• 제목/요약/키워드: recurrent education

검색결과 97건 처리시간 0.026초

순환신경망 기초 실습 사례 개발 (Development of Basic Practice Cases for Recurrent Neural Networks)

  • 허경
    • 실천공학교육논문지
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    • 제14권3호
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    • pp.491-498
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    • 2022
  • 본 논문에서는 비전공자들을 위한 교양과정으로, 기초 순환신경망 과목 커리큘럼을 설계하는데 필수적으로 요구되는 순환신경망 SW 실습 사례를 개발하였다. 개발된 SW 실습 사례는 순환신경망의 동작원리를 이해시키는 데 초점을 두고, 시각화된 전체 동작 과정을 확인할 수 있도록 스프레드시트를 사용하였다. 개발된 순환신경망 실습 사례는 지도학습 방식의 텍스트완성 훈련데이터 생성, 입력층, 은닉층, 상태층(컨텍스트 노드) 그리고 출력층을 차례대로 구현하고, 텍스트 데이터에 대해 순환신경망의 성능을 테스트하는 것으로 구성되었다. 본 논문에서 개발한 순환신경망 실습사례는 다양한 문자 수를 갖는 단어를 자동 완성한다. 제안한 순환신경망 실습사례를 활용하여, 한글 또는 영어 단어를 구성하는 최대 문자 수를 다양하게 확장하여 자동 완성하는 인공지능 SW 실습 사례를 만들 수 있다. 따라서, 본 순환신경망 기초 실습 사례의 활용도가 높다고 할 수 있다.

SOME THEOREMS ON RECURRENT MANIFOLDS AND CONFORMALLY RECURRENT MANIFOLDS

  • Jaeman Kim
    • Korean Journal of Mathematics
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    • 제31권2호
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    • pp.139-144
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    • 2023
  • In this paper, we show that a recurrent manifold with harmonic curvature tensor is locally symmetric and that an Einstein and conformally recurrent manifold is locally symmetric. As a consequence, Einstein and recurrent manifolds must be locally symmetric. On the other hand, we have obtained some results for a (conformally) recurrent manifold with parallel vector field and also investigated some results for a (conformally) recurrent manifold with concircular vector field.

Recurrent Neural Network을 이용한 플로우 기반 네트워크 트래픽 분류 (Flow based Network Traffic Classification Using Recurrent Neural Network)

  • 임현교;김주봉;허주성;권도형;한연희
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2017년도 추계학술발표대회
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    • pp.835-838
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    • 2017
  • 최근 다양한 네트워크 서비스와 응용들이 생겨나면서, 네트워크상에 다양한 네트워크 트래픽이 발생하고 있다. 이로 인하여, 네트워크에 불필요한 네트워크 트래픽도 많이 발생하면서 네트워크 성능에 저하를 발생 시키고 있다. 따라서, 네트워크 트래픽 분류를 통하여 빠르게 제공되어야 하는 네트워크 서비스를 빠르게 전송 할 수 있도록 각 네트워크 트래픽마다의 분류가 필요하다. 본 논문에서는 Deep Learning 기법 중 Recurrent Neural Network를 이용한 플로우 기반의 네트워크 트래픽 분류를 제안한다. Deep Learning은 네트워크 관리자의 개입 없이 네트워크 트래픽 분류를 할 수 있으며, 이를 위하여 네트워크 트래픽을 Recurrent Neural Network에 적합한 데이터 형태로 변환한다. 변환된 데이터 세트를 이용하여 훈련시킴으로써 네트워크 트래픽을 분류한다. 본 논문에서는 훈련시킨 결과를 토대로 비교 분석 및 평가를 진행한다.

ON GENERALIZED Z-RECURRENT MANIFOLDS

  • De, Uday Chand;Pal, Prajjwal
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제24권2호
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    • pp.53-68
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    • 2017
  • The object of the present paper is to study generalized Z-recurrent manifolds. Some geometric properties of generalized Z-recurrent manifolds have been studied under certain curvature conditions. Finally, we give an example of a generalized Z-recurrent manifold.

재가 여성노인에서 1회 낙상군과 반복낙상군의 낙상관련 특성 비교연구 (Comparative Study on Fall Related Characteristics between Single and Recurrent Falls in Community-Dwelling Older Women)

  • 박형숙;장랑;박경연
    • 성인간호학회지
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    • 제20권6호
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    • pp.905-916
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    • 2008
  • Purpose: The purpose of this study was to identify the influencing factors on the single and recurrent falls in community-dwelling older women. Methods: Seventy eight volunteers aged over 65 were included in the study. The participants experienced at least one fall within the past one year. Data were measured on each participant from May 2007 to September 2007, collected using structured researcher-administered sheets and measuring their physical strengths and analyzed by descriptive statistics, t-test, chi-square test, Mann-Whitney U test and logistic regression analysis. Results: The prevalence of recurrent falls were 53.8%. The level of education(Z = -2.455, p = .014) and the presence of spouse($x^2$ = 4.843, p = .044) showed significant differences between the single-fall group and the recurrent-fall group in the study. Significantly predicting factor on the recurrent falls was the level of education and the variable explained 20.1% of variants in the occurrence of recurrent falls. Conclusion: Although a variety of factors affected the single fall in the elderly women, the level of education and the presence of spouse proved to be the significant factors in their recurrent falls. These factors proven to be significant as the result of this should be reflected in the development of effective programs for preventing the elderly from recurrent falls.

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SOME NOTES ON NEARLY COSYMPLECTIC MANIFOLDS

  • Yildirim, Mustafa;Beyendi, Selahattin
    • 호남수학학술지
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    • 제43권3호
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    • pp.539-545
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    • 2021
  • In this paper, we study some symmetric and recurrent conditions of nearly cosymplectic manifolds. We prove that Ricci-semisymmetric and Ricci-recurrent nearly cosymplectic manifolds are Einstein and conformal flat nearly cosymplectic manifold is locally isometric to Riemannian product ℝ × N, where N is a nearly Kähler manifold.

ON GENERALIZED RICCI-RECURRENT TRANS-SASAKIAN MANIFOLDS

  • Kim, Jeong-Sik;Prasad, Rajendra;Tripathi, Mukut-Mani
    • 대한수학회지
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    • 제39권6호
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    • pp.953-961
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    • 2002
  • Generalized Ricci-recurrent trans-Sasakian manifolds are studied. Among others, it is proved that a generalized Ricci-recurrent cosymplectic manifold is always recurrent Generalized Ricci-recurrent trans-Sasakian manifolds of dimension $\geq$ 5 are locally classified. It is also proved that if M is one of Sasakian, $\alpha$-Sasakian, Kenmotsu or $\beta$-Kenmotsu manifolds, which is gener-alized Ricci-recurrent with cyclic Ricci tensor and non-zero A (ξ) everywhere; then M is an Einstein manifold.

Nonlinear Backstepping Control of SynRM Drive Systems Using Reformed Recurrent Hermite Polynomial Neural Networks with Adaptive Law and Error Estimated Law

  • Ting, Jung-Chu;Chen, Der-Fa
    • Journal of Power Electronics
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    • 제18권5호
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    • pp.1380-1397
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    • 2018
  • The synchronous reluctance motor (SynRM) servo-drive system has highly nonlinear uncertainties owing to a convex construction effect. It is difficult for the linear control method to achieve good performance for the SynRM drive system. The nonlinear backstepping control system using upper bound with switching function is proposed to inhibit uncertainty action for controlling the SynRM drive system. However, this method uses a large upper bound with a switching function, which results in a large chattering. In order to reduce this chattering, a nonlinear backstepping control system using an adaptive law is proposed to estimate the lumped uncertainty. Since this method uses an adaptive law, it cannot achiever satisfactory performance. Therefore, a nonlinear backstepping control system using a reformed recurrent Hermite polynomial neural network with an adaptive law and an error estimated law is proposed to estimate the lumped uncertainty and to compensate the estimated error in order to enhance the robustness of the SynRM drive system. Further, the reformed recurrent Hermite polynomial neural network with two learning rates is derived according to an increment type Lyapunov function to speed-up the parameter convergence. Finally, some experimental results and a comparative analysis are presented to verify that the proposed control system has better control performance for controlling SynRM drive systems.