• Earthquakes and Structures
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• v.22 no.4
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• pp.421-430
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• 2022

This paper addresses the stochastic control problem of robots within the framework of parameter uncertainty and uncertain noise covariance. First of all, an open circle deterministic trajectory optimization issue is explained without knowing the unequivocal type of the dynamical framework. Then, a Linear Quadratic Gaussian (LQG) controller is intended for the ostensible trajectory-dependent linearized framework, to such an extent that robust hereditary NN robotic controller made out of the Kalman filter and the fuzzy controller is blended to ensure the asymptotic stability of the non-continuous controlled frameworks. Applicability and performance of the proposed algorithm shown through simulation results in the complex systems which are demonstrate the feasible to improve the performance by the proposed approach.

• Journal of Industrial Technology
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• v.43 no.1
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• pp.57-62
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• 2023

In this review, we introduce the non-parametric Bayesian filtering algorithm known as the point-mass filter (PMF) and discuss recent studies related to it. PMF realizes Bayesian filtering by placing a deterministic grid on the state space and calculating the probability density at each grid point. PMF is known for its robustness and high accuracy compared to other nonparametric Bayesian filtering algorithms due to its uniform sampling. However, a drawback of PMF is its inherently high computational complexity in the prediction phase. In this review, we aim to understand the principles of the PMF algorithm and the reasons for the high computational complexity, and summarize recent research efforts to overcome this challenge. We hope that this review contributes to encouraging the consideration of PMF applications for various systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.155-161
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• 2017

This paper suggests polynomial time solution algorithm for Sudoku puzzle problem. This problem has been known NP (non-deterministic polynomial time)-complete. The proposed algorithm set the initial value of blank cells to value range of [$1,2,{\cdots},9$]. Then the candidate set values in blank cells deleted by preassigned clue in row, column, and block. We apply the basic rules of Stuart, and proposes two additional rules. Finally we apply binary backtracking(BBT) technique. For the experimental Sudoku puzzle with various categories of solution, the BBT algorithm can be obtain all of given Sudoku puzzle regardless of any types of solution.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.4
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• pp.71-79
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• 2000

The original March algorithms cannot detect CMOS ADOFs(Address Decoder Open Faults) which requires separate deterministic test patterns. Modified March algorithm using DOF(Degree of Freedom) was suggested to detect these faults in addition to conventional stuck faults. This paper augments the modified march test to further capture NPSFs(Neighborhood Pattern Sensitive Faults). Complete CA(Cellular Automata) is used for address generation and Rl-LFSRs(Randomly Inversed LFSRs) for data generation. A new modified March algorithm can detect SAF, CF, TF, CMOS ADOFs, and part of NPSFs. Time complexity of this algorithm is still O(n).

• Journal of the Korean Geotechnical Society
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• v.18 no.6
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• pp.117-127
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• 2002

A deterministic approach of slope stability, which is generally corresponding to the model of a simple non-linear function for slopes, is problematic in that it does not account the versatile characteristics of ground layers in an effective way. To resolve this problem, this study proposes a new way of analyzing slope stability, so-called “genetic algorithm method, ” so as to reflect some particular conditions pertaining to the grounds under concern. Similarities and differences in slope stability that may exist between homogeneous and multiple ground layers are examined in a competitive manner, Overall, though similarities deemed a little bit salient, the algorithm method turned out to be very applicable to estimating the validity of slope stability. Furthermore, an additional effort to consider long-standing sequential and dynamic changes in both the amount of rainfall and the underground water level is made in order to improve the results.

• The Journal of the Acoustical Society of Korea
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• v.22 no.6
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• pp.496-504
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• 2003

In this paper, the error tolerance of each array element to ensure a given specified error level for the array pattern is analyzed using the Genetic Algorithm. In the conventional deterministic method for synthesis of sonar way problems the computational resource required in the simulation grows rapidly as the number of way elements increases. To alleviate this numerical inefficiency, the Monte-Carlo method may be considered as an alternative technique for array syntheses. However, it is difficult to apply the method to the synthesis of array patterns because of its relatively lower accuracy in spite of moderate computational complexity. A new analysis method for estimating error tolerances in sonar arrays is Proposed since the Genetic Algorithm has significant promise to efficiently solve way synthesis problems. Through several numerical tests in linear and planar arrays, it is demonstrated that the proposed method can provide accurate results for error tolerances of sonar arrays.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.1-9
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• 2011

Wireless mobile networks that exploit generalized PF scheduling can dynamically allocate network resources by using scheduling parameters. There are limitations to predict throughputs by the conventional stochastic approach in general. Moreover the limitations make it difficult to find appropriate scheduling parameters for achieving the demanded throughputs. This paper derives a prediction algorithm that predicts throughputs of the networks by using deterministic approach. A throughput adjust algorithm and a throughput switching algorithm are derived from the prediction algorithm. The performance of the throughput prediction/switching algorithms is evaluated by a simulator based on IEEE 802.16m system.

• Fire Science and Engineering
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• v.13 no.1
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• pp.21-30
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• 1999

In this paper, the smoke filling process for the three types of atrium spaces are simulated u using the two types of deterministic fire model; zone models and field models. The zone models u used are the FffiST, CFAST, and CCFM.VENTS m떠els develo야퍼 at the Building and Fire R Research Laboratories, NIST, USA and the NBTC one-room model of FIR.ECAIι delveloped at C CSffiO, Austr;외ia. The field models used are the fire field model developed by W. K Chow and a a self-developed Sl\1EP(Smoke Movement Estimating Program) based on computational fluid d dynamics the$\alpha$1es. The results pn려icted by the two approaches are very similar. The field model u using SIl\1PLE algorithm or SIl\1PLER algorithm requires much more computing time compared w with the use of Sl\1EP using PISO algorithm.

• Journal of Communications and Networks
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• v.6 no.1
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• pp.68-77
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• 2004

In the near future packet networks should support applications which can not predict their traffic requirements in advance, but still have tight quality of service requirements, e.g., guaranteed bandwidth, jitter, and packet loss. These dynamic characteristics mean that the sources can be made to modify their data transfer rates according to network conditions. Depending on the customer&; needs, network operator can differentiate incoming connections and handle those in the buffers and the interfaces in different ways. In this paper, dynamic QoS-aware scheduling algorithm is presented and investigated in the single node case. The purpose of the algorithm is in addition to fair resource sharing to different types of traffic classes with different priorities ?to maximize revenue of the service provider. It is derived from the linear type of revenue target function, and closed form globally optimal formula is presented. The method is computationally inexpensive, while still producing maximal revenue. Due to the simplicity of the algorithm, it can operate in the highly nonstationary environments. In addition, it is nonparametric and deterministic in the sense that it uses only the information about the number of users and their traffic classes, not about call density functions or duration distributions. Also, Call Admission Control (CAC) mechanism is used by hypothesis testing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.40-48
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• 2022

An automated material handling system (AMHS) has been emerging as an important factor in the semiconductor wafer manufacturing industry. In general, an automated guided vehicle (AGV) in the Fab's AMHS travels hundreds of miles on guided paths to transport a lot through hundreds of operations. The AMHS aims to transfer wafers while ensuring a short delivery time and high operational reliability. Many linear and analytic approaches have evaluated and improved the performance of the AMHS under a deterministic environment. However, the analytic approaches cannot consider a non-linear, non-convex, and black-box performance measurement of the AMHS owing to the AMHS's complexity and uncertainty. Unexpected vehicle congestion increases the delivery time and deteriorates the Fab's production efficiency. In this study, we propose a Q-Learning based dynamic routing algorithm considering vehicle congestion to reduce the delivery time. The proposed algorithm captures time-variant vehicle traffic and decreases vehicle congestion. Through simulation experiments, we confirm that the proposed algorithm finds an efficient path for the vehicles compared to benchmark algorithms with a reduced mean and decreased standard deviation of the delivery time in the Fab's AMHS.