Shan Feng

An intelligent decision support system for fuzzy comprehensive evaluation of urban development

Abstract More applications that integrate knowledge-based decision support systems, artificial neural networks, and fuzzy systems are starting to appear, and interest in such integrated systems is growing rapidly. This paper presents an integrated system in which a knowledge-based decision support system is integrated with a multilayer artificial neural network for urban development. By integrating decision support systems, knowledge-based systems, artificial neural networks, and fuzzy systems, the system achieves improvements in the implementation of each, as well as increases in the scope of the application. The paper discusses the structure of the integrated system, as well as providing an example of decision support systems application.

Information visualization for intelligent decision support systems

To work efficiently with decision support systems (DSS), most users benefit from representation conversion, i.e. translating the specific outcome from the DSS, normally portrayed in a numerical format, into the universal language of the visual. In general, interpretation of data is much more intuitive if the results from the DSS are translated into charts, maps, and other graphical displays because visualization exploits our natural ability to recognize and understand visual patterns. In this paper we discuss the concept of visualization user interface (VUI) for DSS. A proprietary software system known as AniGraftool is introduced as an example of an information visualization application for DSS. In addition, a visualized information retrieval engine based on fuzzy control is proposed.

An agent-based geographical information system

In this paper, a prototype geographical information system (GIS) using agent-based technology is introduced. The system known as GXGIS uses agent-based architecture for interactability and scalability. An interface agent is developed to interactively assist the user with the query formation process. The agent has the capability of offering domain knowledge that is associated with a given query. The agent is also able to record a users troubleshooting experience and show it to the same user or other users as hints. Furthermore, an agent-based architecture with a two-tier mediator model in GIS is developed to satisfy the needs for interoperability among diverse application domains and integration of heterogeneous data sources. As a result, both qualitative and quantitative data can be integrated into GIS.

Using MLP networks to design a production scheduling system

This paper investigates the application of artificial neural networks to the problem of job shop scheduling with a scope of a deterministic time-varying demand pattern over a fixed planning horizon. The purpose of the research is to design and develop a job shop scheduling system (a scheduling software) that can generate effective job shop schedules using the multi-layered perceptron (MLP) networks. The contributions of this study include designing, developing, and implementing a production activity scheduling system using the MLP networks; developing a method for organizing sample data using a denotation bit to indicate processing sequence and processing time of a job simultaneously; using the back-propagation training process to control local minimal solutions; and developing a heuristics to improve and revise the initial production schedule. The proposed production activity schedule system is tested in a real production environment and illustrated in the paper with a sample case.

An object-oriented intelligent design tool to aid the design of manufacturing systems

Manufacturing systems design appears to be an excellent area for applying artificial intelligence (AI), object-oriented techniques and computer simulation methods, however, so far there have been limited research on integrating AI, object-oriented techniques and simulation techniques for manufacturing systems design. In this paper, an integrated approach for manufacturing systems design is introduced which consists of the developing and testing of alternative designs using an integrated system SBDSS. SBDSS mainly consists of two subsystems, Object Library Modeler and Simulation Engine with its manager. Using SBDSS, decision makers (DMs) can evaluate alternatives in manufacturing and production, e.g. annual production plan under certain circumstances through scenario simulations. DMs can also test a set of virtual organizations reflecting business process reengineering before a real change is made, as well as testing a virtual manufacturing process for a newly designed product. The paper describes three possible application cases including centralized versus decentralized organizational structure, global goal-oriented planning and highly integrated information systems to illustrate the flexibility of the system.

A novel Bayesian learning method for information aggregation in modular neural networks

Modular neural network is a popular neural network model which has many successful applications. In this paper, a sequential Bayesian learning (SBL) is proposed for modular neural networks aiming at efficiently aggregating the outputs of members of the ensemble. The experimental results on eight benchmark problems have demonstrated that the proposed method can perform information aggregation efficiently in data modeling.

An intelligent agent with layered architecture for operating systems resource management

Abstract: A software agent is defined as an autonomous software entity that is able to interact with its environment. Such an agent is able to respond to other agents and/or its environment to some degree, and has some sort of control over its internal state and actions. In belief–desire–intention (BDI) theory, an agents behavior is described in terms of a processing cycle. In this paper, based on BDI theory, the processing cycle is studied with a software feedback mechanism. A software feedback or loop-back control mechanism can perform functions without direct external intervention. A feedback mechanism can continuously monitor the output of the system under control (the target system), compare the result against preset values (goals of the feedback control) and feed the difference back to adjust the behavior of the target system in a processing cycle. We discuss the modeling and design aspects of an autonomous, adaptive monitoring agent with layered control architecture. The architecture consists of three layers: a scheduling layer, an optimizing layer and a regulating layer. Experimental results show that the monitoring agent developed for an e-mail server is effective.

Hybrid artificial intelligence approach to urban planning

Knowledge-based modeling and implementation of the various urban planning processes represent an intensive research area. This paper presents a hybrid artificial intelligence system using a knowledge-based approach, neural networks and fuzzy logic that automates the decision-making process in urban planning. The system is used for developing urban development alternatives based on real-world data. Results show that, by integrating knowledge-based systems, artificial neural networks and fuzzy systems, the system achieves improvements in the implementation of each respective system as well as an increase in the breadth of functionality within the application. With this approach, the best of three technologies can be compiled together to solve complex urban problems. We discuss the structure of the combined technologies, as well as providing examples of its application in the field of urban development.

Production research in China

yDepartment of Decision and Information Technologies, Villanova University, Villanova, PA 19085, USA zInstitute of Systems Engineering, Huazhong University of Science and Technology, Wuhan 430074, China }School of Business, University of Alberta, Edmonton, Alberta, Canada T6G 2E1; School of Management, Xian Jiaotong University, Xian 710049 #Department of Information Technology and Decision Sciences, Old Dominion University, Norfolk, VA 23529, USA yyGraduate School, Chinese Academy of Sciences, Beijing 100039, China zzSchool of Management, Huazhong University of Science and Technology, Wuhan 430074, China }}School of Economics and Business Administration, Chongqing University, Chongqing 400030, China

Fuzzy modeling of the medical treatment effects of superoxide dismutase

: In this paper, the effect of superoxide dismutase (SOD) in treating certain types of oral diseases is evaluated with a fuzzy relation composition method and a fuzzy integral method. Evaluation results demonstrate that SOD is effective in treating oral diseases. It is found also that SOD and SOD-containing complex enzyme are proven treatments for certain types of oral diseases. The effects of some applications are compared and discussed.