• Bulletin of the Korean Mathematical Society
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• v.53 no.5
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• pp.1327-1339
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• 2016

Self-organizing systems arise very naturally in artificial intelligence, and in physical, biological and social sciences. In this paper, we modify the classic Cucker-Smale model at both microscopic and macroscopic levels by taking the target motion pattern driving forces into consideration. Such target motion pattern driving force functions are properly defined for the line-shaped motion pattern and the ball-shaped motion pattern. For the modified Cucker-Smale model with the prescribed line-shaped motion pattern, we have analytically shown that there is a flocking pattern with an asymptotic flocking velocity. This is illustrated by numerical simulations using both symmetric and non-symmetric pairwise influence functions. For the modified Cucker-Smale model with the prescribed ball-shaped motion pattern, our simulations suggest that the solution also converges to the prescribed motion pattern.

• Korean Journal of Computational Design and Engineering
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• v.10 no.5
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• pp.339-348
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• 2005

In this paper, LOD (Level Of Detail) for flocking, which is the real-time simulation on the movement or some groups such as fighting soldiers, moving fishes and flying birds, is presented. And a flocking LOD algorithm that uses factors such as the speed of fish, direction, and shape is proposed. Model data is modified for LOD in advance, so as to reduce strange edge collapse and unwanted holes. The errors of model data were identified by transforming polygonal model into octree-based cubes and revised before rendering. Experimental results show that the proposed algorithm considering flocking characteristics shows fast frame rates as compared with the conventional continuous LOD algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.195-200
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• 2004

Computer games use an intelligent method called flocking for boids' group behavioral modeling. Flocking can naturally model group behavioral patterns of unpredictable forms such as birds and fishes using some computer resource. In this paper, we implemented an ecosystem which is composed of predator and prey for group behavioral modeling of real underwater ecosystem. Also fuzzy logic is applied to implement instinct desire of ecosystem elements. As the result, we confirmed that the model can overcome breakdown of ecosystem and model naturally ecosystem behavior.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.49-58
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• 2009

Top-down approach in the intelligent robot research has focused on the single object intelligence however, it has two weaknesses. One is that has a high cost and a long spending time of sensing, calculating and communications. The other is the difficulty of responding to react changes in the unpredictable environment. we propose the collective intelligence algorithm based on Bottom-up approach for improving these weaknesses and the applied agent model and verify by simulation. The Modified Flocking Algorithm proposed in this research is the algorithm which is modified version of the concept of the Flocking (Craig Reynolds) which is used to model the flocks, herds, and schools in the graphics or games, and simplified the operation of conventional Flocking algorithm to make it easy to apply for the number of group robots. We modeled the Boid agent and verified possibility collectivization of the Modified Flocking Algorithm by simulation. And We validated by the actual multiple mobile robot experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1186-1189
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• 2016

A distributed uplink power control algorithm based on flocking model is proposed to improve the energy efficiency of mobiles station (MS) in cellular networks. As each bird in a flock matches its velocity with the average velocity of the adjacent birds, each MS in a cell matches its uplink rate with the average uplink rate of the co-channel MSs in adjacent cells by controlling its transmission power. Results show that the proposed algorithm effectively reduces the power consumption in the MS, while maintaining a low outage probability, which eventually improves the energy efficiency of the MS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1873-1880
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• 2016

Most of the energy used to operate a cellular network is consumed by a base station (BS), and reducing the transmission power of a BS is required for energy-efficient cellular networks. In this paper, a distributed transmit power control (TPC) algorithm is proposed based on the flocking model to improve the energy efficiency of a cellular network. Just as each bird in a flock attempts to match its velocity with the average velocity of adjacent birds, in the proposed algorithm each mobile station (MS) in a cell matches its rate with the average rate of the co-channel MSs in adjacent cells by controlling the transmit power of its serving BS. Simulation results show that the proposed TPC algorithm follows the same convergence properties as the flocking model and also effectively reduces the power consumption at the BSs while maintaining a low outage probability as the inter-cell interference increases. Consequently, it significantly improves the energy efficiency of a cellular network.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.176-180
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• 1998

We may gaze at some peculiar scenes of flocking of birds and fishes. This paper demonstrates that multiple agent mobile robots show complex behaviors from efficient and strategic rules. The simulated flock are realized by a distributed behavioral model and each mobile robot decides its own motion as an individual which moves constantly by sensing the dynamic environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.595-609
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• 2020

In this study, we propose a decentralized mathematical model for predictive control of a system of multi-autonomous unmanned aerial vehicles (UAVs), also known as drones. Being decentralized and autonomous implies that all members make their own decisions and fly depending on the dynamic information received from other unmanned aircraft in the area. We consider a variety of realistic characteristics, including time delay and communication locality. For this flocking flight, we do not possess control for central data processing or control over each UAV, as each UAV runs its collision avoidance algorithm by itself. The main contribution of this work is a mathematical model for stable group flight even in adverse weather conditions (e.g., heavy wind, rain, etc.) by adding Gaussian noise. Two of our proposed variance control algorithms are presented in this work. One is based on a simple biological imitation from statistical physical modeling, which mimics animal group behavior; the other is an algorithm for cooperatively tracking an object, which aligns the velocities of neighboring agents corresponding to each other. We demonstrate the stability of the control algorithm and its applicability in autonomous multi-drone systems using numerical simulations.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.1-9
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• 2010

In this paper, advanced evacuation analysis simulation on a passenger ship is performed. Velocity based model has been implemented and used to calculate the movement of the individual passengers under the evacuation situation. The age and gender of each passenger are considered as the factors of walking speed. Flocking algorithm is applied for the passenger's group behavior. Penalty walking velocity is introduced to avoid collision between the passengers and obstacles, and to prevent the position overlap among passengers. Application of flocking algorithm and penalty walking velocity to evacuation simulation is verified through implementation of the 11 test problems in IMO (International Maritime Organization) MSC (Maritime Safety Committee) Circulation 1238.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.8
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• pp.488-490
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• 2014

This paper deals with distributed time and frequency synchronization algorithms using the flocking technique for OFDMA-based wireless mesh networks. We propose a time and frequency synchronization model taking into account channel propagation delays existing in wireless mesh networks, and analyze the convergence condition of the proposed synchronization algorithm. Convergence performance of the proposed synchronization algorithm is analyzed via computer simulation in terms of synchronization parameters in the time and frequency synchronization model.