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116 An intelligent economic decision support system IEDSS for development strategic design
Abstracts
1088
111 Intelligent Management System (]MS) Xuyan Tu, Xiushan Li, K.Y. Sun, Wei Lln, pp 145-151
116 An Intelligent Economic Decision Support System IEDSS for Development Strategic Design Feng Shan, pp 181-186
The Intelligent Management System (IMS) is the 4th generation of computer-aided management systems. It is developed by the methodology of large system cybernetics. In this paper, the main ideas concerning the methods and technology for the design and implementation of IMS, and the architecture, performance and application of IMS are discussed.
The paper presents the theoretical background and conceptual framework for an intelligent decision support system for the economic development strategy of China (national and/or regional). AI technology plays prominent and direct roles in the implementauon. The decision maker and the system DSS work cooperatively to reach an optimal or sub-optimal solution. The "intelligent" features of the system are configured with an integrated knowledge base management system IK.BMS, and an intuitive man-machine interface, M-M. The IK.BMS is essentially an object-oriented (or frame/rule-based) system and the desired M-M functions are dynamically determined. The M-M is designed to facilitate easy utilization and access.
112 Application of Intelligent Management System in Foreign Trade Contract LlnLin Cheng, XIYuan Liu, ZhlMing Chen, Ping Chen, XueFeng Zheng, Xiao Chuan Pu, HuiBing Li pp 153-158 This paper discusses the development schemes, operating principles, key technologies and operation flows relevant to the system structure, knowledge representation, inference mechanism and intelligent interface for an Intelligent Management System for foreign trade contracts. This development is taken as an attempt toward the application of fourth-generation CAMS.
113 Applying IMS to Management Systems of Daqing Oil Field - Oil-Mine IMS Li Xiushan, Tu Xuyan, Sun Kulylng, Zeng Shuquan, Yu Ylhai, pp 159-165
117 Development of a Primary Prototype of SXSES-DSS
S.J. Llu, C.Z. Han, B.W. Wan, pp 187-190 This paper describes the required functions and development tactics for the SXSES-DSS, and outlines the general design of the system and a developed primary prototype based on the design. It is pointed out that the system is an intelligent, distributed, integrated group DSS based on a model base, a knowledge base, an algorithm base, a graph base and a text base, etc., and has a two-layer coordination structure.
This paper discusses the overall goal, system design, application of key techniques and development of OIMS - an Oil-Mine Intelligent Management System.
114 Intelligent Telecommunication System Integration D.T. Lee, pp 167-173 Information has emerged as an important resource in almost any organization. Telecommunication has become a dominant component of information technologies. In the past, information technologies were treated in isolation. Now, they have almost reached maturity. It is no longer practical to think of computing, telecommunication, artificial intelligence, and intelligent databases as separate entities. They should be integrated to create synergetic effects. The impact of this integration on human civilization will be tremendous and revolutionary. The purpose of this paper is to conduct an intensive investigation of the related components of the integrated intelligent telecommunication network system, and the feasibility of such system integration.
118 The Design of a Forecasting Model Selection Expert System Liang Wang, G. Libert, pp 191-196 A problem facing the users of forecasting systems is the selection of (an) appropriate model(s) for the application at hand. It is especially acute for high-density, real-time and multiple-data-set environments such as manufacturing. In this paper, an expert system for forecasting model selection is developed. Detailed discussion of three components of this system - the knowledge base, the inference engine, and the user interface (explanation facility) - is included. A new inference algorithm is proposed, which is capable not only of dealing with uncertainty of information, but also of handling logical symbols in parallel.
119 EDSS A Framework of Whole-Brained DSS Yunsheng Ma, Qiusheng Zheng, D.T. Lee, pp 197-200 -
115 Decision Support System Based on General Modeling E. Wu, Yonghong Chen, pp 175-179 Aimed at the coordination of decision resources such as model, data, algorithm and knowledge in a decision support system, the paper advances a DSS framework based on the idea of general modeling. A knowledgedriven structure is a unique characteristic in this system. A modular series for problem solving is constituted by the inference rule set. A DSS oriented to macroeconomies was developed using the idea.
Decision support systems have been designed for decision support for over two decades. They are still in an infant stage. Expert systems have suddenly emerged as one of the decision support tools. Since both types seek to improve the quality of the decision, they need to be integrated for better performance. Unfortunately, the integration is constrained by human know-how. The purpose of this paper is to identify the similarities and differences between the two, and to lay down a framework for developing an integrated system which can be used to enhance decision-making.
1088
111 Intelligent Management System (]MS) Xuyan Tu, Xiushan Li, K.Y. Sun, Wei Lln, pp 145-151
116 An Intelligent Economic Decision Support System IEDSS for Development Strategic Design Feng Shan, pp 181-186
The Intelligent Management System (IMS) is the 4th generation of computer-aided management systems. It is developed by the methodology of large system cybernetics. In this paper, the main ideas concerning the methods and technology for the design and implementation of IMS, and the architecture, performance and application of IMS are discussed.
The paper presents the theoretical background and conceptual framework for an intelligent decision support system for the economic development strategy of China (national and/or regional). AI technology plays prominent and direct roles in the implementauon. The decision maker and the system DSS work cooperatively to reach an optimal or sub-optimal solution. The "intelligent" features of the system are configured with an integrated knowledge base management system IK.BMS, and an intuitive man-machine interface, M-M. The IK.BMS is essentially an object-oriented (or frame/rule-based) system and the desired M-M functions are dynamically determined. The M-M is designed to facilitate easy utilization and access.
112 Application of Intelligent Management System in Foreign Trade Contract LlnLin Cheng, XIYuan Liu, ZhlMing Chen, Ping Chen, XueFeng Zheng, Xiao Chuan Pu, HuiBing Li pp 153-158 This paper discusses the development schemes, operating principles, key technologies and operation flows relevant to the system structure, knowledge representation, inference mechanism and intelligent interface for an Intelligent Management System for foreign trade contracts. This development is taken as an attempt toward the application of fourth-generation CAMS.
113 Applying IMS to Management Systems of Daqing Oil Field - Oil-Mine IMS Li Xiushan, Tu Xuyan, Sun Kulylng, Zeng Shuquan, Yu Ylhai, pp 159-165
117 Development of a Primary Prototype of SXSES-DSS
S.J. Llu, C.Z. Han, B.W. Wan, pp 187-190 This paper describes the required functions and development tactics for the SXSES-DSS, and outlines the general design of the system and a developed primary prototype based on the design. It is pointed out that the system is an intelligent, distributed, integrated group DSS based on a model base, a knowledge base, an algorithm base, a graph base and a text base, etc., and has a two-layer coordination structure.
This paper discusses the overall goal, system design, application of key techniques and development of OIMS - an Oil-Mine Intelligent Management System.
114 Intelligent Telecommunication System Integration D.T. Lee, pp 167-173 Information has emerged as an important resource in almost any organization. Telecommunication has become a dominant component of information technologies. In the past, information technologies were treated in isolation. Now, they have almost reached maturity. It is no longer practical to think of computing, telecommunication, artificial intelligence, and intelligent databases as separate entities. They should be integrated to create synergetic effects. The impact of this integration on human civilization will be tremendous and revolutionary. The purpose of this paper is to conduct an intensive investigation of the related components of the integrated intelligent telecommunication network system, and the feasibility of such system integration.
118 The Design of a Forecasting Model Selection Expert System Liang Wang, G. Libert, pp 191-196 A problem facing the users of forecasting systems is the selection of (an) appropriate model(s) for the application at hand. It is especially acute for high-density, real-time and multiple-data-set environments such as manufacturing. In this paper, an expert system for forecasting model selection is developed. Detailed discussion of three components of this system - the knowledge base, the inference engine, and the user interface (explanation facility) - is included. A new inference algorithm is proposed, which is capable not only of dealing with uncertainty of information, but also of handling logical symbols in parallel.
119 EDSS A Framework of Whole-Brained DSS Yunsheng Ma, Qiusheng Zheng, D.T. Lee, pp 197-200 -
115 Decision Support System Based on General Modeling E. Wu, Yonghong Chen, pp 175-179 Aimed at the coordination of decision resources such as model, data, algorithm and knowledge in a decision support system, the paper advances a DSS framework based on the idea of general modeling. A knowledgedriven structure is a unique characteristic in this system. A modular series for problem solving is constituted by the inference rule set. A DSS oriented to macroeconomies was developed using the idea.
Decision support systems have been designed for decision support for over two decades. They are still in an infant stage. Expert systems have suddenly emerged as one of the decision support tools. Since both types seek to improve the quality of the decision, they need to be integrated for better performance. Unfortunately, the integration is constrained by human know-how. The purpose of this paper is to identify the similarities and differences between the two, and to lay down a framework for developing an integrated system which can be used to enhance decision-making.