of disaster. Moreover, many studies have been only focused on the characteristics and typhoon and regional characteristics without various influencing factors. Therefore, the objective of this study is to analyze typhoon damage by path and develop to prediction model for building damage ratio by using multiple regression analysis. This study classifies the building damages by typhoon paths to identify influencing factors then the correlation analysis is conducted between building damage ratio and their factors. In addition, a multiple regression analysis is applied to develop a typhoon damage prediction model. Four categories; typhoon information, geography, construction environment, and socio-economy, are used as the independent variables. The results of this study will be used as fundamental material for the typhoon damage prediction model development of South Korea.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.459-473
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• 2007

In this paper, we suggest a spatial regression model to predict AADT. Although Euclidian distances between one monitoring site and its neighboring sites were usually used in the many analysis, we consider the shortest travel path between monitoring sites to predict AADT for unmonitoring site using spatial regression model. We used universal Kriging method for prediction and found that the overall predictive capability of the spatial regression model based on shortest travel path is better than that of the model based on multiple regression by cross validation.

• Journal of the Korea Computer Industry Society
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• v.3 no.5
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• pp.547-556
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• 2002

This paper was proposed a wave path loss prediction algorithm using multilayer perceptron (MLP) model and wave propagation characteristic parameters for Wireless LAN in indoor radio environments. Receiving power was predicted by calculating indoor path loss in a Wireless LAN that has transmission power of 100mW and frequency of 2.4GHz, and was compared with measured. In the result of measurement shows that there is a difference between predicted and measured receiving power which can be reduced by an accurate analysis of the various path loss factors. In order to fix the access point(AP) positions was used the proposed a wave path loss prediction algorithm, and designed the optimum cell for Wireless LAN.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.655-660
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• 2009

The context prediction algorithms are not suitable to provide real-time personalized service for users in context-awareness environment. The algorithms have problems like time delay in training data processing and the difficulties of implementation in real-time environment. In this paper, we propose a prediction algorithm with user modeling to shorten of processing time and to improve the prediction accuracy in the context prediction algorithm. The algorithm uses moving path of user contexts for context prediction and generates user model by time-series analysis of user's moving path. And that predicts the user context with the user model by sequence matching method. We compared our algorithms with the prediction algorithms by processing time and prediction accuracy. As the result, the prediction accuracy of our algorithm is similar to the prediction algorithms, and processing time is reduced by 40% in real time service environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1A
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• pp.1-7
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• 2011

Cell Capacity and cell layout are strongly dependent on the up-link interference caused by out-of-cell mobiles. Accurate prediction of the propagation path loss from out-of-cell mobiles is essential to achieve system designs that minimize the infrastructure required for a given quality of service (QOS). Less accurate predictions can be expected to yield designs requiring the use of a greater number of base stations. In order to quantify the dependence of infrastructure on prediction accuracy, this paper considers the cellular systems, LOS (line of sight) cells along a road or highway.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.103-112
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• 1998

This paper proposes a propagation prediction model which can calculate a propagation path loss easily at option point in case of the propagation processing by repeat reflection when we analysis a propagation route, it makes the calculation speed which is the defect of a geometrical of image method and a ray-launching method improve and we develop and apply the algorithms which can do an angle of incidence, an angle of reflection with a propagation direct path, a reflection path and a maximum reflection number arithmetic process synchronously. Finally we choose as a sample which is the real road condition where is around SK telecoms chunnam branch office in wolgok-dong, kwangsan-ku, kwangju and simulate proposition model then we demonstrate the relative superiority with comparing the results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1774-1794
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• 2024

In the field of environmental sensing, it is necessary to develop radio planning techniques for the next generation Internet of Things (IoT) networks over mixed terrains. Such techniques are needed for smart remote monitoring of utility supplies, with links situated close to but out of range of cellular networks. In this paper, a three-dimension (3-D) geometric optimization algorithm is proposed, considering the positions of edge IoT devices and antenna coupling factors. Firstly, a multi-level single linkage (MLSL) iteration method, based on geometric objectives, is derived to evaluate the data rates over ISM 915 MHz channels, utilizing optimized power-distance profiles of continuous waves. Subsequently, a federated learning (FL) data selection algorithm is designed based on the 3-D geometric positions. Finally, a measurement example is taken in a meadow biome of the Mexican Colima district, which is prone to fluvial floods. The empirical path loss model has been enhanced, demonstrating the accuracy of the proposed optimization algorithm as well as the possibility of further prediction work.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.592-598
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• 2008

This paper presents collision prediction and avoidance method for AGVS (Automatic Guide Vehicle System). Also, we propose the PO(Right of Path Occupying) with decentralized delay time for collision avoidance. Classified essential element of AGV's working environment is modeled in this paper. Using this model, we propose a new shortest path algorithm using A* search algorithm and obtain the information on AGVs travel time, coordinates and rotation vector. Finally, we use the AGVs information data as input for simulation program. The simulation practice is used in order to evaluate a collision prediction and avoidance, and it has been presented to demonstrate the applicability of the minimize delay time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.31-44
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• 2004

The study of Estimation model for the short-term travel time prediction. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Before providing a dynamic shortest path finding, the prediction model should be verified. To verify the prediction model, three models such as Kalman filtering, Stochastic Process, ARIMA. The ARIMA model should adjust optimal parameters according to the traffic conditions. It requires a frequent adjustment process of finding optimal parameters. As a result of these characteristics, It is difficult to use the ARIMA model as a prediction. Kalman Filtering model has a distinguished prediction capability. It is due to the modification of travel time predictive errors in the gaining matrix. As a result of these characteristics, the Kalman Filtering model is likely to have a non-accumulative errors in prediction. Stochastic Process model uses the historical patterns of travel time conditions on links. It if favorably comparable with the other models in the sense of the recurrent travel time condition prediction. As a result, for the travel time estimation, Kalman filtering model is the better estimation model for the short-term estimation, stochastic process is the better for the long-term estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.765-772
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• 2013

In this paper, we studied the path loss model of Air Traffic Control(ATC) telecommunication radio channel at the Incheon International Airport(IIA) concourse area. We measured wave propagation characteristics on the two frequencies among VHF/UHF channel bands. The transmitting site radiated the Continuous Wave(CW). The propagation measurement was taken using the moving vehicle equipped with receiver and antenna. The transmitting power, frequency, and antenna height are the same as the current operating condition. The path loss exponent and intercept parameters were extracted by the basic path loss model and hata model. The path loss exponents at Concourse area were 3.1/3.13 and 3.01/3.38 respectively in 128.2MHz and 269.1MHz. The deviation of prediction error is 2.77/3.17 and 4.01/3.66. The new path loss equation at the Concourse area was also developed using the derived path loss parameters. The new path loss model was compared with other models. This result will be helpful for the ATC site selection and service quality evaluation.