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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 歐陽彥正 | zh_TW |
| dc.contributor.advisor | Yen-Jen Oyang | en |
| dc.contributor.author | 賈皓中 | zh_TW |
| dc.contributor.author | Hao-Chung Chia | en |
| dc.date.accessioned | 2024-08-08T16:24:09Z | - |
| dc.date.available | 2024-08-09 | - |
| dc.date.copyright | 2024-08-08 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-08-01 | - |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/93822 | - |
| dc.description.abstract | 資源在空間上的分配已被探討許久，如緊急醫療服務、學校、警局等設施在地理空間的設置。現今大部分的討論都建立在「最大覆蓋位置問題」(Maximal Coverage Location Problem)，該模型旨在找到給定數量的設施在空間中的最佳放置位置的問題，目標是在一定限制下最大化覆蓋人口的總需求。此研究我們以找出移動式中風診療單元的部屬地點為目的，使用美國加利福尼亞州馬林縣的緊急救護資料，從機器學習的角度，用最大期望演算法(Expectation-maximization algorithm)找出最佳部屬地點。再輔以救護車派遣模擬估計派遣花費的時間。考慮到MCLP是一個NP-hard問題，EM衍生方法不需要複雜的數據預處理，能更快地提供解決方案，這使其成為解決覆蓋位置問題的一個更有效的替代方案。 | zh_TW |
| dc.description.abstract | The allocation of resources in spatial distribution has been a topic of discussion for a long time, including the placement of emergency medical services, schools, and police stations in geographic spaces. Most current discussions are based on the Maximal Coverage Location Problem (MCLP), a model focused on finding the optimal placement of a given number of facilities in a space to maximize the total demand coverage under certain constraints. In this study, we aim to determine the deployment locations for Mobile Stroke Units (MSUs) using emergency medical data from Marin County, California. From a machine learning perspective, we employ the Expectation-Maximization (EM) algorithm to identify the optimal deployment sites. Additionally, we use an ambulance dispatch simulation to estimate the dispatch time. Considering that MCLP is an NP-hard problem, the EM derivative method, which does not require complex data preprocessing, provides a quicker solution. This makes it a more effective alternative for solving the coverage location problem. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-08-08T16:24:09Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-08-08T16:24:09Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | ABSTRACT II
摘要 III TABLE OF CONTENTS IV LIST OF FIGURES VII LIST OF TABLES VII CHAPTER 1 INTRODUCTION 1 1-1 Background 1 1-1-1 The Mobile Stroke Units (MSUs) 1 1-1-2 Location Allocation Problem 2 1-2 Aim of Study 3 CHAPTER 2 LITERATURE REVIEW 5 2-1 Deterministic Location Problem 5 2-1-1 Location Set Covering Problem (LSCP) 5 2-1-2 Maximal Covering Location Problem (MCLP) 6 2-1-3 Multiple-Performance Problem 7 2-2 Probabilistic and Stochastic Location Problem 9 2-2-1 Maximum Expected Covering Location Problem (MEXCLP) 9 2-2-2 The Maximum Availability Location Problem (MALP) 10 2-3 Two - Step Floating Catchment Area 12 CHAPTER 3 METHOD 14 3-1 The Maximum Accessibility 14 3-2 Maximum Likelihood 14 3-3 Expectational – Maximum Derivative Algorithm 16 3-4 Performance Measurement - Dispatch Simulation 17 CHAPTER 4 EXPERIMENT 19 4-1 Maximizing Accessibility with EM – Derivative 19 4-2 Dataset used and area information 21 4-3 Data Preparation 22 4-4 Initial Seeds Selection 22 4-5 Simulation Related Work 23 4-6 Comparison Model － MCLP 23 CHAPTER 5 RESULT 25 5-1 EM Derivative Computed Location 25 5-2 Ambulance Dispatch Simulation Result 27 5-3 Performance Comparison with MCLP 28 CHAPTER 6 CONCLUSION AND FUTURE WORK 37 6-1 Conclusion 37 6-2 Future Work 38 REFERENCE 40 APPENDIX 45 EM-derivative algorithm, Marin County 45 MCLP Location and Simulation Result, Marin County 53 Coordinate of Relocated Sites, Marin County 69 EM – derivative and MCLP calculation result, Montgomery County 70 Coordinate of Relocated Sites, Montgomery County 82 Box plot and the Corresponding Distribution 85 | - |
| dc.language.iso | en | - |
| dc.subject | 位置分配問題 | zh_TW |
| dc.subject | 緊急醫療服務 | zh_TW |
| dc.subject | 機器學習 | zh_TW |
| dc.subject | Location allocation problem | en |
| dc.subject | Emergency Medical Services | en |
| dc.subject | Machine learning | en |
| dc.title | 行動式中風診療單元部署之最佳化研究 | zh_TW |
| dc.title | A Study on Optimization of the Deployment of Mobile Stroke Units | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 楊孟翰;黃乾綱;孫維仁 | zh_TW |
| dc.contributor.oralexamcommittee | Meng-Han Yang;Chien-Kang Huang;Wei-Zen Sun | en |
| dc.subject.keyword | 緊急醫療服務,機器學習,位置分配問題, | zh_TW |
| dc.subject.keyword | Emergency Medical Services,Machine learning,Location allocation problem, | en |
| dc.relation.page | 85 | - |
| dc.identifier.doi | 10.6342/NTU202402651 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2024-08-04 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 資訊工程學系 | - |
| dc.date.embargo-lift | 2025-07-30 | - |
| 顯示於系所單位： | 資訊工程學系 | |
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