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題名:兒童遊具產品安全評估模式之建構─以鞦韆與滑梯設施為例
作者:黃獻平
作者(外文):Shien-Ping Huang
校院名稱:中華大學
系所名稱:科技管理研究所
指導教授:賀力行
學位類別:博士
出版日期:2006
主題關鍵詞:層級貝氏模型基因演算法安全評估遊具設計Hierarchical Bayes Modelgenetic algorithmsafety evaluationdesign of entertainment facilities design
原始連結:連回原系統網址new window
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摘 要
在過去的遊樂設施使用傷害研究上可以發現,學者通常會將特定遊具所造成的傷害視為具有同質性的個體來進行分析。但是隨著整體消費者意識形態的改變,家長或遊具製造商對遊具使用安全性的要求逐漸升高,再加上遊具設計因子對每種傷害的發生確實具備不同的影響結果,造成傳統將特定遊具所造成的傷害視為同質性的概念已經不能符合實務之狀況,因此,所謂的異質性(Heterogeneity)分析概念乃因應而生。間接的也促成了近年來設計及製造業者逐漸將如何生產安全性高的遊具產品,作為其主要競爭力的行銷優勢。為了成功達到了解遊具設計因子對每種傷害發生的關係,設計業者常須先針對遊樂設施使用傷害的異質性發生進行了解。
為了能確切的提供設計業者了解造成傷害發生的關鍵遊具設計因子,在本研究中,嘗試以實際傷害發生的個案資料佐證層級貝氏模型的延展性與實用性。本論文的整體架構整理如下:第一章說明研究背景、動機以及研究架構;第二章則針對本文中所使用方法及應用課題進行相關文獻的探討;第三章研究方法乃是運用層級貝氏方法、基因演算法遊具產品安全評估建構研究探討;第四章實證分析是利用台灣各縣市之國民小學學童的受傷情況資料來進行設計因子與傷害種類發生關係的異質性分析,並根據實證結果提供遊具設計者了解遊具使用傷害造成的確切因素,以進一步提供整體解決方案。以及針對層級貝氏模型在參數估計上的效率的問題,提出整合基因演算法的技術來加速蒙第卡羅-馬可夫鏈 (Monte Carlo Markov Chain, MCMC)估計方法的收斂速度。第五章結論與建議。
Abstract
In past research on the use of entertainment facilities, it was found that scholars usually regard the injuries, which specific entertainment facilities cause, as individual with homogeneity and use the view to guide their research. Gradually, because consumers’ thinking is changing, parents and manufacturers make increasing demands for the safety of entertainment facilities. Also, injuries that designs of facilities bring about have indeed different impacts and results. So the traditional homogeneity view cannot meet the new practical situation. For this reason, the conception of analysis by using heterogeneity has been discussed. In recent years, designers and manufacturers have gradually regarded how to produce entertainment facilities with high safety as the main advantage of competitive marketing. In order to have successful understanding of the relation of every element of facilities designing with the happening of every injury, first of all, designing companies need to focus on advancing understanding of the heterogeneity of injuries caused by use of entertainment facilities.
To make sure of designing companies’ realization on every element of facilities’ design causing injury, the study will try to use information of actual injuries to prove the extended nature and practical nature of a Hierarchical Bayes Model. The whole structure of the dissertation for individual chapters is as follows. Chapter One deals with research background, motivation and research structure. Chapter Two proceeds to explore the contents of documents according to methodology and applied issues of the dissertation. Chapter Three this research was done by using hierarchical Bayes approaches. The research on the structure of playgroud equipment security assessment using genetic algoritm. Chapter Four makes use of data about injurious situations of elementary school students of Taiwan’s every county and city to be engaged in analysis on heterogeneity of relation between elements of design and the type of injuries. In this chapter, according to actual proved results, clear elements causing injuries will be proposed in order to let facility-designing companies have a clear understanding. Further, here also offers some solutions for the whole. Directly aiming at question about the effectiveness of Hierarchical Bayes Model in parameter estimation, proposes techniques of integrated genetic algorithm to speed up convergence speed of Monte Carlo Markov Chain’s (MCMC) estimation method. Chapter Five makes conclusions from the whole study and proposes future research direction and suggestions.
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