Real-time Discharge Forecasting by Fuzzy Time Series
碩士 === 逢甲大學 === 水利工程與資源保育研究所 === 100 === Fuzzy time series forecasts are often preferable because they take explicitly into account the predictor variability. However, in real world accurate data are not easily collected. Data is often gathered from human experience and knowledge, which can be vague...
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ndltd-TW-100FCU053980122015-10-13T21:27:33Z http://ndltd.ncl.edu.tw/handle/34597825162436852506 Real-time Discharge Forecasting by Fuzzy Time Series 以模糊時間數列進行即時流量預報 Wan-zhen Wu 吳婉甄 碩士 逢甲大學 水利工程與資源保育研究所 100 Fuzzy time series forecasts are often preferable because they take explicitly into account the predictor variability. However, in real world accurate data are not easily collected. Data is often gathered from human experience and knowledge, which can be vague and uncertain. Fuzzy time series is usefull for developing an interval forecasting model which can solve this uncertainty issue. There are many parameters that can impact a fuzzy time series forecast. Regardless of the interval length, universe, defuzzification and building model data are need gives parameters. Therefore, the study will first-order, time-variant, fuzzy time series interval, universe ,different defuzzification method and building model data, in order to obtain the most suitable discharge forecast parameters of fuzzy time series models. In practical applications, when the moment of the actual discharge is the limit value, the different parameters are used to forecast the discharge. Results show that the fuzzy time series model is accurately forecast discharge. Chang-shian Chen 陳昶憲 2012 學位論文 ; thesis 101 zh-TW |
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碩士 === 逢甲大學 === 水利工程與資源保育研究所 === 100 === Fuzzy time series forecasts are often preferable because they take explicitly into account the predictor variability. However, in real world accurate data are not easily collected. Data is often gathered from human experience and knowledge, which can be vague and uncertain. Fuzzy time series is usefull for developing an interval forecasting model which can solve this uncertainty issue.
There are many parameters that can impact a fuzzy time series forecast. Regardless of the interval length, universe, defuzzification and building model data are need gives parameters. Therefore, the study will first-order, time-variant, fuzzy time series interval, universe ,different defuzzification method and building model data, in order to obtain the most suitable discharge forecast parameters of fuzzy time series models. In practical applications, when the moment of the actual discharge is the limit value, the different parameters are used to forecast the discharge. Results show that the fuzzy time series model is accurately forecast discharge.
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Chang-shian Chen |
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Chang-shian Chen Wan-zhen Wu 吳婉甄 |
author |
Wan-zhen Wu 吳婉甄 |
spellingShingle |
Wan-zhen Wu 吳婉甄 Real-time Discharge Forecasting by Fuzzy Time Series |
author_sort |
Wan-zhen Wu |
title |
Real-time Discharge Forecasting by Fuzzy Time Series |
title_short |
Real-time Discharge Forecasting by Fuzzy Time Series |
title_full |
Real-time Discharge Forecasting by Fuzzy Time Series |
title_fullStr |
Real-time Discharge Forecasting by Fuzzy Time Series |
title_full_unstemmed |
Real-time Discharge Forecasting by Fuzzy Time Series |
title_sort |
real-time discharge forecasting by fuzzy time series |
publishDate |
2012 |
url |
http://ndltd.ncl.edu.tw/handle/34597825162436852506 |
work_keys_str_mv |
AT wanzhenwu realtimedischargeforecastingbyfuzzytimeseries AT wúwǎnzhēn realtimedischargeforecastingbyfuzzytimeseries AT wanzhenwu yǐmóhúshíjiānshùlièjìnxíngjíshíliúliàngyùbào AT wúwǎnzhēn yǐmóhúshíjiānshùlièjìnxíngjíshíliúliàngyùbào |
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