• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1261-1269
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• 1999

다층 퍼셉트론은 다양한 응용 분야에 성공적으로 적용되고 있는 대표적인 신경회로망 모델이다. 그러나 다층 퍼셉트론의 학습에서 나타나는 플라토에 기인한 느린 학습 속도와 지역 극소는 실제 응용문제에 적용함에 있어서 가장 큰 문제로 지적되어왔다. 이 문제를 해결하기 위해 여러 가지 다양한 학습알고리즘들이 개발되어 왔으나, 계산의 비효율성으로 인해 실제 문제에는 적용하기 힘든 예가 많은 등, 현재까지 만족할 만한 해결책은 제시되지 못하고 있다. 본 논문에서는 다층퍼셉트론의 베이시스 함수로 사용되는 시그모이드 함수를 보다 일반화된 형태로 정의하여 사용함으로써 학습에 있어서의 플라토를 완화하고, 지역극소에 빠지는 것을 줄이는 접근방법을 소개한다. 본 방법은 기존의 변형된 가중치 수정식을 사용한 학습 속도 향상의 방법들과는 다른 접근 방법을 택함으로써 기존의 방법들과 함께 사용하는 것이 가능하다는 특징을 갖고 있다. 제안하는 방법의 성능을 확인하기 위하여 간단한 패턴 인식 문제들에의 적용 실험 및 기존의 학습 속도 향상 방법을 함께 사용하여 시계열 예측 문제에 적용한 실험을 수행하였고, 그 결과로부터 제안안 방법의 효율성을 확인할 수 있었다. Abstract A multilayer perceptron is the most well-known neural network model which has been successfully applied to various fields of application. Its slow learning caused by plateau and local minima of gradient descent learning, however, have been pointed as the biggest problems in its practical use. To solve such a problem, a number of researches on learning algorithms have been conducted, but it can be said that none of satisfying solutions have been presented so far because the problems such as computational inefficiency have still been existed in these algorithms. In this paper, we propose a new learning approach to minimize the effect of plateau and reduce the possibility of getting trapped in local minima by generalizing the sigmoidal function which is used as the basis function of a multilayer perceptron. Adapting a new approach that differs from the conventional methods with revised updating equation, the proposed method can be used together with the existing methods to improve the learning performance. We conducted some experiments to test the proposed method on simple problems of pattern recognition and a problem of time series prediction, compared our results with the results of the existing methods, and confirmed that the proposed method is efficient enough to apply to the real problems.

• Horticultural Science & Technology
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• v.29 no.5
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• pp.420-432
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• 2011

Population dynamics of greenhouse whitefly, Trialeurodes vaporariorum (Westwood), were modeled and simulated to compare the temperature effects of air and tomato leaf inside greenhouse using DYMEX model simulator (pre-programed module based simulation program developed by CSIRO, Australia). The DYMEX model simulator consisted of temperature dependent development and oviposition modules. The normalized cumulative frequency distributions of the developmental period for immature and oviposition frequency rate and survival rate for adult of greenhouse whitefly were fitted to two-parameter Weibull function. Leaf temperature on reversed side of cherry tomato leafs (Lycopersicon esculentum cv. Koko) was monitored according to three tomato plant positions (top, > 1.6 m above the ground level; middle, 0.9 - 1.2 m; bottom, 0.3 - 0.5 m) using an infrared temperature gun. Air temperature was monitored at same three positions using a Hobo self-contained temperature logger. The leaf temperatures from three plant positions were described as a function of the air temperatures with 3-parameter exponential and sigmoidal models. Data sets of observed air temperature and predicted leaf temperatures were prepared, and incorporated into the DYMEX simulator to compare the effects of air and leaf temperature on population dynamics of greenhouse whitefly. The number of greenhouse whitefly immatures was counted by visual inspection in three tomato plant positions to verify the performance of DYMEX simulation in cherry tomato greenhouse where air and leaf temperatures were monitored. The egg stage of greenhouse whitefly was not counted due to its small size. A significant positive correlation between the observed and the predicted numbers of immature and adults were found when the leaf temperatures were incorporated into DYMEX simulation, but no significant correlation was observed with the air temperatures. This study demonstrated that the population dynamics of greenhouse whitefly was affected greatly by the leaf temperatures, rather than air temperatures, and thus the leaf surface temperature should be considered for management of greenhouse whitefly in cherry tomato grown in greenhouses.