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Your search keyword '"Pan, Wen-Tsao"' showing total 2 results
Start Over Author "Pan, Wen-Tsao" Topic artificial neural networks Topic information technology
2 results on '"Pan, Wen-Tsao"'

1. Study on the performance evaluation of online teaching using the quantile regression analysis and artificial neural network.

Author

Pan, Wen-Tsao, Huang, Chiung-En, and Chiu, Chiung-Lin

Subjects
*ONLINE education, *PERFORMANCE evaluation, *ARTIFICIAL neural networks, *REGRESSION analysis, *INFORMATION technology, *EXPERT systems
Abstract

This paper is totally different than the research design and research method in the related literature for investigating how information technology-based reading and learning process of network distance teaching affects the assessment result in the past, that is, innovative research architecture and process is adopted. Here, quantile regression analysis is applied to the investigation of how the time and frequency of log-in curriculum, browsing teaching material, and curriculum discussion in learning process record affects the final-term assessment result of multimedia design digital teaching material subject. In depth research is done under such research architecture, and it is hoped that how each independent variable affects the final-term assessment result under different quantile can be investigated. In addition, this paper has applied new artificial neural network technology to set up expert system for teacher's assessment result in distance teaching so as to reduce teacher's teaching pressure, moreover, the result can be used as reference by general researchers and scientific education researchers. The research result shows that the use of quantile regression to analyze the influence of different variable on the teacher's final-term assessment result of distance teaching is a feasible way; FOAGRNN model, as compared to other five models, has better forecasting capability. [ABSTRACT FROM AUTHOR]

Published
2016
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2. Mixed modified fruit fly optimization algorithm with general regression neural network to build oil and gold prices forecasting model.

Author

Pan, Wen-Tsao

Subjects
*PETROLEUM product sales & prices, *GOLD sales & prices, *MATHEMATICAL models of forecasting, *ARTIFICIAL neural networks, *CLUSTER analysis (Statistics), *PRICE indexes, *MATHEMATICAL optimization
Abstract

Purpose – When facing a clouded global economy, many countries would increase their gold reserves. On the other hand, oil supply and demand depends on the political and economic situations of oil producing countries and their production technologies. Both oil and gold reserve play important roles in the economic development of a country. The paper aims to discuss this issue. Design/methodology/approach – This paper uses the historical data of oil and gold prices as research data, and uses the historical price tendency charts of oil and gold, as well as cluster analysis, to discuss the correlation between the historical data of oil and gold prices. By referring to the technical index equation of stocks, the technical indices of oil and gold prices are calculated as the independent variable and the closing price as the dependent variable of the forecasting model. Findings – The findings indicate that there is no obvious correlation between the price tendencies of oil and gold. According to five evaluating indicators, the MFOAGRNN forecast model has better forecast ability than the other three forecasting models. Originality/value – This paper explored the correlation between oil and gold prices, and built oil and gold prices forecasting models. In addition, this paper proposes a modified FOA (MFOA), where an escape parameter Δ is added to Si. The findings showed that the forecasting model that combines MFOA and GRNN has the best ability to forecast the closing price of oil and gold. [ABSTRACT FROM AUTHOR]

Published
2014
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