• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2075-2076
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• 2006

In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Backpropagation(BP). The conventional BP does not guarantee that the BP generated through learning has the optimal network architecture. But the proposed GA-based BP enable the architecture to be a structurally more optimized network, and to be much more flexible and preferable neural network than the conventional BP. The experimental results in BP neural network optimization show that this algorithm can effectively avoid BP network converging to local optimum. It is found by comparison that the improved genetic algorithm can almost avoid the trap of local optimum and effectively improve the convergent speed.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.434-439
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• 1994

Recently neural networks leave been proposed as new computational tools for solving constrained optimization problems because of its computational power. In this paper, the shortest path finding algorithm is proposed by rising a Hopfield type neural network. In order to design a Hopfield type neural network, an energy function must be defined at first. To obtain this energy function, the concept of a vector-represented network is introduced to describe the connected path. Through computer simulations, it will be shown that the proposed algorithm works very well in many cases. The local minima problem of a Hopfield type neural network is discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.925-930
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• 2005

In this paper, evolutionary multi-objective selection method of RBF networks structure is considered. The candidates of RBF network structure are encoded into the chromosomes in GAs. Then, they evolve toward Pareto-optimal front defined by several objective functions concerning with model accuracy and model complexity. An ensemble network constructed by such Pareto-optimal models is also considered in this paper. Some numerical simulation results indicate that the ensemble network is much robust for the case of existence of outliers or lack of data, than one selected in the sense of information criteria.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.119-126
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• 1995

The purpose of this study is to develop the technique of energy recovery and energy saving by using the optimization of heat exchanger network synthesis. This article proposes a new method of determining the optimal target of a heat exchanger network synthesis problem of which data feature multiple pinch points. The system separation method we suggest here is to subdivide the original system into independent subsystems with one pinch point. The optimal cost target was evaluated and the original pinch rules at each subsystem were employed. The software developed in this study was applied to the Alko prosess, which is an alcohol production process, for the synthesis of heat exchanger network. It was possible to save about 15% of the total annual cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1144-1158
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• 2016

In this paper, delay-constrained data transmission is considered over error-prone networks. Network coding is deployed for efficient information exchange, and an approximate decoding approach is deployed to overcome potential all-or-nothing problems. Our focus is on determining the cluster size and its impact on approximate decoding performance. Decoding performance is quantified, and we show that performance is determined only by the number of packets. Moreover, the fundamental tradeoff between approximate decoding performance and data transfer rate improvement is analyzed; as the cluster size increases, the data transfer rate improves and decoding performance is degraded. This tradeoff can lead to an optimal cluster size of network coding-based networks that achieves the target decoding performance of applications. A set of experiment results confirms the analysis.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.633-638
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• 2011

In this paper, we consider resource allocation with proportional fairness in the downlink orthogonal frequency division multiple access relay networks, in which relay nodes operate in decode-and-forward mode. A joint optimization problem is formulated for relay selection, subcarrier assignment and power allocation. Since the formulated primal problem is nondeterministic polynomial time-complete, we make continuous relaxation and solve the dual problem by Lagrangian dual decomposition method. A near-optimal solution is obtained using Karush-Kuhn-Tucker conditions. Simulation results show that the proposed algorithm provides superior system throughput and much better fairness among users comparing with a heuristic algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6A
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• pp.511-518
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• 2007

One of the major issues that has to be carefully considered when upgrading current transport network capacity, is network scalability. A novel full-meshed connected ring expansion methodology and planning tool have been proposed. A 3 to 15 node expansion ring has been studied by demonstrating a dramatic system SNR improvement when the proposed planning tool was used. The results are that node output signal and optical SNR have been improved from -16dBm/10dB to +005dBm/21dB by NPOT.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.224-233
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• 1999

The quality of injection molded parts is affected by the variables such as materials, design variables of part and mold, molding machine, and processing conditions. It is difficult to consider all the variables at the same time to predict the quality. In this paper neural network was applied to analyze the relationship between processing conditions and volumetric shrinkage of part. Engineering plastic gear was used for the study, and the learning data was extracted by the simulation software like Moldflow. Results of neural network was good agreement with simulation results. Nonlinear regression model was formulated using the test data of 3,125 obtained from neural network, Optimal processing conditions were calculated to minimize the volumetric shrinkage of molded part by the application of RQP(Recursive Quadratic Programming) algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3110-3125
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• 2014

Network coding improves TCP's performance in lossy wireless networks. However, the complex congestion window evolution of network coded TCP (TCP-NC) makes the analysis of end-to-end throughput challenging. This paper analyzes the evolutionary process of TCP-NC against lossy links. An analytic model is established by applying a two-dimensional Markov chain. With maximum window size, end-to-end erasure rate and redundancy parameter as input parameters, the analytic model can reflect window evolution and calculate end-to-end throughput of TCP-NC precisely. The key point of our model is that by the novel definition of the states of Markov chain, both the number of related states and the computation complexity are substantially reduced. Our work helps to understand the factors that affect TCP-NC's performance and lay the foundation of its optimization. Extensive simulations on NS2 show that the analytic model features fairly high accuracy.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.892-904
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• 2021

An image semantic segmentation model is proposed based on improved ENet network in order to achieve the low accuracy of image semantic segmentation in complex environment. Firstly, this paper performs pruning and convolution optimization operations on the ENet network. That is, the network structure is reasonably adjusted for better results in image segmentation by reducing the convolution operation in the decoder and proposing the bottleneck convolution structure. Squeeze-and-excitation (SE) module is then integrated into the optimized ENet network. Small-scale targets see improvement in segmentation accuracy via automatic learning of the importance of each feature channel. Finally, the experiment was verified on the public dataset. This method outperforms the existing comparison methods in mean pixel accuracy (MPA) and mean intersection over union (MIOU) values. And in a short running time, the accuracy of the segmentation and the efficiency of the operation are guaranteed.