• 전자공학회논문지C
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• 제34C권6호
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• pp.71-78
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• 1997

In this paper, a new neural network training algorithm will be devised for function approximator with good generalization characteristics and tested with the time series prediction problem using santaFe competition data sets. To enhance the generalization ability a constraint term of hidden neuraon activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. A hybrid learning algorithm of the error-back propagation and Hebbian learning algorithm with weight decay constraint will be naturally developed by the steepest decent algorithm minimizing the proposed cost function without much increase of computational requriements.

• Industrial Engineering and Management Systems
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• 제12권3호
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• pp.244-253
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• 2013

In industries, shipping is an important issue in improving the forecasting accuracy of sales. This paper introduces a hybrid method and plural methods are compared. Focusing the equation of exponential smoothing method (ESM) that is equivalent to (1, 1) order autoregressive-moving-average (ARMA) model equation, a new method of estimating the smoothing constant in ESM had been proposed previously by us which satisfies minimum variance of forecasting error. Generally, the smoothing constant is selected arbitrarily. However, this paper utilizes the above stated theoretical solution. Firstly, we make estimation of ARMA model parameter and then estimate the smoothing constant. Thus, theoretical solution is derived in a simple way and it may be utilized in various fields. Furthermore, combining the trend removing method with this method, we aim to improve forecasting accuracy. This method is executed in the following method. Trend removing by the combination of linear and 2nd order nonlinear function and 3rd order nonlinear function is executed to the original production data of two kinds of bread. Genetic algorithm is utilized to search the optimal weight for the weighting parameters of linear and nonlinear function. For comparison, the monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non-monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful for the time series that has various trend characteristics and has rather strong seasonal trend. The effectiveness of this method should be examined in various cases.

• 한국인공지능학회지
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• 제11권1호
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• pp.17-24
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• 2023

With the continuous growth in the amount of data collected and analyzed, deep learning has become increasingly popular for extracting meaningful insights from various fields. However, hardware limitations pose a challenge for achieving meaningful results with limited data. To address this challenge, this paper proposes an algorithm that leverages the characteristics of convolutional neural networks (CNNs) to reduce the size of image datasets by 20% through smoothing and shrinking the size of images using color elements. The proposed algorithm reduces the learning time and, as a result, the computational load on hardware. The experiments conducted in this study show that the proposed method achieves effective learning with similar or slightly higher accuracy than the original dataset while reducing computational and time costs. This color-centric dataset construction method using image smoothing techniques can lead to more efficient learning on CNNs. This method can be applied in various applications, such as image classification and recognition, and can contribute to more efficient and cost-effective deep learning. This paper presents a promising approach to reducing the computational load and time costs associated with deep learning and provides meaningful results with limited data, enabling them to apply deep learning to a broader range of applications.

• 정보처리학회논문지C
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• 제11C권7호
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• pp.1009-1022
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• 2004

스무딩은 가변 비트율의 비디오 데이터를 고정 비트율로 변환하는 전송 계획이다. 이를 위한 스무딩 알고리즘에는 CBA, MCBA, MVBA, PCRTT, e-PCRTT등이 있으며, PCRTT 알고리즘을 개선한 e-PCRTT 알고리즘에서는 전송률 변화 횟수사 주어지고 런의 크기가 일정하다. 이는 불필요한 전송률의 변화를 필요로 하고, 또한 버퍼 크기가 작은 경우에는 QoS를 보장하지 못할 수 도 있다. 본 논문에서는 이러한 e-PCRTT 알고리즘의 단점을 해결하기 위해 전송률 변화 횟수에 대한 제한이 없고, 런의 크기가 가변적인 스무딩 알고리즘을 제안한다. 제안 알고리즘의 성능은 e-PCRTT 알고리즘을 포함한 다른 알고리즘들과 전송률 변화 횟수, QoS를 유지하기 위한 버퍼 크기 등과 같은 다양한 평가 요소들로 비교하여 우수함을 보였다.

• 사물인터넷융복합논문지
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• 제7권2호
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• pp.47-53
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• 2021

IoT(Internet of Things) 환경에서 한정된 대역폭을 갖는 서버에서 저장된 비디오 데이터를 많은 클라이언트들에게 전송하기 위해서는 전송률 변화 횟수, 첨두 전송률, 전송률 변화량 등의 요소를 고려하여 전송 계획을 세워야 한다. 이 전송 계획을 스무딩이라고 하며 전송률 증가 횟수를 최소화하는 CBA, 전송률 변화횟수를 최소화하는 MCBA, 전송률 변화량을 최소화하기 위한 MVBA 등이 있다. 본 연구에서는 평균 전송률을 최소화하기 위해 제안된 알고리즘[16]에 대한 성능을 평가하기 위해, 제안된 알고리즘과 기존 스무딩 알고리즘들에서의 첨두 전송률, 전송률 변화횟수, 전송률 증가횟수, 전송률 변화량, 첨두 전송률 이용률, 평균 전송률을 다양한 비디오 데이터와 버퍼 크기로 비교한다. 평가 결과 제안 알고리즘은 평균 전송률이 가장 낮은 전송 계획을 세움으로써, 서버의 한정된 네트워크 자원의 효율적인 사용에 도움을 준다.

• Current Optics and Photonics
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• 제2권1호
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• pp.7-14
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• 2018

As a sophisticated detection technology, LIDAR has been widely employed to probe low-altitude windshear. Due to the drawbacks of the traditional ramp algorithm, the alarm accuracy of the LIDAR has not been satisfactory. Aiming at settling this matter, a novel method is proposed on the basis of improved signal smoothing and second windshear detection, which essentially acts as a combination of ramp algorithm and segmentation approach, involving the human factor as well as signal fluctuations. Experiments on the real and artificial signals verify our approach.

• 제어로봇시스템학회논문지
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• 제10권9호
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• pp.809-815
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• 2004

Researches on mobile robots have been mainly focused on the autonomous navigation and a lot of interesting results have been published so far. Most of applications are, however, fancy, unpractical, and very expensive to be used for 'UN-expensive' purpose. Well-known soccer robot may be an example of unpractical application. Un-autonomous mobile robot has, however, potential for a lot of practical applications. Especially, tele-operation of the un-autonomous mobile robot may the central issue of research. Major research topics for the tele-operated un-autonomous mobile robot include development of a force reflecting joystick for tele-operation and development of a sophisticated algorithm for smooth tele-operation. A new concept named fuzzy command smoothing algorithm is proposed in this paper in order to provide smooth motion to a tele-operated mobile robot. It gives smooth motion command to the mobile robot from possibly abrupt quick turn motion command of the joystick using fuzzy logic. Simulation results verify the usefulness of the proposed algorithm.

• 한국컴퓨터산업학회논문지
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• 제3권8호
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• pp.1027-1038
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• 2002

인터넷 기술의 발전은 멀티미디어 데이터 서비스에 대한 관심을 증가시키고 있는데, 제한된 자원을 갖고 서비스를 할 때에는 QoS(Quality of Service)가 보장되어야 한다. 그러나 제한된 대역폭 내에서 전송량의 급격한 증가와 멀티미디어 서비스 사용자 수의 증가는 QoS의 보장과 네트워크 자원의 이용률을 저하시킬 수 있다. 이를 해결하기 위한 스무딩 기법은 가변 비트율(VBR:Variable Bit Rate)을 가진 비디오 스트림을 전송할 때 전송량의 급격한 증가가 발생되는 버스트(Burst)를 방지하기 위한 방법이다. 본 논문에서는 가변 비트율을 가진 멀티미디어 데이터를 전송할 때 MPEG의 특성을 이용하는 효율적인 스무딩 알고리즘을 제안하며, 제안한 알고리즘과 기존 스무딩 알고리즘을 다양한 환경에서 비교 분석하였다.

• 대한의용생체공학회:의공학회지
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• 제22권4호
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• pp.311-319
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• 2001

Statistical reconstruction methods in the context of a Bayesian framework have played an important role in emission tomography since they allow to incorporate a priori information into the reconstruction algorithm. Given the ill-posed nature of tomographic inversion and the poor quality of projection data, the Bayesian approach uses regularizers to stabilize solutions by incorporating suitable prior models. In this work we show that, while the quantitative performance of the standard filtered backprojection (FBP) algorithm is not as good as that of Bayesian methods, the application of spline-regularized smoothing to the sinogram space can make the FBP algorithm improve its performance by inheriting the advantages of using the spline priors in Bayesian methods. We first show how to implement the spline-regularized smoothing filter by deriving mathematical relationship between the regularization and the lowpass filtering. We then compare quantitative performance of our new FBP algorithms using the quantitation of bias/variance and the total squared error (TSE) measured over noise trials. Our numerical results show that the second-order spline filter applied to FBP yields the best results in terms of TSE among the three different spline orders considered in our experiments.

• 경영과학
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• 제21권2호
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• pp.79-91
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• 2004

In industrial production settings, scheduling problems for detailed day-to-day operations are often ordeals to production practitioners. For those who have scheduling experiences with the Gantt Chart, the job oriented heuristic scheduling has illustrated its merits in solving practically large scale scheduling problems. It schedules all operations of a job within a finite capacity before considering the next job. In this paper, we Introduce the LSB (load smoothing backward) scheduling algorithm for the job oriented heuristic scheduling. Through a computer experiment in a hypothetical setting, we make a performance comparison of LSB scheduling algorithm with existing algorithms and also suggest a guideline for selecting the suitable algorithm for certain industrial settings.