• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.21-31
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• 2005

In state-of-the-art games, characters can move in a goal-directed manner so that they can move to the goal position without colliding obstacles. Many path-finding methods have been proposed and implemented for these characters and most of them use the A* search algorithm. When .the map is represented with a regular grid of squares or a navigation mesh, it often takes a long time for the A* to search the state space because the number of cells used In the grid or the mesh increases for higher resolution. Moreover the A* search on the grid often causes a zigzag effect, which is not optimal and realistic. In this paper we propose to use visibility graphs to improve the search time by reducing the search space and to find the optimal path. We also propose a method of taking into account the size of moving characters in the phase of planning to prevent them from colliding with obstacles as they move. Simulation results show that the proposed method performs better than the grid-based A* algorithm in terms of the search time and space and that the resulting paths are more realistic.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.19-29
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• 2015

The purpose of this study is to suggest the grid search method for selecting an optimal decision tree model. It chooses optimal values for the maximum depth of tree and the minimum number of observations that must exist in a node in order for a split to be attempted. Therefore, the grid search method guarantees building a decision tree model that shows more precise and stable classifying performance. Through empirical analysis using data of job satisfaction of workplace reserve force commanders, we show that the grid search method helps us generate an optimal decision tree model that gives us hints for the improvement direction of labor conditions of Korean workplace reserve force commanders.

• Journal of Power Electronics
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• v.18 no.3
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• pp.841-852
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• 2018

This paper presents a dual-algorithm search method (GWO-GSO) combining grey wolf optimization (GWO) and golden-section optimization (GSO) to realize maximum power point tracking (MPPT) for photovoltaic (PV) systems. First, a modified grey wolf optimization (MGWO) is activated for the global search. In conventional GWO, wolf leaders possess the same impact on decision-making. In this paper, the decision weights of wolf leaders are automatically adjusted with hunting progression, which is conducive to accelerating hunting. At the later stage, the algorithm is switched to GSO for the local search, which play a critical role in avoiding unnecessary search and reducing the tracking time. Additionally, a novel restart judgment based on the quasi-slope of the power-voltage curve is introduced to enhance the reliability of MPPT systems. Simulation and experiment results demonstrate that the proposed algorithm can track the global maximum power point (MPP) swiftly and reliably with higher accuracy under various conditions.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.61-73
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• 2004

The efficiency of the real-time route guidance system(RGS) depends largely on the quality of route search algorithms. In this paper, we implement the coarse grid method(CGM) in mathematical programming for finding a good quality route of real-time RGS in large-scale networks. The proposed CGM examines coarser and wider networks as the search phase proceeds, in stead of searching the whole network at once. Naturally, we can significantly reduce computational efforts in terms of search time and memory requirement. We demonstrate the practical effectiveness of the proposed CGM with nationwide real road network simulation.

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.183-189
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• 2016

In this paper, an optimization study on a helicopter rotor blade cross-section was made. Generalization was made to the baseline cross-section to simplify the analysis. To have better performance in aeroelastic response, with the aerodynamic center being the origin of the baseline, the distance between aerodynamic center and shear center, and the distance between mass center and shear center of the blade were minimized. For efficient searching of optimum solutions over the design space, grid search method, which is a method of graphical search was used. Two design variables, radius of balancing weight at leading edge, and offset of the spar from leading edge were selected for the study. Cubic spline interpolation method was used to accommodate searching of the optimum solution. 2-Leveled searching system was devised in accordance with the interpolation method. Optimum solution was found to show 6% decrease in both distance between aerodynamic center and shear center, and mass center and shear center to the baseline.

• Journal of KIISE
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• v.43 no.9
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• pp.1026-1033
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• 2016

Path-finding on a grid map is a problem generally addressed in the fields of robotics, intelligent agents, and computer games. As technology advances, virtual game worlds tend to be represented more accurately and more realistically, resulting in an excessive increase in the number of grid tiles and in path-search time. In this study, we propose a path-finding algorithm that allows a prompt response to real-time queries by constructing a reduced state space and by precomputing all possible paths in an offline preprocessing stage. In the preprocessing stage, we vertically decompose free space on the grid map, construct a connectivity graph where nodes are the decomposed regions, and store paths between all pairs of nodes in matrix form. In the real-time query stage, we first find the nodes containing the query points and then retrieve the corresponding stored path. The proposed method is simulated for a set of maps that has been used as a benchmark for grid-based path finding. The simulation results show that the state space and the search time decrease significantly.

• The KIPS Transactions:PartA
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• v.11A no.1
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• pp.75-80
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• 2004

To interact database data with GRID system, implementation and installation of data manipulation module which manipulates database data and its index is required. Developing a search system searching data on web-based database, and integrating it with grid system, it is possible that searching data on web and use it directly on GRID system without independent data module. So, we can build easy and effective grid system, and the system could have more flexible architecture adapting data change. In this paper, we propose a searching system which interacting web-based database with GRID systems. We integrated the searching system with a bio god system which runs virtual screening jobs. As a result, UB Grid (Universal Bio Grid) is constructed. Developer could reduce time and effort required to integrate web data to GRID system, and user could use UB Grid system easily and effectively.

• Environmental Engineering Research
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• v.24 no.4
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• pp.559-565
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• 2019

In order to alleviate the environmental pressure caused by production process of thermal power plants, the application of cleaner production is imperative. To estimate the implementation effects of cleaner production in thermal plants and optimize the strategy duly, it is of great significance to take a comprehensive evaluation for sustainable development. In this paper, a hybrid model that integrated the analytic hierarchy process (AHP) with least squares support vector machine (LSSVM) algorithm optimized by grid search (GS) algorithm is proposed. Based on the establishment of the evaluation index system, AHP is employed to pre-process the data and GS is introduced to optimize the parameters in LSSVM, which can avoid the randomness and inaccuracy of parameters' setting. The results demonstrate that the combined model is able to be employed in the comprehensive evaluation of the cleaner production in the thermal power plants.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.89-104
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• 2008

Growth curves including Bass, Logistic and Gompertz functions are widely used in forecasting the market demand. Nonlinear least square method is often adopted for estimating the model parameters but it is difficult to set up the starting value for each parameter. If a wrong starting point is selected, the result may lead to erroneous forecasts. This paper proposes a method of selecting starting values for model parameters in estimating some growth curves by nonlinear least square method through grid search and transformation into linear regression model. Resealing the market data using the national economic index makes it possible to figure out the range of parameters and to utilize the grid search method. Application to some real data is also included, where the performance of our method is demonstrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3937-3954
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• 2014

With the increasing electricity consumption and the wide application of renewable energy sources, energy auction attracts a lot of attention due to its economic benefits. Many schemes have been proposed to support energy auction in smart grid. However, few of them can achieve range query, ranked search and personalized search. In this paper, we propose an efficient multi-keyword range query (EMRQ) scheme, which can support range query, ranked search and personalized search simultaneously. Based on the homomorphic Paillier cryptosystem, we use two super-increasing sequences to aggregate multidimensional keywords. The first one is used to aggregate one buyer's or seller's multidimensional keywords to an aggregated number. The second one is used to create a summary number by aggregating the aggregated numbers of all sellers. As a result, the comparison between the keywords of all sellers and those of one buyer can be achieved with only one calculation. Security analysis demonstrates that EMRQ can achieve confidentiality of keywords, authentication, data integrity and query privacy. Extensive experiments show that EMRQ is more efficient compared with the scheme in [3] in terms of computation and communication overhead.