模糊資料探勘方法於影響登革熱疫情之因素關聯性分析系統設計研究

A study on Association Analysis System Design of Influencing Factors for Dengue Fever Based on Fuzzy Data Mining

近年來，我國國人感染「登革熱」的人數有逐年增加的趨勢。尤其，在2015年的夏季登革熱嚴重襲捲南台灣，總感染人數創下歷年來的新高，全國民眾無不人心惶惶。故此，了解登革熱疫情擴散的影響因素以防止疫情擴散乃是相當重要的課題。事實上，可能影響登革熱疫情之因素甚多，本研究以資料探勘的關聯規則分析作為基礎，進行登革熱疫情影響因素關聯性分析系統的規劃與設計。然而，在探討因素的關聯性時，常常因為影響因素的質化特性以及評估人員的主觀性判斷，使得影響登革熱之因素關聯分析過程與結果隱含不確定性與模糊性。為此，本研究結合模糊理論與資料探勘技術，探討影響登革熱疫情因素之間的關聯性，進而利用雛型法規劃一個登革熱疫情影響因素關聯性分析系統，透過互動的操作介面快速提供分析結果，以提供醫療機構及民眾進行登革熱防疫工作的參考。

In recent years, Dengue fever brings a huge of impacts in Taiwan. Dengue fever has caused the outbreaks in Taiwan every summer. The dengue fever severely hit southern Taiwan in the summer of 2015. Therefore, it is very important to understand the factors that influence the spread of dengue fever in order to prevent the spread of the epidemic. In fact, many factors will influence the epidemic of dengue fever. However, the process of the factors relationship analysis of the dengue fever always implies the uncertainties and fuzziness due to the qualitative characteristics of factors and subjective assessment of people. Therefore, we combined the fuzzy set theory with data mining technology in this paper to explore the key factors and their relationships of the dengue fever epidemic and plan an association analysis system of the influencing factors of dengue fever. According to the proposed system, it can provide the important factors and association rules of dengue fever to the medical institutions and people to prevent the spread of the epidemic.