• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2561-2576
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• 2013

The ship ad-hoc network (SANET) extends the coverage of the high data-rate terrestrial communications to the ships with the reduced cost in maritime communications. Cognitive radio (CR) has the ability of sensing the radio environment and dynamically reconfiguring the operating parameters, which can make SANET utilize the spectrum efficiently. However, due to the dynamic topology nature and no central entity for data fusion in SANET, the interference brought into the primary network caused by the hidden primary user requires to be carefully managed by a sort of decentralized cooperative spectrum sensing schemes. In this paper, we propose a self-weighted decentralized cooperative spectrum sensing (SWDCSS) scheme to solve such a problem. The analytical and simulation results show that the proposed SWDCSS scheme is reliable to detect the primary user in SANET. As a result, secondary network can efficiently utilize the spectrum band of primary network with little interference to primary network. Referring the complementary receiver operating characteristic (ROC) curves, we observe that with a given false alarm probability, our proposed algorithm reduces the missing probability by 27% than the traditional embedded spectrally agile radio protocol for evacuation (ESCAPE) algorithm in the best condition.

• Structural Engineering and Mechanics
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• v.61 no.3
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• pp.359-370
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• 2017

This study presents a particle swarm optimization algorithm integrated with weighted particle concept and improved fly-back technique. The rationale behind this integration is to utilize the affirmative properties of these new terms to improve the search capability of the standard particle swarm optimizer. Improved fly-back technique introduced in this study can be a proper alternative for widely used penalty functions to handle existing constraints. This technique emphasizes the role of the weighted particle on escaping from trapping into local optimum(s) by utilizing a recursive procedure. On the other hand, it guaranties the feasibility of the final solution by rejecting infeasible solutions throughout the optimization process. Additionally, in contrast with penalty method, the improved fly-back technique does not contain any adjustable terms, thus it does not inflict any extra ad hoc parameters to the main optimizer algorithm. The improved fly-back approach, as independent unit, can easily be integrated with other optimizers to handle the constraints. Consequently, to evaluate the performance of the proposed method on solving the truss weight minimization problems with discrete variables, several benchmark examples taken from the technical literature are examined using the presented method. The results obtained are comparatively reported through proper graphs and tables. Based on the results acquired in this study, it can be stated that the proposed method (integrated particle swarm optimizer, iPSO) is competitive with other metaheuristic algorithms in solving this class of truss optimization problems.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.324-333
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• 2013

The purpose of this paper is to improve the efficiency of multi-objective topology optimization using a genetic algorithm (GA) with bar-system representation. We proposed a new GA using an elite initial population obtained from a Solid Isotropic Material with Penalization (SIMP) using a weighted sum method. SIMP with a weighted sum method is one of the most established methods using sensitivity analysis. Although the implementation of the SIMP method is straightforward and computationally effective, it may be difficult to find a complete Pareto-optimal set in a multi-objective optimization problem. In this study, to build a more convergent and diverse global Pareto-optimal set and reduce the GA computational cost, some individuals, with similar topology to the local optimum solution obtained from the SIMP using the weighted sum method, were introduced for the initial population of the GA. The proposed method was applied to a structural topology optimization example and the results of the proposed method were compared with those of the traditional method using standard random initialization for the initial population of the GA.

• Convergence Security Journal
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• v.7 no.2
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• pp.39-47
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• 2007

The scheduling algorithms to provide quality of service (QoS) in broadband convergence network (BcN) are compared and analysed. The main QoS management methods such as traffic classification, traffic processing in the input queue and weighted queueing are first analysed, and then the major scheduling algorithms of round robin, priority and weighted round robin under recently considering for BcN to supply real time multimedia communications are analysed. The simulation results by NS-2 show that the scheduling algorithm with proper weights for each traffic class outperforms the priority algorithm.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.9
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• pp.29-37
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• 1998

In weighted random pattern testing it is an important issue to find the optimal weight sets for achieving a high fault coverage using a small number of weighted random patterns. In this paper, a new weight set optimization algorithm is developed, which can generate the optimal weight sets in an efficient way using the sampling probabilities of deterministic tests patterns. In addition, the simulation based method of finding the proper maximum Hamming distance is presented. Experimental results for ISCAS 85 benchmark circuits prove the effectiveness of the new weight set optimization algorithm and the method of finding the proper maximum Hamming distance.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.141-157
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• 2013

In this paper, we consider the minimization of the total weighted earliness-tardiness penalty of jobs, regarding the partial precedences between jobs. We present an optimal scheduling algorithm in O(n(n+m log m)) where n is the number of jobs and m is the number of partial precedences. In the algorithm, the optimal schedule is constructed iteratively by considering each group of contiguous jobs as a block that is represented by a tree.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.323-328
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• 1998

In this paper, a new input estimation algorithm is proposed for target tracking problem. The unknown target maneuver is approximated by a linear combination of independent time functions and the coefficients are estimated by using a weighted least-squares estimation technique. The proposed algorithm is verified by computer simulation of a realistic two-dimensional tracking problem. The proposed algorithm provides significant improvements in estimation performance over the conventional input estimation techniques based on the constant-input assumption.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.334-340
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• 2002

This paper proposes a self-organizing fuzzy modeling which can create a new hyperplane-shaped cluster by applying multiple regression to input/output data with relatively large fuzzy entropy, add the new cluster to fuzzy rule base and adjust parameters of the fuzzy model in repetition. Tn the coarse tuning, weighted recursive least squared algorithm and fuzzy C-regression model clustering are used and in the fine tuning, gradient descent algorithm is used to adjust parameters of the fuzzy model precisely And learning rates are optimized by utilizing meiosis-genetic algorithm. To check the effectiveness and feasibility of the suggested algorithm, four representative examples for system identification are examined and the performance of the identified fuzzy model is demonstrated in comparison with that of the conventional fuzzy models.

• Journal of Welding and Joining
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• v.15 no.1
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• pp.66-80
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• 1997

This paper describes a newly developed arc-sensing algorithm of seam-tracking for FCA W (flux-cored arc welding) horizontal fillet welding. In this algorithm, arc current and the Weighted-Are-Current (WAC) are used to adjust the position of a weld torch in directions of bead throat and weaving, respectively. The WAC, which is newly devised in this study, means that arc current in the vicinity of weaving end is more emphasized than that in the center of weaving. The reason of this is because there usually exists much noise in the center of weaving due to abrupt change of arc length in case some empty gaps exist in a fillet joint Variance analysis was performed in order to check the effect of weld parameters on arc current and the WAC. As a result, the relationships between tip-to-workpiece distance and arc current, and between weaving offset and the WAC were established.To check "the validity of the algorithm, seam-tracking experiments were performed ;mder various welding condition. The result of experiments showed a satisfactory tracking performance in the presence of empty gaps in a horizontal fillet joint.et joint.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.135-143
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• 2006

PQ(Priority Queue) and WRR(Weighted Round Robin) are the most famous schedulers, however, these schedulers have both points of advantages and disadvantages. In this paper, we propose an algorithm that can be adopted in my kind of scheduling type with making up for weak points of PQ and WRR. The proposed algorithm includes a fuzzy theory in the scheduler to assign priorities dynamically in the DiffServ network. This algorithm produces the control discipline by the fuzzy theory to assign priorities of the Queue effectively with checking the Queue status of each class dynamically under the discipline.