data modeling and decision 中文意思是什麼
data modeling and decision
解釋
模型與決策-
The author have studied data warehouse and olap and data mining, then discussed the relevant concepts, development status, system structure and implementation in details ; meanwhile, through studying the data model of university enrollment examination, integrating with data obtaining technology, multidimensional modeling technology and olap in data warehouse, designed a data mart of university enrollment examination and thus developed a data analyzing system of university enrollment examination based on model supporting decision and olap and data mining
本論文對數據倉庫、聯機分析處理和數據挖掘技術進行了研究，並詳細介紹了有關的概念、發展狀況、體系結構和實現手段；同時，通過對普通高校招生考試的數據模型進行研究，結合數據倉庫中的數據獲取技術、多維建模技術設計了一個以普通高校招生考試數據分析為主題的數據集市，並在此基礎上綜合運用聯機分析處理技術、數據挖掘技術和模型輔助決策技術實現了一個招生考試數據分析系統。 -
This research focused on applying the system analysis principle and mathematical modeling technique to study knowledge expression system for crop cultivation management. based on extensively collecting, understanding, analysis, and integration of expert ' s knowledge and experience, literature and experiment data for cotton cultivation management, the dynamic relationships of cotton growth and management indices to variety types, ecological environments and production levels were quantified, and a dynamic knowledge model for cotton management ( cottonknow ) was developed. by further incorporating the rule - based knowledge system for cotton management, a comprehensive and intelligent knowledge model - based decision support system for cotton management ( kmdsscm ) was established with component design
本研究著重利用系統分析原理和數學建模技術來研究作物栽培管理的知識表達體系，在廣泛收集及充分理解和分析棉花栽培管理專家知識、經驗和資料的基礎上，利用棉花栽培理論與技術方面的現有研究成果，並結合必要的試驗支持，解析、提煉和綜合棉花生育及管理指標與品種類型、生態環境及生產水平之間的定量化關系，首次構建了棉花栽培管理動態知識模型，並進一步結合基於知識規則的棉花栽培管理知識庫表達系統，設計和實現了綜合性、智能化和構件化的基於知識模型的棉花管理決策支持系統（ kmdsscm ） 。 -
The data mining modeling of a decision tree is studied using the transmission system of a lathe as an example, and the mapping of product conceptual design is primarily achieved
以機床傳動系統為例，研究決策樹演算法的數據挖掘模型，並初步實現了產品概念設計過程的功能結構映射。 -
The modeling process is based on data mining technology, which can automatically discover the rules and knowledge in desulfuration process, and then provides the decision support, improves the desulfuration effect and decreases the cost. the successful use of this static model will be a solid prerequisite for full automatic dusulfuration in the future
本文以國內某大型鋼鐵公司為背景，採用數據挖掘方法建立脫硫靜態模型，自動尋找脫硫過程的規律和知識，從而對脫硫過程進行決策支持，提高脫硫效果，降低脫硫成本，為全自動脫硫創造了良好的條件。 -
Analysis and modeling of statistical distributions of indoor radon concentration from data valorization to mapping and simulations are critical issues for real decision - making processes
本研究經由統計分析及模式化室內氡氣濃度，使資料繪圖及模擬作為真正決策時之依據。 -
In order to offer model for model system of decision support system, data processing techniques of neural network etc. dynamic and no need user - defined dimension are used to modeling
為給決策支持系統中的模型庫系統提供模型，採用神經網路等具有動態的以及不需自定義維數的數據處理技術進行建模。 -
This thesis mainly researches on pattern of telecommunication management analysis and decision support in our fix - line telecommunication operation. first the construction of data warehouse is discussed, analyses the data of the base information, billing information and calling detail record of the customer, and then discuss the methods of data mining including defining the operation scope, sampling, data analysis, modeling and implementation we put focal point on the choice and design that the model of data mining, on the basis of the already studies of abroad and the actual needs of fix - line telecommunication company. three data mining models of our fix - line telecommunication operation are putted forward : customer value model, customer retention model, and customer segment model
本文對于固網通信業經營決策支持模式的探討和研究，是從企業級數據倉庫的構建出發，圍繞如何提高企業客戶細化和預測能力的問題，針對通信企業積累的大量客戶基本信息、客戶通話信息、客戶帳單信息、客戶繳欠費等數據，在數據挖掘方法論的指導下，通過業務問題范圍、選取和抽樣、探索型數據分析、建模和實施等步驟進行分析，闡述通信企業以數據倉庫為核心的數據挖掘模型選擇與設計的一般方法，提出我國固網通信運營業的三個數據挖掘應用模型:客戶分群，客戶流失和客戶價值分析。
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