如果要监视的数据库系统是用于决策支持(DSS)的，查询比较长而且比较复杂，那么不要让质量控制(QC)代理运行大型的查询。
If the database system you are monitoring is for decision support (DSS), and the queries are long and complicated, don't have the quality control (QC) agent run a large query.
例如，如果您的数据库用于事务处理和繁重的决策支持(DSS)查询，则可以确定非预定的DSS查询将牺牲您的事务性能。
For example, if your database is used for transaction processing and heavy decision-support (DSS) queries, you can be sure that a non-scheduled DSS query will trash your transaction performance.
针对关系型数据库在联机分析方面的不足，利用数据仓库的相关技术和开发方法，提出了决策支持系统开发的一种新途径。
A new approach to decision support system is put forward based on related techniques and development methods of data warehouse for the shortage of relational database in the aspect of OLAP.
数据库是计算机智能决策支持系统的核心。
Database is the core of intelligent decision support system.
本文首先对决策支持系统(dss)的概念、体系结构进行了简要的介绍，阐述了DSS的数据库系统、模型库系统、知识库系统以及方法库系统。
This paper describes the concept, system structure of the Decision Support system (DSS) firstly, then introduces the database, model library, knowledge library and arithmetic library of the DSS.
传统的决策支持系统以数据库作为数据管理的手段，而数据库系统主要用于事务处理，使得基于数据库的决策支持系统存在于事务处理环境之中。
The DSS is planted in the transaction-processing environment for the sake of its data management based on the traditional database that is mainly used for transaction processing.
决策支持需要历史数据，而操作数据库一般不维护历史数据。
Decision support requires historical data, whereas operational databases do not typically maintain historical data.
研究表明，物流决策支持系统开发是一个十分复杂的软件和硬件集成过程，数据库和模型库设计是系统开发的关键所在。
The results indicate that the system development of LDSS involves complicated processes of software and hardware integration and the design of database is the key of the development.
本文介绍工资智能决策支持系统SIDSS系统结构和主要功能，讨论了事件处理器、规则处理器及方法库与数据库等关键技术。
This paper introduces the architecture and main functions of SIDSS, discusses the key implementations such as event handler, rule handler, method base and database.
目前，该研究领域已经成为数据库、信息管理系统、人工智能及决策支持等相关领域的研究课题。
At present, this research area already became correlation domain and so on the database, information management system, artificial intelligence and policy-making support research topics.
在实际应用中，详细论述了采用前述的建模方法进行决策支持系统数据仓库层模型的设计，包括数据建模、关系数据库选择及实现。
In the application of the aforementioned theory, the design of database 's system model on DSS is elaborated, including data modeling, the choice and realization of relational database.
服务器调用智能系统，并请求数据库服务器和虚拟诊断平台提供支持，对现场状态进行监控和诊断决策。
The intelligence system was called by server; and the support from database server and virtual diagnosis platform was requested. At last, the actual state monitor and diagnosis were carried out.
接着对泵站机组启停决策支持系统的目标、结构和功能做了分析，建立了决策所需要的数据库、模型库和知识库。
Afterwards, the goal, structure and function of PSSEDSS are analyzed and the data base, model base, knowledge base necessary for decision-making are set up as following.
DSS的本质就是将各种广义模型相互有机结合起来，对数据库中的数据进行处理，从而辅助决策支持过程。
The essence of DSS is to process data on the basis of databases and model system consisting all kinds of the generalized models that have been well joint with each other and to help to make decisions.
为弥补传统数据库管理系统在智能决策支持系统应用中的缺陷，一种新的数据组织和管理技术——数据仓库技术应运而生。
To make up for the limitations of normal DBMSs to be used in IDSSs, a new technique-data warehouse is developed for the requirement of data organization and administration.
其次，根据决策支持系统理论，采用三库结构即：数据库、模型库、方法库及其管理子系统并设计各库的组成与功能。
Then the bases of system were designed, which included data base, model base, method base as well as each one's management base.
数据仓库技术、OLAP 技术和数据挖掘技术对决策支持系统的有力支持使其成为数据库技术领域一个研究的热点和重点。
There have been growing interests in the techniques of date warehouse, OLAP and data mining since they strongly support the decision-making.
数据挖掘是当前国际上数据库和决策支持分析领域最前沿的研究方向之一。
Data mining is one of the most advanced research directions of data warehouse and decision support analysis nowadays.
数据挖掘是目前数据库和决策支持领域的最前沿的研究领域之一。
The DataMining is one of the most front research area in Data-Base and Decision-making support system.
文章通过对现有GIS中空间数据库系统模型的分析与比较，提出了一个适用于智能化空间决策支持系统(SDSS)的空间数据库系统模型。
This paper analyzes the current Database Systems in GIS, then a new Spatial Database System Model (SDB-SM) is introduced, which adapt to intelligent Spatial Decision Support System (SDSS).
数据挖掘是一项较新的数据库技术，它基于大量数据所构成的数据库，从中发现潜在的、有价值的信息——称为知识，用于支持决策。
Data Mining is a newer database technique which aims at discovering potential and valuable pattern that is called as knowledge. The knowledge discovered can be used for decision-making.
文章第二章到第四章分别是对三库结构设施区位决策支持系统模型库、数据库和算法库的详细研究。
Lastly, this article designs and implements facility location DSS based on a three-base structure, which are the Model base, Data base and Algorithm base.
本论文中论述了当前主要的数据库、数据仓库优化理论和决策支持系统的关键技术。
This thesis expounds current primary database, data warehouse optimization theory, decision trees and decision support systems critical technologies.
然后，将此数据库提供给多个客户(包括广告商、企业等)，为其的经营决策和市场营销决策提供数据支持。
Then this database is provided to many customers (including advertising agency and enterprise) to support management decision-making and marketing decision-making.
通过系统结构与功能的分析，确定了数据库与模型库的范畴，并通过流程图将这一决策支持系统表示出来，最后以上海公交问路系统的开发展示了该系统的应用前景。
Then, according to practical problem on asking the way system, it introduces the structure and function of DSS. Finally, it takes Shanghai as example to show the future of DSS based on GIS.
通过系统结构与功能的分析，确定了数据库与模型库的范畴，并通过流程图将这一决策支持系统表示出来，最后以上海公交问路系统的开发展示了该系统的应用前景。
Then, according to practical problem on asking the way system, it introduces the structure and function of DSS. Finally, it takes Shanghai as example to show the future of DSS based on GIS.
应用推荐