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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 徐世勳(Shih-Hsun Hsu) | |
dc.contributor.author | Fu-Rong Lee | en |
dc.contributor.author | 李芙蓉 | zh_TW |
dc.date.accessioned | 2021-06-17T03:10:48Z | - |
dc.date.available | 2023-08-01 | |
dc.date.copyright | 2018-08-01 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-07-17 | |
dc.identifier.citation | 地理沙龍,2016。”世界三大糧食作物的種植區域分布”,農業,
https://kknews.cc/zh-tw/agriculture/annpjj6.html,2016,10,31。 李元和、周國偉、張芷瑄,”台灣白米批發與零售市場之不對稱價格傳遞”, 農業經濟論叢刊(TSSCI),19(1),49-80,2013年12。 林慧貞,2017。”農業氣象大數據,如何讓農民看得懂?”,農傳媒,2017年 10月20日。 邱郁筑,2016。“農業生產大數據之建置與應用”,行政院農業委員會統計室, 105年3月9日。 馬偉倫,2013。”臺灣稻米價格不對稱轉嫁之研究”,碩士論文,佛光大學, 宜蘭,礁溪。 焦鈞,2017。”農業二三事》農業大數據是擺脫看天田的一個契機“, 自由評論網專欄,自由時報,2017.7.15。 楊軼萃,2016。”圖解!大數據下必學的統計基礎”,碁峰資訊股份有限公司, 台北,pp. 36-38。 溫祖康,2009。“2008國際主要糧食穀物及油籽供需變化與價格走勢之近況 分析”,農政與農情,200期2009年2月。 農委會,2016。”104年我國糧食供需統計結果”,農政與農情 ,第294期。 簡禎富、許嘉裕,2014。”資料挖礦與大數據分析”,前程文化事業有限公司, 新北市。 譚磊,2013。”大數據挖掘,從巨量資料發現別人看不到的秘密”,上奇資訊 股份有限公司,台北。 Benzie, M. and A. John, 2015, Reducing Vulnerability to Food Price Shocks in a Changing Climate, Research Report, Stockholm Environment Institute, Jan. 1, 2015. Bharadi1,V. A., P. P. Abhyankar, R. S. Patil, S. S. Patade, T. U. Nate, and A. M. Joshi, 2017, “Analysis and Prediction in Agricultural Data Using Data Mining Techniques”, International Journal of Research In Science & Engineering e-ISSN: 2394-8299, Special Issue 7-ICEMTE March 2017, pp. 386–393. Dorosh, P. A. and M. Malek, 2015, “Rice Imports, Prices, and Challenges for Trade Policy”, The Nigerian Rice Economy: Policy Options for Transforming Production, Marketing, and Trade, University of Pennsylvania Press, U.S.A. Dumbre, N., O. Chikane, G. More, 2015, “System for Agriculture Recommendation Using Data Mining”, International Education & Research Journal, vol. 1, issue 5, Dec. 2015. FAO, 2006, 'Rice is life': International Rice Commission meets in Peru, World experts discuss ways to promote rice production and consumption, 24 April 2006, Rome/Lima, http://www.fao.org/Newsroom/en/news/2006/1000267/index.html FAOSTAT,UN,2017, World Population Prospects 2017, https://esa.un.org/unpd/wpp. Gartner, 2017. https://www.gartner.com/it-glossary/data-mining. Gartner, Inc., Stamford, Connecticut. U.S.A. Gilbert, C. L. and C. W. Morgan, 2010, “Food Price Volatility”, Philosophical Transactions: Biological Sciences, Vol. 365, No. 1554, Food security: feeding the world in 2050 (27 September 2010), pp. 3023-3034. Gopakumar, K. U. and V. Pandit, 2014, “Price Movements for Rice and Wheat: A Structuralist Policy Perspective”, Indian Economic Review, Vol. 49, No. 2 (July - December 2014), pp. 227-244. Kalpana, R., N. Shanthi and S. Arumugam, 2014, “A Survey on Data Mining Techniques in Agriculture”, International Journal of Advances in Computer Science and Technology, Volume 3, No.8, August 2014. Kavitha, S., D. Geetha, M. Gomathi, and R. S. Kumar, 2016, “Agricultural Analysis for Next Generation High Tech Farming in Data Mining”, International Journal of Scientific Development and Research (IJSDR), Volume 1, Issue 10, pp. 82 -86. Kim, J. and P. A. Ramirez, 2014, “Regionalism and Rice Trade in Southeast and Northeast Asia: Making Liberalization Work”, Journal of International and Area Studies, Vol. 21, No. 2 (December 2014), pp. 83-98. Korea Herald, 2017, “Agriculture minister says no to FTA changes on rice imports”, http://www.koreaherald.com/view.php?ud=20170720000851 Korea Herald, 2017, Korea vows no concessions in farm sector in talks with US to amend FTA, http://www.koreaherald.com/view.php?ud=20170720000262 Slotnik, W. J. and M. Orland, 2010. “Data Rich But Information Poor”, Education Week, May 6, 2010. http://www.edweek.org/ew/articles/2010/05/06/31slotnik.h29.html USDA, 2017, Economic Research Service, “Rice Yearbook”, http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do;jsessionid=9443E3085B683F05A69DBBA8934D5E7C?documentID=1229. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/69219 | - |
dc.description.abstract | 本研究選取稻穀為研究主題並應用大數據的資料探索方法探討台灣稻榖價格隱含的訊息,其目的是(1)藉著大數據資料探索稻穀價格的各項機率分布,從而找出台灣稻穀價格的領先地區和落後地區;(2)探討稻穀帄均價格之高、中及低價位之分布;(3)探討不同節氣的稻榖價格變動及各地區在不同節氣下的稻榖價格變動;(4)探討各地區稻榖價格的群聚關係。 資料範圍是從2012年1月1日至2017年12月31日,共有2,190天,15個地區別,原始資料筆數為32,850筆。所得結論是價格不變的天數占全部天數的43.91%,價格下跌的天數和上漲的天數分別占全部天數的28.78%和27.31%。全年價格不變的最高機率是二月份,全年稻穀價格下跌機率最高的是五月份,全年稻穀價格上漲機率最高的是十一月份。各月別稻穀帄均價格變動標準差顯示一月分為全年稻穀價格最穩定的月別。七月份是全年中變化最大的月別。 稻穀帄均價格之價位分布,北部地區全年皆落在中價位和低價位水準,中部地區除台中市外,大部分的縣市是落在高價位和中價位水準,南部地區的情況與北部地區類似,東部地區除宜蘭縣外,全年皆位於高價位和中價位水準。台東縣全年稻穀價格皆位於高價位水準,但桃園市、新竹縣、苗栗縣、台中市、高雄市和宜蘭縣皆未曾出現高價位水準。 由節氣分析,整個春季的稻穀帄均價格除了高雄市和宜蘭縣為低價位外,其餘各地區均落在高價位和中價位水準。夏季和秋季除南投縣、台東縣和花蓮縣仍然維持春季的價位水準外,其餘各縣市均落在中價位和低價位水準。冬季除了立冬和小雪有些地區出現低價位外,其餘各縣市均落在中價位和高價位水準。 由集群分析顯示台東縣和花蓮縣分屬最高和次高稻穀價格群。雲林縣、南投縣、彰化縣、屏東縣、嘉義市、嘉義縣、台南市為中價位群,其中雲林縣和南投縣為中價位群之最高者,嘉義市、嘉義縣和台南市是中價位群的最低者。新竹縣、苗栗縣、台中市為低價位群的最高者,桃園市、高雄市是低價位群的最低者。 | zh_TW |
dc.description.abstract | This study chose paddy as the research topic and applied data exploration methods of big data to explore the hidden information of paddy price in Taiwan. The purpose was to (1) explore the probability distribution of paddy price by using data explore of big data to find out the leading and lagging areas of paddy price in Taiwan; (2) explore the distribution of high, mid, and low levels of the average price of paddy; (3) explore the variations of paddy price in different solar terms and the variations of paddy price at various regions with different solar terms; (4) explore the clustering patterns of paddy price in various regions. The data period is from January 1, 2012 to December 31, 2017. It covers 2,190 days and 15 different areas. Total number of original data is 32,850. The research results showed that the price-invariant days accounted for 43.91% of the total number of days, and the days of price falling and increasing accounted for 28.78% and 27.31% of the total days, respectively. The highest probability of price-invariant throughout the year was in February. The highest probability of paddy price falling in the whole year was in May. The highest probability of paddy price increasing in the whole year was in November. The standard deviation of the average price of paddy in each month indicated that January was the most stable month for paddy price throughout the year. July was the month of greatest variation in the year. The price-level distribution of the average price of paddy in the northern region falls at mid-price level and low-price level throughout the year. In the central region except Taichung City, most of the counties and cities are at high-price and mid-price level. In the southern region is similar to the northern region. In the eastern region except for Yilan County, it is located at high-price and mid-price level throughout the year. The annual price of paddy in Taitung County is located at the high-price level, but there are no high-price level in Taoyuan City, Hsinchu County, Miaoli County, Taichung City, Kaohsiung City, and Yilan County.
From the solar terms analysis, except for Kaohsiung City and Yilan County which are low-price, the average price of paddy in the entire spring season falls at the high-price and mid-price level. In summer and autumn, other than Nantou County, Taitung County, and Hualien County kept the price level in the spring, all other counties and cities decreased to the mid-price and low-price level. During the winter season, except some areas indicated low price in the beginning of winter and small-snow period, all other counties and cities were located in mid-price and high-price level. Cluster analysis shows that Taitung County and Hualien County belong to the highest and second highest price group of paddy, respectively. Yunlin County, Nantou County, Changhua County, Pingtung County, Chiayi City, Chiayi County, and Tainan City are mid-price group, of which Yunlin County and Nantou County being the highest among the mid-price group, Chiayi City, Chiayi County, and Tainan City being the lowest of this group. Hsinchu County, Miaoli County, and Taichung City are the highest of the low-price group, and Taoyuan City and Kaohsiung City are the lowest of the low-price group. Keywords:Price of | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T03:10:48Z (GMT). No. of bitstreams: 1 ntu-107-P05627010-1.pdf: 3989723 bytes, checksum: 6e57b02a779a3c34fcd633bb14128b8d (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 謝辭 ....................................................................................................................................i
摘要 ................................................................................................................................... ii Abstract ............................................................................................................................. iii 圖目錄 .............................................................................................................................. vi 表目錄 .............................................................................................................................. ix 第一章緒論 ...................................................................................................................... 1 第一節稻榖在全球糧食作物中的重要性 .............................................................. 1 第二節研究動機 ...................................................................................................... 3 第三節研究目的 .................................................................................................... 10 第四節研究流程 .................................................................................................... 11 第二章文獻探討 ............................................................................................................ 12 第一節台灣稻米產銷概況之回顧 ........................................................................ 12 第二節稻米價格文獻之回顧 ................................................................................ 21 第三節農業大數據文獻之回顧 ............................................................................ 24 第三章研究方法 ............................................................................................................ 26 第一節描述性統計方法 ........................................................................................ 27 第二節機率分布與貝氏定理 ................................................................................ 31 第三節集群分類法 ................................................................................................ 34 第四章實證結果與分析 ................................................................................................ 35 第一節描述性統計方法 ........................................................................................ 36 第二節各月別稻穀帄均價格變動分析 ................................................................ 44 第三節各地區不同節氣稻穀帄均價格之探討 .................................................... 65 第四節稻穀帄均價格分組頻率之節氣分析 ........................................................ 84 第五節稻穀帄均價格之集群分類 ...................................................................... 110 第五章結論與建議 ...................................................................................................... 116 第一節結論 .......................................................................................................... 116 第二節建議 .......................................................................................................... 119 參考文獻 .............................................................................................................. 121 中文部分 .............................................................................................................. 121 西文部分 .............................................................................................................. 122 | |
dc.language.iso | zh-TW | |
dc.title | 台灣稻穀價格之研究-大數據之應用 | zh_TW |
dc.title | A Study on the Price of Paddy in Taiwan–The Application of Big Data | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 李元和(Yuan-Ho Lee) | |
dc.contributor.oralexamcommittee | 張靜貞(Ching-Cheng Cgang) | |
dc.subject.keyword | 稻穀價格,節氣,大數據, | zh_TW |
dc.subject.keyword | Price of paddy,Solar terms,Big data, | en |
dc.relation.page | 123 | |
dc.identifier.doi | 10.6342/NTU201801629 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2018-07-18 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 農業經濟學研究所 | zh_TW |
顯示於系所單位: | 農業經濟學系 |
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