基于知识挖掘的企业管理集成系统研究
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摘要
知识经济是以知识为基础的一种新型的富有生命力的经济形态,知识不仅是新经济发展的动力,也是现代社会进步的重要资源之一。而现代科技所表现出的高度分化和高度综合的特点,决定了任何单一组织都难以同时具备创新所需要的知识和能力。知识转移、挖掘的方法与模型能有效利用智能计算原理来加快知识的发现、分类、提取、识别等过程,具有智能化、动态化、网络化等特点,在客户管理、企业资源计划、供应链等知识管理中具有重要的应用前景。
本文以智能知识管理为主要研究对象,以知识转移、挖掘、管理理论为基础,以提高知识发现、分类、提取、识别的效率与效果为目的,对知识管理的理论体系作了全面、系统的总结与归纳,运用管理科学、信息技术等学科的内容与方法,对知识转移、挖掘的方法进行了探讨,并结合具体的管理应用实例建立具体的知识管理系统,取得了一定的研究进展。论文研究工作主要体现在以下几个方面：
首先,简要描述了本文的研究背景、研究的目的和意义意义和主要研究内容及创新点,并对整个论文架构进行扼要介绍。对知识与知识管理、知识转移、知识发现的含义、国内外理论研究与应用的发展现状及其知识转移方法与模型进行了分析与比较。
其次,根据知识发现和知识转移的目的和要求,利用背景理论和先验知识在知识表示与运行效率之间相均衡的基础上,提出了一种基于个体免疫与群体进化机制于一体的一种高效的全局优化搜索算法,着重新知识的发现和对高级规则的预测,有利于进化群体的相对稳定和整体性能的提高,并可以在规则提取过程中保持较高的精确度。
第三,针对客户知识管理系统中对知识发现与挖掘的目标与任务,结合数据挖掘技术与方法的特征与客户知识管理的特点,运用关联规则方法开发与研究了客户知识挖掘系统,并给出了具体算法与程序。
第四,在霍尔三维结构分析的基础上,将ERP与KMS在方法论层面进行比较分析,提出了一种基于企业资源计划的知识管理系统。通过对基于ERP和KMS的知识要素的动力学分析,对系统进行动态的模拟,以观察系统在不同的组织状态、不同的参数、不同的知识要素输入时所表现的行为和趋势,从而研究知识转移结构和动态行为,获得丰富的信息,为选择最优的或次优的方案提供有力工具。
第五,在对风险知识发现、分类的基础上,将定性分析与定量研究相结合,在对供应链风险及其特征描述的基础上,分析了供应链风险管理的意义和重要性,将模糊优化与知识挖掘的方法相结合,建立供应链风险决策优化模型,以辅助供应链企业降低风险,提高抗风险能力。
第六,从企业管理的目标以及知识需求的角度,阐述了ERP、SCM、CRM综合系统规划的必要性和可行性,从知识挖掘的角度提出了综合系统的基本框架和实施思路、技术难点与重点。并结合数据仓库技术从宏观的角度,建立ERP、SCM、CRM综合系统系统,以实现全面、实时的数据分析、处理、控制、决策管理。
最后,对全文研究内容进行了总结,指出研究工作中存在的不足,明确了下一步的研究方向。
Being a new form of economy, Knowledge Based Economy not only drives the development of economy itself but also emerges as a very import resource to evaluate the progress of modern society. However, the characteristics of high technologies, which poses highly integrated yet polarized features, leads to that no single organization is capable to have both knowledge and ability for Business Innovation. Therefore, employing the algorithms and models from knowledge transform and knowledge mining can effectively utilize computing power to speed up knowledge discovery, classification, extraction and recognition. These intelligent, dynamic and networking algorithms have broad prospects in many knowledge management research areas including customer management, Enterprise Resource Planning and supply chain.
With knowledge transform, mining and management as the foundation, this thesis targets at knowledge discovery, classification, extraction and recognition in aspects of both performance and effects to provide an overall view in the following areas:review of systematic theory of knowledge management, combining management and information technology to discuss knowledge transform and mining. Furthermore, a few case studies are adopted to build specific knowledge management system. The thesis is organized as follows:
First of all, it briefly describes the background, research objective and motivation of knowledge based economy. Then, it reviews the literatures of the field to analyze and compare the current research status and applications regarding to the knowledge management, transform and discovery.
Secondly, we use background theory and prior knowledge on the basis of knowledge expression and algorithm efficiency to present an efficient global optimization searching algorithm based on individual immunity and group evolution. The proposed algorithm emphasizes the discovery of new knowledge and the prediction of advanced rules, which promotes the stability and overall performance of the group. In addition, this algorithm can also provide relative high precision during the rule extraction process.
In a further step, regarding to the objective of knowledge discovery in customer knowledge management system, this thesis applies data mining technology over customer knowledge management through employing association rule mining. The built customer knowledge discovery system is presented in this section along with the relative algorithm and source code.
In addition, based on Hall three dimensions structure, we compare ERP and KMS in the level of research methodology. Then, a new knowledge management system based on enterprise resource planning is proposed. By using the kinetic analysis of important knowledge factors of ERP and KMS, the system is then dynamically simulated and observed with various parameters and knowledge inputs to evaluate the system behavior and trends. As a result, the knowledge transform can be studied to choose optimal or second best solutions.
In the fifth part of this thesis, it puts qualitative and quantitative analysis together to inspect supply chain risk management based on risk knowledge discovery and classification. Next, we apply fuzzy optimization to data mining methodology in order to build supply chain risk decision optimization model, which can be used to reduce the supply chain risk and enhance risk resistance capability.
Last but not least, this section discusses the necessity and feasibility of overall system planning of ERP, SCM and CRM from the view of enterprise management and knowledge demand. Additionally, this section proposes an overall system framework, deployment plan, technology difficulty and priority. Moreover, it uses data warehouse technology to macroscopically build ERP, SCM and CRM system so that the real time data analysis, processing, management and decision can be achieved.
The last section concludes and discusses step-wise future works. Some inadequate points of this study are also illustrated to expect further improvement.
本文以智能知识管理为主要研究对象,以知识转移、挖掘、管理理论为基础,以提高知识发现、分类、提取、识别的效率与效果为目的,对知识管理的理论体系作了全面、系统的总结与归纳,运用管理科学、信息技术等学科的内容与方法,对知识转移、挖掘的方法进行了探讨,并结合具体的管理应用实例建立具体的知识管理系统,取得了一定的研究进展。论文研究工作主要体现在以下几个方面：
首先,简要描述了本文的研究背景、研究的目的和意义意义和主要研究内容及创新点,并对整个论文架构进行扼要介绍。对知识与知识管理、知识转移、知识发现的含义、国内外理论研究与应用的发展现状及其知识转移方法与模型进行了分析与比较。
其次,根据知识发现和知识转移的目的和要求,利用背景理论和先验知识在知识表示与运行效率之间相均衡的基础上,提出了一种基于个体免疫与群体进化机制于一体的一种高效的全局优化搜索算法,着重新知识的发现和对高级规则的预测,有利于进化群体的相对稳定和整体性能的提高,并可以在规则提取过程中保持较高的精确度。
第三,针对客户知识管理系统中对知识发现与挖掘的目标与任务,结合数据挖掘技术与方法的特征与客户知识管理的特点,运用关联规则方法开发与研究了客户知识挖掘系统,并给出了具体算法与程序。
第四,在霍尔三维结构分析的基础上,将ERP与KMS在方法论层面进行比较分析,提出了一种基于企业资源计划的知识管理系统。通过对基于ERP和KMS的知识要素的动力学分析,对系统进行动态的模拟,以观察系统在不同的组织状态、不同的参数、不同的知识要素输入时所表现的行为和趋势,从而研究知识转移结构和动态行为,获得丰富的信息,为选择最优的或次优的方案提供有力工具。
第五,在对风险知识发现、分类的基础上,将定性分析与定量研究相结合,在对供应链风险及其特征描述的基础上,分析了供应链风险管理的意义和重要性,将模糊优化与知识挖掘的方法相结合,建立供应链风险决策优化模型,以辅助供应链企业降低风险,提高抗风险能力。
第六,从企业管理的目标以及知识需求的角度,阐述了ERP、SCM、CRM综合系统规划的必要性和可行性,从知识挖掘的角度提出了综合系统的基本框架和实施思路、技术难点与重点。并结合数据仓库技术从宏观的角度,建立ERP、SCM、CRM综合系统系统,以实现全面、实时的数据分析、处理、控制、决策管理。
最后,对全文研究内容进行了总结,指出研究工作中存在的不足,明确了下一步的研究方向。
Being a new form of economy, Knowledge Based Economy not only drives the development of economy itself but also emerges as a very import resource to evaluate the progress of modern society. However, the characteristics of high technologies, which poses highly integrated yet polarized features, leads to that no single organization is capable to have both knowledge and ability for Business Innovation. Therefore, employing the algorithms and models from knowledge transform and knowledge mining can effectively utilize computing power to speed up knowledge discovery, classification, extraction and recognition. These intelligent, dynamic and networking algorithms have broad prospects in many knowledge management research areas including customer management, Enterprise Resource Planning and supply chain.
With knowledge transform, mining and management as the foundation, this thesis targets at knowledge discovery, classification, extraction and recognition in aspects of both performance and effects to provide an overall view in the following areas:review of systematic theory of knowledge management, combining management and information technology to discuss knowledge transform and mining. Furthermore, a few case studies are adopted to build specific knowledge management system. The thesis is organized as follows:
First of all, it briefly describes the background, research objective and motivation of knowledge based economy. Then, it reviews the literatures of the field to analyze and compare the current research status and applications regarding to the knowledge management, transform and discovery.
Secondly, we use background theory and prior knowledge on the basis of knowledge expression and algorithm efficiency to present an efficient global optimization searching algorithm based on individual immunity and group evolution. The proposed algorithm emphasizes the discovery of new knowledge and the prediction of advanced rules, which promotes the stability and overall performance of the group. In addition, this algorithm can also provide relative high precision during the rule extraction process.
In a further step, regarding to the objective of knowledge discovery in customer knowledge management system, this thesis applies data mining technology over customer knowledge management through employing association rule mining. The built customer knowledge discovery system is presented in this section along with the relative algorithm and source code.
In addition, based on Hall three dimensions structure, we compare ERP and KMS in the level of research methodology. Then, a new knowledge management system based on enterprise resource planning is proposed. By using the kinetic analysis of important knowledge factors of ERP and KMS, the system is then dynamically simulated and observed with various parameters and knowledge inputs to evaluate the system behavior and trends. As a result, the knowledge transform can be studied to choose optimal or second best solutions.
In the fifth part of this thesis, it puts qualitative and quantitative analysis together to inspect supply chain risk management based on risk knowledge discovery and classification. Next, we apply fuzzy optimization to data mining methodology in order to build supply chain risk decision optimization model, which can be used to reduce the supply chain risk and enhance risk resistance capability.
Last but not least, this section discusses the necessity and feasibility of overall system planning of ERP, SCM and CRM from the view of enterprise management and knowledge demand. Additionally, this section proposes an overall system framework, deployment plan, technology difficulty and priority. Moreover, it uses data warehouse technology to macroscopically build ERP, SCM and CRM system so that the real time data analysis, processing, management and decision can be achieved.
The last section concludes and discusses step-wise future works. Some inadequate points of this study are also illustrated to expect further improvement.
引文
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