Application of Support Vector Machine (SVM) to Forecast Climate and Consumption Intention-In a restaurant in the northern Case

碩士 === 國立臺中科技大學 === 資訊工程系碩士班 === 106 === In this study, we adopt support vector machine (SVM) to predict the restaurant sales volume according to the weather information. With climate-related open data of the Central Weather Bureau including the minimum temperature, maximum temperature, average temp...

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Bibliographic Details
Main Authors:	Yu-Ling Liu, 劉育玲
Other Authors:	陳同孝
Format:	Others
Language:	zh-TW
Published:	2018
Online Access:	http://ndltd.ncl.edu.tw/handle/xv86uc

id	ndltd-TW-106NTTI5392001
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spelling	ndltd-TW-106NTTI53920012019-05-16T00:22:32Z http://ndltd.ncl.edu.tw/handle/xv86uc Application of Support Vector Machine (SVM) to Forecast Climate and Consumption Intention-In a restaurant in the northern Case 應用支援向量機(SVM)於氣候與消費意願之預測分析-以北部某餐廳為例 Yu-Ling Liu 劉育玲碩士國立臺中科技大學資訊工程系碩士班 106 In this study, we adopt support vector machine (SVM) to predict the restaurant sales volume according to the weather information. With climate-related open data of the Central Weather Bureau including the minimum temperature, maximum temperature, average temperature, average rainfall, wind speed, maximum ten minutes, the maximum instantaneous wind, pressure, humidity, average rainfall for several days and sunshine hours, those weather information are used as the attributes of LibSVM to run the analysis of sales volume prediction. The number of monthly sales volume of the restaurant from July of 2014 to June of 2017 are collected from the restaurant in Keelung by combining the weather information from Central Weather Burea as the experimental data for the prediction model. The results show that support vector machines can accurately predict the weather information for the sales volume of the restaurant. The results can help the restaurant owner to plan good marketing campaigns and reduce inventory costs. 陳同孝謝俊宏 2018 學位論文 ; thesis 34 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 國立臺中科技大學 === 資訊工程系碩士班 === 106 === In this study, we adopt support vector machine (SVM) to predict the restaurant sales volume according to the weather information. With climate-related open data of the Central Weather Bureau including the minimum temperature, maximum temperature, average temperature, average rainfall, wind speed, maximum ten minutes, the maximum instantaneous wind, pressure, humidity, average rainfall for several days and sunshine hours, those weather information are used as the attributes of LibSVM to run the analysis of sales volume prediction. The number of monthly sales volume of the restaurant from July of 2014 to June of 2017 are collected from the restaurant in Keelung by combining the weather information from Central Weather Burea as the experimental data for the prediction model. The results show that support vector machines can accurately predict the weather information for the sales volume of the restaurant. The results can help the restaurant owner to plan good marketing campaigns and reduce inventory costs.
author2	陳同孝
author_facet	陳同孝 Yu-Ling Liu 劉育玲
author	Yu-Ling Liu 劉育玲
spellingShingle	Yu-Ling Liu 劉育玲 Application of Support Vector Machine (SVM) to Forecast Climate and Consumption Intention-In a restaurant in the northern Case
author_sort	Yu-Ling Liu
title	Application of Support Vector Machine (SVM) to Forecast Climate and Consumption Intention-In a restaurant in the northern Case
title_short	Application of Support Vector Machine (SVM) to Forecast Climate and Consumption Intention-In a restaurant in the northern Case
title_full	Application of Support Vector Machine (SVM) to Forecast Climate and Consumption Intention-In a restaurant in the northern Case
title_fullStr	Application of Support Vector Machine (SVM) to Forecast Climate and Consumption Intention-In a restaurant in the northern Case
title_full_unstemmed	Application of Support Vector Machine (SVM) to Forecast Climate and Consumption Intention-In a restaurant in the northern Case
title_sort	application of support vector machine (svm) to forecast climate and consumption intention-in a restaurant in the northern case
publishDate	2018
url	http://ndltd.ncl.edu.tw/handle/xv86uc
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Application of Support Vector Machine (SVM) to Forecast Climate and Consumption Intention-In a restaurant in the northern Case

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