• Title/Summary/Keyword: neural net

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Forecasting uranium prices: Some empirical results

  • Pedregal, Diego J.
    • Nuclear Engineering and Technology
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    • v.52 no.6
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    • pp.1334-1339
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    • 2020
  • This paper presents an empirical and comprehensive forecasting analysis of the uranium price. Prices are generally difficult to forecast, and the uranium price is not an exception because it is affected by many external factors, apart from imbalances between demand and supply. Therefore, a systematic analysis of multiple forecasting methods and combinations of them along repeated forecast origins is a way of discerning which method is most suitable. Results suggest that i) some sophisticated methods do not improve upon the Naïve's (horizontal) forecast and ii) Unobserved Components methods are the most powerful, although the gain in accuracy is not big. These two facts together imply that uranium prices are undoubtedly subject to many uncertainties.

A Study on the Korean Text-to-Speech Using Demisyllable Units (반음절단위를 이용한 한국어 음성합성에 관한 연구)

  • Yun, Gi-Sun;Park, Sung-Han
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.27 no.10
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    • pp.138-145
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    • 1990
  • This paper present a rule-based speech synthesis method for improving the naturalness of synthetic speech and using the small data base based on demisyllable units. A 12-pole Linear Prediction Coding method is used to analyses demisyllable speech signals. A syllable and vowel concatenation rule is developed to improve the naturalness and intelligibility of the synthetic speech. in addiion, phonological structure transform rule using neural net and prosody rules are applied to the synthetic speech.

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An Implementation of Traffic Accident Detection System at Intersection based on Image and Sound (영상과 음향 기반의 교차로내 교통사고 검지시스템의 구현)

  • 김영욱;권대길;박기현;이경복;한민홍;이형석
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.6
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    • pp.501-509
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    • 2004
  • The frequency of car accidents is very high at the intersection. Because of the state of a traffic signal, quarrels happen after accidents. At night many cars run away after causing an accident. In this case, accident analyses have been conducted by investigating evidences such as eyewitness accounts, tire tracks, fragments of the car or collision traces of the car. But these evidences that don't have enough objectivity cause an error in judgment. In the paper, when traffic accidents happen, the traffic accident detection system that stands on the basis of images and sounds detects traffic accidents to acquire abundant evidences. And, this system transmits 10 seconds images to the traffic center through the wired net and stores images to the Smart Media Card. This can be applied to various ways such as accident management, accident DB construction, urgent rescue after awaring the accident, accident detection in tunnel and in inclement weather.

Comparative Analysis of Models used to Predict the Temperature Decreases in the Steel Making Process using Soft Computing Techniques (철강 생산 공정에서 Soft Computing 기술을 이용한 온도하락 예측 모형의 비교 연구)

  • Kim, Jong-Han;Seong, Deok-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.2
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    • pp.173-178
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    • 2007
  • This paper is to establish an appropriate model for predicting the temperature decreases in the batch transferred from the refining process to the caster in steel-making companies. Mathematical modeling of the temperature decreases between the processes is difficult, since the reaction mechanism by which the temperature changes in a molten steel batch is dynamic, uncertain and complex. Three soft computing techniques are examined using the same data, namely the multiple regression, fuzzy regression, and neural net (NN) models. To compare the accuracy of these three models, a limited number of input variables are selected from those variables significantly affecting the temperature decrease. The results show that the difference in accuracy between the three models is not statistically significant. Nonetheless, the NN model is recommended because of its adaptive ability and robustness. The method presented in this paper allows the temperature decrease to be predicted without requiring any precise metallurgical knowledge.

The Development of Automatic Inspection System for Flaw Detection in Welding Pipe (배관용접부 결함검사 자동화 시스템 개발)

  • Yoon Sung-Un;Song Kyung-Seok;Cha Yong-Hun;Kim Jae-Yeol
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.15 no.2
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    • pp.87-92
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    • 2006
  • This paper supplements shortcoming of radioactivity check by detecting defect of SWP weld zone using ultrasonic wave. Manufacture 2 stage robot detection systems that can follow weld bead of SWP by method to detect weld defects of SWP that shape of weld bead is complex for this as quantitative. Also, through signal processing ultrasonic wave defect signal system of GUI environment that can grasp easily existence availability of defect because do videotex compose. Ultrasonic wave signal of weld defects develops artificial intelligence style sightseeing system to enhance pattern recognition of weld defects and the classification rate using neural net. Classification of weld defects that do fan Planar defect and that do volume defect of by classify.

Comparison of Deep-Learning Algorithms for the Detection of Railroad Pedestrians

  • Fang, Ziyu;Kim, Pyeoungkee
    • Journal of information and communication convergence engineering
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    • v.18 no.1
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    • pp.28-32
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    • 2020
  • Railway transportation is the main land-based transportation in most countries. Accordingly, railway-transportation safety has always been a key issue for many researchers. Railway pedestrian accidents are the main reasons of railway-transportation casualties. In this study, we conduct experiments to determine which of the latest convolutional neural network models and algorithms are appropriate to build pedestrian railroad accident prevention systems. When a drone cruises over a pre-specified path and altitude, the real-time status around the rail is recorded, following which the image information is transmitted back to the server in time. Subsequently, the images are analyzed to determine whether pedestrians are present around the railroads, and a speed-deceleration order is immediately sent to the train driver, resulting in a reduction of the instances of pedestrian railroad accidents. This is the first part of an envisioned drone-based intelligent security system. This system can effectively address the problem of insufficient manual police force.

Adaptive Thesaurus using a Neural Network (신경망을 이용한 적응형 시소러스)

  • Choe, Jong-Pil;Choe, Myeong-Bok;Kim, Min-Gu
    • Journal of KIISE:Software and Applications
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    • v.27 no.12
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    • pp.1211-1218
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    • 2000
  • 정보검색 분야에서 시소러스 용어와 용어 사이의 관계를 나타내어, 질의어와 검색될 정보 사이에 존재하는 용어적 차이를 줄이는데 사용될 수 있다. 시소러스를 사용하는 방법 중 진보된 것은 용어 사이의 관계에 가중치를 주어, 소위 스프레딩 엑티베이션 방법을 이용하여 주어진 용어에서 다른 용어들 사이의 유사성을 측정하여 이를 검색에 이용한다. 그러나, 이러한 방법은 가중치를 어떻게 할당하느냐에 따라 그 결과가 달라지는 문제점이 발생한다. 본 논문에서는 시소러스의 가중치를 사용자의 검색된 정보에 대한 적합성 반응에 근거하여 조절할 수 있는 신경망 기반 시소러스를 제안한다. 제안된 시소러스의 타당성을 위하여 프로토타입의 시소러스를 WordNet으로부터 추출하여 실험하였으며, 그 결과로 recall-precision 값이 향상됨을 보였다.

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An Automatic Classification System for Hanmail Net Questions Using Multiple Neural Networks (다중 신경망을 이용한 한메일넷 질의 자동분류 시스템)

  • 이지행;조성배
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04b
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    • pp.232-234
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    • 2000
  • 최근들어 정보의 양이 날로 방대해 짐에 따라 이를 자동으로 분류해 줄 수 있는 무서 자동분류의 중요성이 널리 인식되고 있다. 문서 자동분류는 새로운 문서를 미리 정의된 부류로 대응시키는 일련의 작업을 말하며, 각종 패턴인식 기법들을 이용하여 시도되고 있다. 본 논문에서는 수많은 사용자들의 질의들을 분류하여 자동으로 응답하는 시스템에 적용할 수 있는 자동 질의 분류시스템을 제안한다. 실험은 500만명 이상이 사용하고 있는 한메일넷의 실제 사용자 질의를 수집하여 수행하였으며, 자동분류 방법으로는 다중 신경망을 이용하였다. 또한 효율적인 특징추출 기법과 결과 결합방법을 적용하여 분류의 정확율을 높이고자 하였다. 2204개의 실제 질의메일에 대한 실험결과, 91.1%까지의 정확율을 얻어 제안한 시스템이 실제 한메일넷의 자동응답 시스템에 효과적으로 적용될 수 있음을 알 수 있었다.

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A Design of Multilayer Perceptron for Camera Calibration

  • Do, Yong-Tae
    • Journal of Sensor Science and Technology
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    • v.11 no.4
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    • pp.239-246
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    • 2002
  • In this paper a new design of multi-layer perceptron(MLP) for camera calibration is proposed. Most existing techniques determine a transformation from 3D spatial points to their image points and camera parameters are tried to be estimated from the transformation. The technique proposed here, on the other hand, determines rays of sight uniquely from image points and parameters are estimated from the relationship using an MLP. By this approach projection and back-projection can be done more straightforwardly. Being based on a geometric model, a network design process becomes less ambiguous, which is a clear merit compared to other neural net based techniques. An MLP designed according to the technique proposed showed fast and stable learning in tests under various conditions.

Optical neural-net analog-to-digital converter (광 신경망 아날로그-디지탈 변환기)

  • Jang, Ju-Seog;Shin, Sang-Yung;Lee, Soo-Young
    • Proceedings of the KIEE Conference
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    • 1988.07a
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    • pp.414-417
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    • 1988
  • 신경회로를 모방한 병렬 아날로그-디지탈 변환기를 설계하고 광학적으로 구현하였다. 이 회로의 동작 원리는 주어진 입력 아날로그 값에 대해 출력 bit 들의 디지털 값을 동시에 추정하는 것으로 $2^{N}$ 단계의 구분을 위해서 N개의 단위 소자가 필요하다. 에너지 최소화 방법에 의해 설계된 신경망 아날로그-디지털 변환기와 비교해 볼 때 회로의 구조가 단순하고 출력이 회로의 초기 상태에 관계없이 주어진 입력에 의해 결정된다.

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