Studies of the Catalyst and Heavy Oil

碩士 === 輔仁大學 === 統計資訊學系應用統計碩士在職專班 === 102 === This study aims to identify the heavy oil refining process five parameters: refining capacity, the reactor temperature, iron content, sodium content, viscosity influence on the life of the catalytic cracker. In research methods, using univariate ARIMA mod...

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Main Authors: Po-Chang,Chien, 簡伯錩
Other Authors: Ben-Chang,Shia
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/27546906349256377740
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spelling ndltd-TW-102FJU015060032016-02-28T04:20:21Z http://ndltd.ncl.edu.tw/handle/27546906349256377740 Studies of the Catalyst and Heavy Oil 重油成份與觸媒裂解性能之可行性研究 Po-Chang,Chien 簡伯錩 碩士 輔仁大學 統計資訊學系應用統計碩士在職專班 102 This study aims to identify the heavy oil refining process five parameters: refining capacity, the reactor temperature, iron content, sodium content, viscosity influence on the life of the catalytic cracker. In research methods, using univariate ARIMA model to predict reactor pressure differential trends, and the various input variables and output variables conversion function ARIMA transfer function model predictive models and causality. This study by the univariate ARIMA model predictive capability with moderate R2 value of 0.936, can be regarded as an excellent prediction model; each transfer function model has the same reach of the R2 value greater than 0.936. In addition to sodium no significant effect on the amount of differential pressure in the reactor, the remaining four input variables Individually significant impact on output variables, and input variables most influence upon the number of current or delayed. Ben-Chang,Shia Kuang-Chao,Chang 謝邦昌 張光昭 2014 學位論文 ; thesis 51 zh-TW
collection NDLTD
language zh-TW
format Others
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description 碩士 === 輔仁大學 === 統計資訊學系應用統計碩士在職專班 === 102 === This study aims to identify the heavy oil refining process five parameters: refining capacity, the reactor temperature, iron content, sodium content, viscosity influence on the life of the catalytic cracker. In research methods, using univariate ARIMA model to predict reactor pressure differential trends, and the various input variables and output variables conversion function ARIMA transfer function model predictive models and causality. This study by the univariate ARIMA model predictive capability with moderate R2 value of 0.936, can be regarded as an excellent prediction model; each transfer function model has the same reach of the R2 value greater than 0.936. In addition to sodium no significant effect on the amount of differential pressure in the reactor, the remaining four input variables Individually significant impact on output variables, and input variables most influence upon the number of current or delayed.
author2 Ben-Chang,Shia
author_facet Ben-Chang,Shia
Po-Chang,Chien
簡伯錩
author Po-Chang,Chien
簡伯錩
spellingShingle Po-Chang,Chien
簡伯錩
Studies of the Catalyst and Heavy Oil
author_sort Po-Chang,Chien
title Studies of the Catalyst and Heavy Oil
title_short Studies of the Catalyst and Heavy Oil
title_full Studies of the Catalyst and Heavy Oil
title_fullStr Studies of the Catalyst and Heavy Oil
title_full_unstemmed Studies of the Catalyst and Heavy Oil
title_sort studies of the catalyst and heavy oil
publishDate 2014
url http://ndltd.ncl.edu.tw/handle/27546906349256377740
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