商业决策支持系统的研究与设计

主要介绍商业决策支持系统的设计方法与实现技术，重点讨论商业决策支持系统（CDSS）的主要结构，模型和知识的表示与实现技术、处理机的功能，数据抽取技术等问题。     

基于数据仓库技术的教育评价决策系统的实现

针对高校教务管理系统中存在的不足，将数据仓库技术引入高校教育评价决策支持系统。设计了基于数据仓库和0LAP技术的教育评价决策支持系统的体系结构，描述了各逻辑服务模型的具体功能。文章重点介绍了运用Microsoft SQL Server2000提供的数据透视表服务，由ADO MD对象模型访问数据仓库服务器，最终实现了客户端的数据多维分析与查询．基于数据仓库的教育评价决策系统克服了传统决策支持系统的弊端，增强了高校教务管理功能，对于提高教育质量、促进教育发展具有现实意义。     

基于粗糙集理论的智能决策支持系统

本文着重介绍了基于粗糙集理论的智能决策支持系统的总体结构及其各个模块的功能。首先介绍了智能决策支持系统产生的背景．即人工智能技术和决策支持相结合而产生的。粗糙集理论是研究不完整、不确定知识并口．数据的表达、学习、归纳的理论和方法，适合于发现数据中隐含的、潜在有用的规律，即知识，找出其内部数据的关联关系和特征，因此在智能决策支持系统中发挥着重要作用。     

主动数据库及在DSS中的应用研究

主动数据库是数据库技术中一个活跃的研究领域，它是在传统数据库的基础上，结合人工智能和面向对象技术提出的，其主动性功能正在各种应用中发挥越来越大的作用。主动数据库强调数据库反应能力上具有主动性、快速性和智能化的特性，而决策支持系统要求数据库具有很强的数据预处理和数据分析能力，将主动数据库应用于决策支持系统中，一定会使决策支持系统具有更强的优越性，从而更好地发挥决策支持系统辅助决策的作用，以满足各种层次、各种类型、不同决策者的决策过程对数据的要求。     

房地产决策支持系统的时空数据分析

在房地产决策支持系统的研究开发基础上，结合地理信息技术、数据仓库等决策支持新技术，提出五库和数据仓库的房地产决策支持系统体系结构并分析了房地产决策支持系统时空数据及其管理办法，最后结合房地产数据信息特点给出了房地产决策支持系统数据仓库的层次结构和数据流程，以便计算机上实现，从而辅助高层管理者决策，提高科学决策效能。     

基于数据挖掘的医院决策支持系统设计与实现

介绍了医院决策支持系统的建设背景,描述了在数据挖掘技术的基础上,利用基于Caché数据库的决策支持工具Speedminer建立数据仓库、数据集市和实现决策支持系统的过程,以及决策支持系统在医院管理、临床科研等方面的应用效果.     

基于数据仓库的商业营销决策支持系统开发

针对现有的商业管理信息系统在决策支持方面的不足，提出了一种基干数据仓库的商业营销决策支持系统(DSS)。分析了系统的总体结构、数据仓库实现过程中的数据建模和数据转移问题、联机分析处理的实现，并描述了系统的功能。     

基于多Agent的企业市场营销决策支持系统设计

由于当前已有系统未能采用模糊调整-模拟反馈方法对市场需求进行预测，导致企业市场营销决策支持错误率和响应时间上升、可靠性下降，为此提出一种基于多Agent的企业市场营销决策支持系统，结合Agent技术和理论进行设计，详细阐述系统的具体操作流程。通过模糊调整-模拟反馈方法对企业市场需求进行预测，调整市场营销策略，确定营销计划，最终实现企业市场营销决策支持系统设计。仿真实验结果表明，所设计系统能够有效提升系统的可靠性，同时降低企业市场营销决策支持错误率和响应时间。     

基于Cö S环境的商业决策支持系统研究与设计

介绍基于Ｃ／Ｓ环境的商业决策支持系统的设计方法与实现技术,着重讨论商业决策支持系统的主要结构,模型和知识的表示与实现技术,处理机的功能,数据抽取技术等问题。     

基于Web的电信闭环决策支持系统的研究与实现

通过对电信数据的分析，提出了基于Web的电信闭环决策支持系统的实现方案。确定了电信领域的决策分析主题，建立了相关的联系和模型，阐述了采用基于数据仓库的四层结构的电信闲环决策支持系统的系统架构和功能。运用联机分析处理、数据挖掘等分析决策手段实现了对电信数据多角度、多层次的查询、分析及决策功能。     

电力营销决策支持系统的设计

本文对当前电力营销管理信息系统存在的问题进行探讨,通过对相关软件平台、技术难点的分析,提出了以大型数据库系统和商业智能系统为基础平台开发电力营销决策支持系统设计方案,讨论了系统的功能和实现.     

网络营销的智能决策支持系统设计和开发

着重分析智能决策支持系统在网络营销方面的应用。首先,从Internet出发提出本文课题的讨论背景。接着,叙述电子商务与决策支持系统的发展现状及其发展趋势。通过网络营销智能决策支持系统的设计和开发表达了决策支持系统的重要性。     

Integrated decision support and expert systems in a computer integrated manufacturing environment

In a computer integrated manufacturing (CIM) environment, well planning, control and operational process require both expert knowledge of the area, and powerful decision support capabilities. This paper discusses the features of decision support systems and expert systems, and their integration to support the major functions from marketing and strategic level considerations to manufacturing operational planning and process. From the hierarchical structure of information flow in a company, this paper attempts to find the best way of combining decision support systems with expert systems in enhancing the planning, control and operational functions in a CIM environment.     

Developing a marketing decision model using a knowledge-based system

This paper describes using a knowledge-based system for developing a marketing decision model. The approach used in this study uses a decision table as a knowledge engineering tool. The decision table is used as a means of representing a set of decision rules to construct a developed marketing decision model. To support the modeling process, Prologa, an existing decision table engineering workbench, is used. The developed marketing decision model is used to determine the entrance time of a new product into market by utilizing knowledge-based systems. Presentation of a new product to the market at the best time will provide an advantage to competing companies and will increase their market share.     

Ontology-based data integration and decision support for product e-Design

Currently, computer-based support tools are widely used to facilitate the design process and have the potential to reduce design time, decrease product cost and enhance product quality. Although there are promising information systems to manage product lifecycle and product-related data, including product data management (PDM) and product lifecycle management (PLM), significant limitations still exist, where information required to make decisions may not be available, may be lacking consistency, and may not be expressed in a general way for sharing between systems. Moreover, there remains little support for decision making that considers multiple complex technical and economical criteria, relations, and objectives in product design. To address these problems, this paper presents a framework for an ontology-based data integration and decision support environment for e-Design. The framework can guide designers in the design process, can make recommendations, and can provide decision support for parameter adjustments.     

A framework for systems analysis for decision support systems

Comprehensive and elaborate systems analysis techniques have been developed in the past of routine and operational information systems. Developing support systems for organizational decision-making requires new tools and methodologies. We present a new framework for data collection and decision analysis which is useful for developing decision support systems. This task analysis methodology encompasses (1) event analysis, (2) participant analysis, and (3) decision content analysis. With a proper coding manual, it provides a framework for collecting relevant and detailed information required for decision support design and implementation. Further research is suggested for application and evaluation of the methodology in real-life DSS environments.     

基于云计算的营销决策支持系统

设计并实施了一种基于云计算的营销决策支持系统,和其他管理决策子系统发生交互,共同构成了完整的现代企业经营决策支持系统.系统的数据库采用分布式设计,使得系统既有独立处理本地数据库的能力,也可读取异地数据库中的数据.系统模型库包含多种营销因素的决策模型,并采用模型组合的思想,将复杂的决策问题通过模型之间的组合来实现.在流程设计上充分考虑人机交互,将用户的经验判断纳入到决策过程中.完成了系统的开发,并用仿真数据进行了系统测试,结果表明系统基本运行稳定,各子模块衔接良好,与其他子系统实现了数据共享.     

Decision Tree Algorithm for Precision Marketing via Network Channel

With the development of e-commerce, more and more enterprises attach importance to precision marketing for network channels. This study adopted the decision tree algorithm in data mining to achieve precision marketing. Firstly, precision marketing and C4.5 decision tree algorithm were briefly introduced. Then e-commerce enterprise A was taken as an example. The data from January to June 2018 were collected. Four attributes including age, income, occupation and educational background were selected for calculation and decision tree was established to extract classification rules.The results showed that the consumers of the products of the company were high-income young and middle-aged people, middle-income young people, middle-income middle-aged and elderly people with a college degree or above, low-income middle-aged people with a college degree or above and low-income elderly people with a state-owned enterprise. After precision marketing to these customers, it was found that the monthly sales volume of the enterprise increased by 22.82% and the marketing cost decreased by 28.21%, which verified the effectiveness and application value of precision marketing and showed that the decision tree algorithm could provide enterprises with decision support in precision marketing.