• The Transactions of the Korea Information Processing Society
• /
• v.6 no.8
• /
• pp.2253-2261
• /
• 1999

ACK generates optimized code using the string pattern matching technique in pattern table generator and peephole optimizer. But string pattern matching method is not effective due to the many comparative actions in pattern selection. We designed and implemented the EM intermediate code optimizer using tree pattern matching algorithm composed of EM tree generator, optimization pattern table generator and tree pattern matcher. Tree pattern matching algorithm practices the pattern matching that centering around root node with refer to the pattern table, with traversing the EM tree by top-down method. As a result, compare to ACK string pattern matching methods, we found that the optimized code effected to pattern selection time, and contributed to improved the pattern selection time by about 10.8%.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.4
• /
• pp.505-510
• /
• 2005

The RPO(randomized policy optimizer) algorithm, which utilizes probabilistic policy for the action selection, is a recently developed tool in the area of reinforcement learning, and has been shown to be very successful in several application problems. In this paper, we propose a modified RPO algorithm, whose critic network is adapted via RLS(Recursive Least Square) algorithm. In order to illustrate the applicability of the modified RPO method, we applied the modified algorithm to Kimura's robot and observed very good performance. We also developed a MATLAB-based animation program, by which the effectiveness of the training algorithms on the acceleration or the robot movement were observed.

• Steel and Composite Structures
• /
• v.39 no.1
• /
• pp.81-93
• /
• 2021

Splitting tensile strength (STS) is an important mechanical parameter of concrete. This study offers novel methodologies for the early prediction of this parameter. Artificial neural network (ANN), which is a leading predictive method, is synthesized with two metaheuristic algorithms, namely atom search optimization (ASO) and equilibrium optimizer (EO) to achieve an optimal tuning of the weights and biases. The models are applied to data collected from the published literature. The sensitivity of the ASO and EO to the population size is first investigated, and then, proper configurations of the ASO-NN and EO-NN are compared to the conventional ANN. Evaluating the prediction results revealed the excellent efficiency of EO in optimizing the ANN. Accuracy improvements attained by this algorithm were 13.26 and 11.41% in terms of root mean square error and mean absolute error, respectively. Moreover, it raised the correlation from 0.89958 to 0.92722. This is while the results of the conventional ANN were slightly better than ASO-NN. The EO was also a faster optimizer than ASO. Based on these findings, the combination of the ANN and EO can be an efficient non-destructive tool for predicting the STS.

• Smart Structures and Systems
• /
• v.29 no.5
• /
• pp.677-691
• /
• 2022

Water cycle algorithm (WCA) has been a very effective optimization technique for complex engineering problems. This study employs the WCA for simultaneous prediction of heating load (L_H) and cooling load (L_C) in residential buildings. This algorithm is responsible for optimally tuning a neural network (NN). Utilizing 614 records, the behavior of the L_H and L_C is explored and the captured knowledge is then used to predict for 154 unanalyzed building conditions. Since the WCA is a population-based algorithm, different numbers of the searching agents were tested to find the most optimum configuration. It was observed that the best solution is discovered by 500 agents. A comparison with five newly-developed benchmark optimizers, namely equilibrium optimizer (EO), multi-tracker optimization algorithm (MTOA), slime mould algorithm (SMA), multi-verse optimizer (MVO), and electromagnetic field optimization (EFO) revealed that the WCANN predicts the desired parameters with considerably larger accuracy. Obtained root mean square errors (1.4866, 2.1296, 2.8279, 2.5727, 2.5337, and 2.3029 for the L_H and 2.1767, 2.6459, 3.1821, 2.9732, 2.9616, and 2.6890 for the L_C) indicated that the most reliable prediction was presented by the proposed model. The EFONN, however, provided a more time-effective solution. Lastly, an explicit predictive formula was elicited from the WCANN.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.655-657
• /
• 2021

It is challenging to find breast ultrasound image training dataset to develop an accurate machine learning model due to various regulations, personal information issues, and expensiveness of acquiring the images. However, studies targeting transfer learning for ultrasound breast cancer images classification have not been able to achieve high performance compared to radiologists. Here, we propose an improved transfer learning model for ultrasound breast cancer classification using publicly available dataset. We argue that with a proper combination of ImageNet pre-trained model and optimizer, a better performing model for ultrasound breast cancer image classification can be achieved. The proposed model provided a preliminary test accuracy of 99.5%. With more experiments involving various hyperparameters, the model is expected to achieve higher performance when subjected to new instances.

• KIPS Transactions on Computer and Communication Systems
• /
• v.9 no.3
• /
• pp.45-58
• /
• 2020

In the current trend of increasing network traffic due to the popularization of cloud service and mobile devices, WAN bandwidth is very low compared to LAN bandwidth. In a WAN environment, a WAN optimizer is needed to overcome performance problems caused by transmission protocol, packet loss, and network bandwidth limitations. In this paper, we analyze the data deduplication algorithm of WANProxy, an open source WAN optimizer, and evaluate its performance in terms of network latency and WAN bandwidth. Also, we evaluate the performance of the two-stage compression method of WANProxy and Zstandard. We propose a new method to improve the performance of WANProxy by revising its data deduplication algorithm and evaluate its performance improvement. We perform experiments using 12 data files of Silesia with a data segment size of 2048 bytes. Experimental results show that the average compression rate by WANProxy is 150.6, and the average network latency reduction rates by WANProxy are 95.2% for a 10 Mbps WAN environment and 60.7% for a 100 Mbps WAN environment, respectively. Compared with WANProxy, the two-stage compression of WANProxy and Zstandard increases the average compression rate by 33%. However, it increases the average network latency by 2.1% for a 10 Mbps WAN environment and 5.27% for a 100 Mbps WAN environment, respectively. Compared with WANProxy, our proposed method increases the average compression rate by 34.8% and reduces the average network latency by 13.8% for a 10 Mbps WAN and 12.9% for a 100 Mbps WAN, respectively. Performance analysis results of WANProxy show that its performance improvement in terms of network latency and WAN bandwidth is excellent in a 10Mbps or less WAN environment while superior in a 100 Mbps WAN environment.

• 한국초전도학회:학술대회논문집
• /
• v.16
• /
• pp.55-55
• /
• 2006

• Proceedings of the Korea Concrete Institute Conference
• /
• 1995.04a
• /
• pp.378-384
• /
• 1995

This paper descrides on the economical design of apartment house. * The optimal problems are made by considering the objective function which minimize the construction cost of frame. * The object functions are taken as the codfficient equations of the cost function for a unit area. * Constraints are the design limits defined by the ultimate flexural strength, the ultimate shear strength. the minimum thickness, and the ratio of steel in accordance with ACI 318-89 Code. * Optimization is achieved by optimum nonlinear GINO(General interactive Optimizer)program. In design examples, it is compared with the optimum design results of apartment house and underground parking lot for structural systems.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10b
• /
• pp.879-884
• /
• 1988

For more economical operation of chemical plants, optimal operating conditions are to be set and maintained as far as possible. For this purpose, optimizing control is applied to chemical plants. In this study, a process optimizer composed of a process simulator and an optimization routine using Successive Quadratic Programming as optimization technique is developed and the effect of optimizing control is tested on an example process, and a new process optimization strategy based on modified Jacobian matrix is developed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2003.04a
• /
• pp.3-8
• /
• 2003

In this study, using linear and nonlinear deformation theories and by closed-form analysis and finite difference energy methods, respectively, various buckling load factors are obtained for stiffened laminated composite panel with trapezoidal type stiffeners and various longitudinal length to radius ratios, which are made from Carbon/Epoxy USN 125 prepreg and are simply-supported on four edges under uniaxial compression, and then for them, optimal design analyses are carried out by the nonlinear search optimizer, ADS.