• ETRI Journal
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• v.37 no.2
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• pp.295-305
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• 2015

The purpose of this paper is to a develop model for generation expansion planning that can support diverse environmental policies for the reduction of greenhouse gases (GHGs) of South Korea. South Korea is required to reduce its GHG emissions by 30% from the BAU level by 2020. The Wien Automatic System Planning Package currently used in South Korea has limitations in terms of the application of renewable energy policies and GHG targets; this paper proposes the use of an equipment planning model named generation and transmission expansion program, which has been developed to resolve such limitations. For verification of the model, a case study on the 6th Basic Plan of Long-Term Electricity Supply and Demand has been conducted. The results show that for the year 2020 South Korea's annual GHG emissions will be 36.6% more than the GHG Target Management System (GHG TMS) target set for the same year (30%). To achieve the GHG TMS target, the costs involved amount to about 72 trillion KRW (70 billion USD). Consequently, the South Korean government needs to review the performability of this target.

• Advances in aircraft and spacecraft science
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• v.5 no.1
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• pp.73-105
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• 2018

A particular type of constant speed helical trajectory, with variable ascension rate, is proposed. Such trajectories are candidates of choice as motion primitives in automatic airplane trajectory planning; they can also be used by airplanes taking off or landing in limited space. The equations of motion for airplanes flying on such trajectories are exactly solvable. Their solution is presented, together with an analysis of the restrictions imposed on the geometrical parameters of the helical paths by the dynamical abilities of an airplane. The physical quantities taken into account are the airplane load factor, its lift coefficient, and the thrust its engines can produce. Formulas are provided for determining all the parameters of trajectories that would be flyable by a particular airplane, the final altitude reached, and the duration of the trajectory. It is shown how to construct speed interval tables, which would appreciably reduce the calculations to be done on board the airplane. Trajectories are characterized by their angle of inclination, their radius, and the rate of change of their inclination. Sample calculations are shown for the Cessna 182, a Silver Fox like unmanned aerial vehicle, and the F-16 Fighting Falcon.

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.310-330
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• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1819-1826
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• 2009

To enhance the automatic performance of existing predicting and planning algorithms that require a predefined probability of the states' transition, this paper proposes a multiple sequence generation system. When interacting with unknown environments, a virtual agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. We describe a sequential behavior generation method motivated from the change in the agent's state in order to help the virtual agent learn how to adapt to unknown environments. In a sequence learning process, the sensed states are grouped by a set of proposed motivation filters in order to reduce the learning computation of the large state space. In order to accomplish a goal with a high payoff, the learning agent makes a decision based on the observation of states' transitions. The proposed multiple sequence behaviors generation system increases the complexity and heightens the automatic planning of the virtual agent for interacting with the dynamic unknown environment. This model was tested in a virtual library to elucidate the process of the system.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.645-657
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• 2021

Along with the rapid development of the economy, the urban scale has extended rapidly, leading to the formation of different types of urban function districts (UFDs), such as central business, residential and industrial districts. Recognizing the spatial distributions of these districts is of great significance to manage the evolving role of urban planning and further help in developing reliable urban planning programs. In this paper, we propose an automatic UFD division method based on big data analysis of point of interest (POI) data. Considering that the distribution of POI data is unbalanced in a geographic space, a dichotomy-based data retrieval method was used to improve the efficiency of the data crawling process. Further, a POI spatial feature analysis method based on the mean shift algorithm is proposed, where data points with similar attributive characteristics are clustered to form the function districts. The proposed method was thoroughly tested in an actual urban case scenario and the results show its superior performance. Further, the suitability of fit to practical situations reaches 88.4%, demonstrating a reasonable UFD division result.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2004.11a
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• pp.163-168
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• 2004

The purpose of this study is to analyse the climatic characteristic of South Korea and use it as a fundamental data for planning an environmental housing complex in Seoul, the capital of South Korea. The world after the Industrial Revolution has greatly developed economically but falied to notice the importance of the environment. It has been gradually damaged by the reckless exploitation for tens of years, and thus inflicted a loss on human. In this study, necessity and usability of the application of the climatic element for planning the environmental housing complex are to be presented. The data used in this study are given by the Met.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.333-334
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• 2007

We propose a path planning method to decrease a inspection lead time of line scan camera in SMT(surface mount technology) in-line system. The inspection window area of printed circuit board should be minimized to consider the FOV(field of view) of line scan camera so that line scan inspector is going to find a optimal solution of path planning. We propose one of the hierarchical clustrering algorithm for a given board. Comparative simulation results are presented to verify the usefulness of proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.256-267
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• 2014

An automatic switch among ensembles of clustering algorithms is proposed as a part of the bibliographic big data retrieval system by utilizing a fuzzy inference engine as a decision support tool to select the fastest performing clustering algorithm between fuzzy C-means (FCM) clustering, Newman-Girvan clustering, and the combination of both. It aims to realize the best clustering performance with the reduction of computational complexity from O($n^3$) to O(n). The automatic switch is developed by using fuzzy logic controller written in Java and accepts 3 inputs from each clustering result, i.e., number of clusters, number of vertices, and time taken to complete the clustering process. The experimental results on PC (Intel Core i5-3210M at 2.50 GHz) demonstrates that the combination of both clustering algorithms is selected as the best performing algorithm in 20 out of 27 cases with the highest percentage of 83.99%, completed in 161 seconds. The self-adapted FCM is selected as the best performing algorithm in 4 cases and the Newman-Girvan is selected in 3 cases.The automatic switch is to be incorporated into the bibliographic big data retrieval system that focuses on visualization of fuzzy relationship using hybrid approach combining FCM and Newman-Girvan algorithm, and is planning to be released to the public through the Internet.

• Korean Journal of Remote Sensing
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• v.9 no.2
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• pp.21-34
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• 1993

Digitalized topographic information is necessary for many areas such as landscape analysis, civil engineering planning and design, and geographic information systems. It can also be used in flight simulator and automatic navigation of unmanned plane if it is stored in computer in relevant format. Topographic information is coded with various symbols including contour lines, and is analyzed by trained personnels. The information should be stored in computer for automatic analysis, but it requires a lot of time and manpower to enter the contours using manual input devices such as digitizing tablet. This paper deals with automatic extraction and reconstruction of 3D topographic information from 2D terrain map. Several algorithms were developed in this work including contour segment finding algorithm and contour segment linking algorithm. The algorithm were tested using real 2D terrain map.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.107-108
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• 2011

Since the development of railway technology, the current urban Railway the first train line in the country for safe operation control automatic/unattended operation, automatic train operation equipment available (ATO) on time and reliable operation has introduced. ATO Automatic operation controlled by the value (Target velocity) and the feedback value (Actual velocity) by the error between the backing and braking of the train by repeated low energy efficiency. In this paper, given a fixed distance stations between time operation with minimal energy in the driving characteristics and driving trains are modeled. Therefore, in line 5 real route time sectional drive straight sections for experimental data analysis / draft Section / curved and section of the train on that line is selected according to the changing driving patterns to minimize the energy optimal driving patterns were presented.