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이일병,임현정 대한교통학회 1992 대한교통학회지 Vol.10 No.3
The objective of this research is to develop a traffic accident forecasting model using traffic accident data in pusan from 1963 to 1991 and then to make short-term forecasts('93~'94) of traffic accidents in pusan. In this research, several forecasting models are developed. They include a multiple regression model, a time-series ARIMA model, a Logistic curve model, and a Gompertz curve model. Among them, the model which shows the most significance in forecasting accuracy is selected as the traffic accident forecasting model. The results of this research are as followings. 1. The existing model such as Smeed model which was developed for foreign countries shows only 47.8% explanation for traffic accident deaths in Korea. 2. A nonliner regression model ($R^2$=0.9432) and a Logistic curve model are appeared to be th gest forecasting models for the number of traffic accidents, and a Logistic curve model shows th most significance in predicting the accident deaths and injuries. 3. The forecasting figures of the traffic accidents in pusan are as followings: . In 1993, 31, 180 accidents are predicted to happen, and 430 persons are predicted to be deaths and 29, 680 persons are predicated to be injuries. . In 1994, 33, 710 accidents are predicted to happen, and 431.persons are predicted to be deat! and 30, 510 persons are predicted to be injuried. Therefore, preventive measures against traffic accidents are certainly required.
망막 외망층의 국부회로에 대한 신경망 모델 및 컴퓨터 모의실험
이일병 대한의용생체공학회 1988 의공학회지 Vol.9 No.1
This paper describes a neural network modelling of a vertebrate retina using a discrete-time and discrete-space approach based on neuro-anatomical data, and the computer simulations of the model which approximate the frog/amphibian negro-physiological data. It then compares them and describes how such a model can be beneficially used for confirming the hypothesis of a given neural system and further predict yet unknown experimental data.
이일병 연세대학교 대학원 1995 延世論叢 Vol.31 No.1
Abstract Neural Networks have gotten much attention from many scientists and engineers in recent years. Especially image processing, one of the inverse problems, takes many advantages of neural networks which are tolerant to noises and have adaptability. But computer simulation of neural network takes much time because von Neumann computer cannot support the full parallelism of neural networks. We need special hardware implemetation for neural networks. And one of the hardware implementation methods is VLSI chip. The study on the neuro-chip have been started many years ago abroad and they made some commercial neuro-chips. Some neuro-chops were made for retina model which was suited for pre-processing of visual information processing. But there are few tries for making neuro-chips in Korea. Some research institutes started studying on the neuro-chips. And we have possibility to have a commercial neuro -chips in a few years. This paper explains about the human image processing and the algorithms for computer image processing. And we also show some vision chips made abroad and some neuro-chips made in Korea.