• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.6
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• pp.824-834
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• 1993

In cellular mobile communication systems, if the size of a cell is decreasing for economic utilization of frequency resources, frequent handovers may be requested because the time a mobile stays in a cell is decreasing. In general the measured parameters to decide handover including RSSI, BER, and the distance between mobile station and base station, are usually incorrect and handover decision using single parameter insufficient. Therefore, the better handover algorithm should take over the problems of this uncertain measurements, and make the decision more robust and flexible by the consideration of all those decision parameters at the same time. We propose a novel handover algorithm based the multicriteria decision making, in which those parameters are participated in the decision process using aggregation function in fuzzy set theory. As a simulation results, the overall decision making is more reliable and flexible than the conventional method using only one parameter, RSSI in terms of call force ratio, and handover request ratio.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.39-50
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• 2015

Genetic algorithm (GA) and particle swarm optimization (PSO) are two excellent approaches to multimodal optimization problems. However, slow convergence or premature convergence readily occurs because of inappropriate and inflexible evolution. In this paper, a novel optimization algorithm with a flexible grid optimization (FGO) is suggested to provide adaptive trade-off between exploration and exploitation according to the specific objective function. Meanwhile, a uniform agents array with adaptive scale is distributed on the gird to speed up the calculation. In addition, a dominance centroid and a fitness center are proposed to efficiently determine the potential guides when the population size varies dynamically. Two types of subregion division strategies are designed to enhance evolutionary diversity and convergence, respectively. By examining the performance on four benchmark functions, FGO is found to be competitive with or even superior to several other popular algorithms in terms of both effectiveness and efficiency, tending to reach the global optimum earlier. Moreover, FGO is evaluated by applying it to a parameter decision in a least squares support vector machine (LS-SVM) to verify its practical competence.

• Journal of Communications and Networks
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• v.17 no.3
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• pp.213-220
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• 2015

In this paper, we present a reliability-based iterative proportionality-logic decoding algorithm for two classes of structured low-density parity-check (LDPC) codes. The main contributions of this paper include: 1) Syndrome messages instead of extrinsic messages are processed and exchanged between variable nodes and check nodes, which can reduce the decoding complexity; 2) a more flexible decision mechanism is developed in which the decision threshold can be self-adjusted during the iterative process. Such decision mechanism is particularly effective for decoding the majority-logic decodable codes; 3) only part of the variable nodes satisfying the pre-designed criterion are involved for the presented algorithm, which is in the proportionality-logic sense and can further reduce the computational complexity. Simulation results show that, when combined with factor correction techniques and appropriate proportionality parameter, the presented algorithm performs well and can achieve fast decoding convergence rate while maintaining relative low decoding complexity, especially for small quantized levels (3-4 bits). The presented algorithm provides a candidate for those application scenarios where the memory load and the energy consumption are extremely constrained.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.514-519
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• 2003

The aircraft engine is usually supported by rolling element bearings and has a small damping rate, which is vol y sensitive to external force. The high-performance requirement of the rotors leads to complex assembly designs and are more flexible. Squeeze film dampers (SFDs) are introduced to provide damping while crossing the critical speeds and stability to the rotor s :stem. Hence, the focus of the present investigation is on the decision of an optimal size of the flexible rotor system supported by the squeeze film dampers to minimize the maximum transmitted load and unbalance response over a range operating speeds. The enhanced genetic algorithm (EGA), which was developed by authors, is used in the optimization process. This algorithm is based on the synthesis of a modified genetic algorithm and simplex method. The results show significant benefits in using EGA when compared with nonlinear programming (NLP).

• Journal of the Korea Society for Simulation
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• v.9 no.1
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• pp.21-38
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• 2000

A fuzzy dispatching algorithm with adaptable control scheme is proposed for more flexible and adaptable operation of AGV system. The basic idea of the algorithm is prioritization of all move requests based on the fuzzy urgency. The fuzzy urgency is measured by the fuzzy multi-criteria decision-making method, utilizing the relevant information such as incoming and outgoing buffer status, elapsed time of move request, and AGV traveling distance. At every dispatching decision point, the algorithm prioritizes all move requests based on the fuzzy urgency. The performance of the proposed algorithm is compared with several dispatching algorithms in terms of system throughput in a hypothetical job shop environment. Simulation experiments are carried out varying the level of criticality ratio of AGVs , the numbers of AGVs, and the buffer capacities. The rule presented in this study appears to be more effective for dispatching AGVs than the other rules.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1995.10a
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• pp.30-36
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• 1995

Conventionally design for multi-stage cold forging depends on the designer's experience and decision-making. Due to such non-deterministic nature of the process sequence design, a flexible inference engine is needed for process design expert system. In this study, A* searching algorithm was introduced to arrive at the vetter process sequence design considering the number of forming stages and levels of effective strain, effective stress, and forming load during the porcess. In order to optimize the process sequence in producing the final part, cost function was defined and minimized using the proposed A* searching algorithm. For verification of the designed forming sequences, forming experiments and finite element analyses were carried out in the present investigation. The developed expert system using A* searching algorithm can produce a flexible design system based on changes in the number of forming stages and weights.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.833-834
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• 2006

In this paper, It is proposed collecting, processing, and learning of data with PIC16F877 and Acode 300[3], constructing database in PC. The PIC16F877 microcontroller nodes are the radio sensor and the DC motor controller. The PC of flexible factory level construct the data-table for object-oriented optimal environment control. The DC Motor control command is decision with back-propagation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2942-2960
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• 2022

The core of cognitive radio is the problem concerning intelligent decision-making for communication parameters, the objective of which is to find the most appropriate parameter configuration to optimize transmission performance. The current algorithms have the disadvantages of high dependence on prior knowledge, large amount of calculation, and high complexity. We propose a new decision-making model by making full use of the interactivity of reinforcement learning (RL) and applying the Q-learning algorithm. By simplifying the decision-making process, we avoid large-scale RL, reduce complexity and improve timeliness. The proposed model is able to find the optimal waveform parameter configuration for the communication system in complex channels without prior knowledge. Moreover, this model is more flexible than previous decision-making models. The simulation results demonstrate the effectiveness of our model. The model not only exhibits better decision-making performance in the AWGN channels than the traditional method, but also make reasonable decisions in the fading channels.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.514-521
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• 2016

The High Efficiency Video Coding (HEVC) standard provides superior coding efficiency by utilizing highly flexible block structure and more diverse coding modes. However, rate-distortion optimization (RDO) process for the decision of optimal block size and prediction mode requires excessive computational complexity. To alleviate the computation load, this paper proposes a new moment-based fast CU size decision algorithm for intra coding in HEVC. In the proposed method, moment values are computed in each CU block to estimate the texture complexity of the block from which the decision on an additional CU splitting procedure is performed. Unlike conventional methods which are mostly variance-based approaches, the proposed method incorporates the third-order moments of the CU block in the design of the fast CU size decision algorithm, which enables an elaborate classification of CU types and thus improves the RD-performance of the fast algorithm. Experimental results show that the proposed method saves 32% encoding time with 1.1% increase of BD-rate compared to HM-10.0, and 4.2% decrease of BD-rate compared to the conventional variance-based fast algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1415-1421
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• 2016

There are considerable concern on the methods for the efficient utilization of the test-resources as increasing of the number of the tests for functionality and performance verification of weapon systems. Furthermore, with an increase in the complexity of the resource assignment the decision support is required. Test resource allocation is basically the same problems as conventional NP-hard FJSP(Flexible Job Shop Problem), therefore empirical test resource allocation method that has been used in many decades is limited in the time performance. Although research has been conducted applying the genetic algorithm to the FJSP, it is limited in the test resource allocation domain in which more than one machine is necessary for a single operation. In this paper, a variable group genetic algorithm is proposed. The algorithm is expected to improve the test plan efficiency by automating and optimizing the existing manual based allocation. The simulation result shows that the algorithm could be applicable to the test plan.