臺灣博碩士論文加值系統

由於國人對於飲食的健康需求越來越講究，進而造就「有機農業」的興起。但大多數農民在從事有機種植時，常會面臨到一個問題 - 「要種什麼才好？」。因此，如何有效率且精確地選擇出合適的種植作物，是非常值得去探討的方向。此外，在所有合適種植的作物中，考慮其相對的經濟價值，作為各季節中應優先選擇之依據，以達到整年度種植最大經濟利潤之目標，也是另一個值得去深思的課題。
本研究以有機蔬菜種植為例，運用知識庫與規則判斷，結合賽局理論之推導，並透過多重代理人機制，以ASP.NET和MS-SQL來開發一套圖形化的智慧型推薦系統。在第一階段推薦中，先透過文獻回顧與專家訪談來進行知識擷取的動作，進而建置出本研究之有機蔬菜生長屬性知識庫，再依據知識庫來制定本研究的規則判斷演算式，以篩選出各季節中適合種植的蔬菜種類，並依照合適程度做優劣排序後，提出整年度蔬菜種植的合適性推薦；在第二階段推薦裡，則是考量有機蔬菜種植的相關規範與限制下，分析蔬菜彼此之間所存在的相對影響因素及轉換成本，來設計實際賽局運作的協議過程，並結合多重代理人機制，設計出三個代理人，分別為季節代理人、衝突協調代理人以及推薦代理人，讓系統能更有效率地執行，最後透過多重代理人之賽局協議模式，來進行最大經濟利潤的比較分析，以提出整年度蔬菜種植最大經濟利潤的推薦。
在這套系統中，以苗栗農改場之有機種戶所提供的土地環境參數，共11組，來進行實際的系統測試；其次，發放120份的專家問卷來進行驗證，以相同的土地環境參數條件來詢問領域專家，最後得到100份的有效問卷，並將領域專家所推薦的結果與本系統所推薦之結果進行比較分析，證實的確能及時且提供相當於領域專家約84.25%的推薦水準，以克服領域專家缺乏之問題。此外，利用窮舉法列出所有組合的經濟利潤並依利潤大小給予排名，證明本系統所推薦之最大經濟利潤約為所有組合中的前4.64%。
本研究藉由知識庫與模式的結合，打破原有單純進行評估、決策方案的推薦系統模式，除了領域知識的知識庫外，也包含了模式，讓使用者在面對數個可能的選擇中，提供較更客觀且有效之建議。未來期望此系統也能應用在其它不同作物之選擇的研究上。

Because the people are fastidious more and more regarding the diet healthy demand, therefore has accomplished the organic agriculture starting. But the majority farmers when are engaged in the organic planter, does the regular session faced with - what need to plant to a question to be only then good. Therefore, how effectiveness, and chooses the appropriate planter crops precisely, is direction which is worth discussing. In addition, in all appropriate planter's crops, considered that its relative economic value, takes in various seasons should basis of the priority selection, achieves goal of the entire year planter most greatly economic profit, is also another ponder topic.
Taking organic vegetables farming as an example, this research uses knowledge-based and rule-based methods, while applying the game theory and multi-agent theory, this study develops a set of graphic intellectual suggestion mechanism with ASP.NET and MS-SQL. In the first stage of the study, we apply the knowledge base and the rule base composed for this study, we filter the suitable crops for each season, and order the list of crops in the order of suitability before we propose the planting suggestion for the entire year. Next, we design a realistic game theory and multi-agent theory to operate a negotiation process for a more effective system, which considers the organic plantations’ affect between each crop and the limitation of the system, as well as the crop shifting cost. In the end, we construct a multi-agent game theory of negotiation in order to analyze the maximum profit and propose a one year with a maximum profit.
In this system, a merge of game theory and multi-agent system has been tested and verified to give suggestions that are 84.25% as effective, compared to the suggestions provided by human professionals. Other than this, the system’s greatest contribution is that, the mechanism may act as a front system of e-learning application, thus increase the level of the organic farming techniques.
This research because of knowledge library and pattern union breaks original carries on the appraisal, the decision scheme recommendation system model purely. Besides domain knowledge knowledge library and model let the user in face several possibilities in the choices, provides is more objective a more effective suggestion. In the furture, it is expected to be applied to other crops planting suggestion.

指導教授推薦書
論文口試委員審定書
博碩士論文授權書
博碩士論文電子檔案上網授權書
誌謝
摘 要
Abstract
目 錄
圖目錄
表目錄
第一章 緒論
1.1 研究背景與動機
1.2 研究目的
1.3 研究範圍與限制
1.4 研究流程及內容
第二章 文獻回顧
2.1 有機農業
2.1.1 種類的選定
2.1.2 相關的規範
2.1.3 生產與銷售方式
2.1.4 國內發展與研究
2.2 知識管理
2.2.1 知識的定義
2.2.2 知識的表示法
2.2.3 知識的擷取
2.3 推薦系統
2.3.1 系統模式
2.3.2 國內、外著名之推薦系統
2.4 賽局理論
2.4.1 議價賽局
2.4.2 衝突分解
2.5 多重代理人系統
2.5.1 代理人特性
2.5.2 多重代理人特性
第三章 研究方法及步驟
3.1 第一階段-整年度之合適性推薦
3.1.1 制定判斷的決策因子
3.1.2 邏輯推論原則制定
3.1.3 知識庫與規則產生
3.2 第二階段-整年度之最大經濟利潤推薦
3.2.1 田野調查法收集資料
3.2.2 制定實際賽局協議之分析架構
3.2.3 導入多重代理人衝突分解之觀念
第四章 系統實作與驗證
4.1 系統架構
4.2 系統代理人之設計
4.3 系統功能介紹
4.4 系統測試
4.5 系統驗證
第五章 結論
5.1 系統功能特色
5.2成果與貢獻
參考文獻
附錄

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