• 로봇학회논문지
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• 제18권1호
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• pp.1-9
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• 2023

This paper presents an optimal path planning strategy for aerial searching and surveying of a user-designated area using multiple Unmanned Aerial Vehicles (UAVs). The method is designed to deal with a single unseparated polygonal area, regardless of polygonal convexity. By defining the search area into a set of grids, the algorithm enables UAVs to completely search without leaving unsearched space. The presented strategy consists of two main algorithmic steps: cellular decomposition and path planning stages. The cellular decomposition method divides the area to designate a conflict-free subsearch-space to an individual UAV, while accounting the assigned flight velocity, take-off and landing positions. Then, the path planning strategy forms paths based on every point located in end of each grid row. The first waypoint is chosen as the closest point from the vehicle-starting position, and it recursively updates the nearest endpoint set to generate the shortest path. The path planning policy produces four path candidates by alternating the starting point (left or right edge), and the travel direction (vertical or horizontal). The optimal-selection policy is enforced to maximize the search efficiency, which is time dependent; the policy imposes the total path-length and turning number criteria per candidate. The results demonstrate that the proposed cellular decomposition method improves the search-time efficiency. In addition, the candidate selection enhances the algorithmic efficacy toward further mission time-duration reduction. The method shows robustness against both convex and non-convex shaped search area.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1571-1581
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• 2016

A novel method is proposed to construct the voltage stability boundary of power system considering different Reactive Power Control Mode (RPCM) of Doubly-Fed Induction Generator (DFIG) Wind Power Plant (WPP). It can be used for reflecting the static stability status of grid operation with wind power penetration. The analytical derivation work of boundary search method can expound the mechanism and parameters relationship of different WPP RPCMs. In order to improve the load margin and find a practical method to assess the voltage security of power system, the approximate method of constructing voltage stability boundary and the critical points search algorithms under different RPCMs of DFIG WPP are explored, which can provide direct and effective reference data for operators.

• Journal of Electrical Engineering and Technology
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• 제10권2호
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• pp.529-538
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• 2015

Due to the high efficiency and compact mechanical structure, direct drive variable speed generators are used for power conversion in wind turbines. The wind energy conversion system (WECS) considered in this paper consists of a permanent magnet synchronous generator (PMSG), uncontrolled rectifier, dc-dc boost converter controlled with maximum power point tracking (MPPT) and adaptive hysteresis controlled voltage source inverter (VSI). For high utilization of the converter's power capability and stabilizing voltage and power flow, constant DC-link voltage is essential. Step and search MPPT algorithm which senses the rectified voltage ($V_{DC}$) alone and controls the same is used to effectively maximize the output power. The adaptive hysteresis band current control is characterized by fast dynamic response and constant switching frequency. With MPPT and adaptive hysteresis band current control in VSI, the DC link voltage is maintained constant under variable wind speeds and transient grid currents respectively.

• 로봇학회논문지
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• 제8권4호
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• pp.256-265
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• 2013

A local map-based exploration algorithm for mobile robots is presented. Segmented frontiers and their relative transformations constitute a tree structure. By the proposed efficient frontier segmentation and a local map management method, a robot can reduce the unknown area and update the local grid map which is assigned to each frontier node. Although this local map-based exploration method uses only local maps and their adjacent node information, mapping completion and efficiency can be greatly improved by merging and updating the frontier nodes. Also, we suggest appropriate graph search exploration methods for corridor and hall environments. The simulation demonstrates that the entire environment can be represented by well-distributed frontier nodes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2542-2547
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• 2005

In this paper, we propose a support vector machine (SVM) hyper and kernel parameter optimization method which is based on minimizing radius/margin bound which is a kind of estimation of leave-one-error. This method uses dynamic encoding algorithm for search (DEAS) and gradient information for better optimization performance. DEAS is a recently proposed optimization algorithm which is based on variable length binary encoding method. This method has less computation time than genetic algorithm (GA) based and grid search based methods and better performance on finding global optimal value than gradient based methods. It is very efficient in practical applications. Hand-written letter data of MNI steel are used to evaluate the performance.

• 전자공학회논문지A
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• 제31A권10호
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• pp.1-9
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• 1994

In this paper, we have studied optimal FCL(Frequently Called List) table sizes in a grid topology circuit-switched network including wireless subscribers. The FCL table gives the position information of a destination subscriber for a call. When the call is generated in a node, this call is routed by the referenced position information of the destination subscriber in FCL table. In this paper, we have proposed an efficient routing algorithm, mixed FSR(Flood Search Routing) and DAR(Dynamic Adaptive Routing), considering moving wireless subscribers. Also, we have simulated hit ratio and incorrect ratio as performance parameters, consequently proposed the object function composed of table search time, hit ratio, incorrect ratio, FSR time and DAR time, and derived the optimal FCL table size by using it.

• 전자통신동향분석
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• 제34권4호
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• pp.32-42
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• 2019

The performance of machine learning algorithms significantly depends on how a configuration of hyperparameters is identified and how a neural network architecture is designed. However, this requires expert knowledge of relevant task domains and a prohibitive computation time. To optimize these two processes using minimal effort, many studies have investigated automated machine learning in recent years. This paper reviews the conventional random, grid, and Bayesian methods for hyperparameter optimization (HPO) and addresses its recent approaches, which speeds up the identification of the best set of hyperparameters. We further investigate existing neural architecture search (NAS) techniques based on evolutionary algorithms, reinforcement learning, and gradient derivatives and analyze their theoretical characteristics and performance results. Moreover, future research directions and challenges in HPO and NAS are described.

• 한국생물물리학회:학술대회논문집
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• 한국생물물리학회 1996년도 정기총회 및 학술발표회
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• pp.32-32
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• 1996

Molecular docking studies were performed for a humanized HBV Pre-S2 antibody and its antigen adr. Antigen structure was taken from NMR experiment and antibody structure was determined by using homology technique. At first step, Grid search was performed for finding energetically favorable orientations antigen. (omitted)

• 대한기계학회논문집A
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• 제20권10호
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• pp.3160-3172
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• 1996

A search algorithm for the collision free, time optimal transport path of overhead cranes has been proposed in this paper. The map for the working environment of overhead cranes was constructed in the form of three dimensional grid. The obstacle occupied region and unoccupied region of the map has been represented using the octree model. The best-first search method with a suitable estimation function was applied to select the knot points on the collision free transport path to the octree model. The optimization technique, minimizing the travel time required for transporting objects to the goal while subjected to the dynamic constraints of the crane system, was developed to find the smooth time optimal path in the form of cubic spline functions which interpolate the selected knot points. Several simulation results showed that the selected estimation function worked effectively insearching the knot points on the collision free transport path and that the resulting transport path was time optimal path while satisfying the dynamic constraints of the crane system.

• Management Science and Financial Engineering
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• 제15권1호
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• pp.81-96
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• 2009

Data mining, specially clustering is one of exciting research areas for ant based algorithms. Ant clustering algorithm, however, has many difficulties for resolving practical situations in clustering. We propose a new grid-based ant colony algorithm for clustering of data. The previous ant based clustering algorithms usually tried to find the clusters during picking up or dropping down process of the items of ants using some stigmergy information. In our ant clustering algorithm we try to make the ants reflect neighborhood information within the storage nests. We use two ant classes, search ants and labor ants. In the initial step of the proposed algorithm, the search ants try to guide the characteristics of the storage nests. Then the labor ants try to classify the items using the guide in-formation that has set by the search ants and the stigmergy information that has set by other labor ants. In this procedure the clustering decision of ants is quickly guided and keeping out of from the stagnated process. We experimented and compared our algorithm with other known algorithms for the known and statistically-made data. From these experiments we prove that the suggested ant mining algorithm found the clusters quickly and effectively comparing with a known ant clustering algorithm.