Construction and realization of the knowledge base and inference engine of an IDSS model for air-conditioning cooling/heating sources selection

The knowledge representation mode and inference control strategy were analyzed according to the specialties of air-conditioning cooling/heating sources selection. The constructing idea and working procedure for knowledge base and inference engine were proposed while the realization technique of the C language was discussed. An intelligent decision support system (IDSS) model based on such knowledge representation and inference mechanism was developed by domain engineers. The model was verified to have a small kernel and powerful capability in list processing and data driving, which was successfully used in the design of a cooling/heating sources system for a large-sized office building.

Intelligent decision support system of operation-optimization in copper smelting converter

An artificial intelligence technique was applied to the optimization of flux adding systems and air blasting systems, the display of on line parameters, forecasting of mass and compositions of slag in the slagging period, optimization of cold material adding systems and air blasting systems, the display of on line parameters, and the forecasting of copper mass in the copper blow period in copper smelting converters. They were integrated to build the Intelligent Decision Support System of the Operation Optimization of Copper Smelting Converter(IDSSOOCSC), which is self learning and self adaptating. Development steps, monoblock structure and basic functions of the IDSSOOCSC were introduced. After it was applied in a copper smelting converter, every production quota was clearly improved after IDSSOOCSC had been run for 4 months. Blister copper productivity is increased by 6%, processing load of cold input is increased by 8% and average converter life span is improved from 213 to 235 furnace times.

Research of IDSS Architecture Based on Hybrid Systems

This paper discusses the necessity of building IDSS on hybrid systems, and adopts XML technology to manage isomeric knowledge in hybrid systems. The paper proposes a new architecture of hybrid systems based IDSS whose core system is isomeric knowledge system. The architecture is composed of knowledge component, problems processing system, data component and intelligent user interface. This new architecture aims to enhance the capability of integrating hybrid systems, to improve the supporting effectiveness of decision-making and the intelligent level of IDSS, and tries a new way to elevate the system’s ability of handling and learning knowledge.

Methodological Approaches to Development and Implementation of Multi-agents Investment DSS Using JADE Platform

In these latter days software agents are used for the development and implementation of intellectual decision support systems. In order to implement intelligence in a system some or several dozen of software agents are used and the made system becomes multi-agent. For the development of these systems a set of methodologies, i.e., the sequence of consequent steps of analysis, designing and implementation, is offered. The carried out analysis of the methodologies showed that as a rule they are limited by the spectrum of their pending problem （within the pales of the requirements of specific applied task, within the pales of the possibilities of technical implementation） or within the pales of amount of detail. The variety of methodologies is influenced by the fact that for the development of these systems the requirements and attitudes are offered by the specialists of related spheres such as software, numeral intellect engineers. In the course of the development of hardware and software appeared possibilities to implement mobile multi-agents systems, however, there is no one united mobile multi-agent systems design methodology, whereas existing systems are underdeveloped and their number is small. In this article we introduce the course of the designing of an intellectual real time multi-agent investment management decision support information system adapting and combining some methodologies where the choice to use either communicating or mobile agents is the question of rather technical implementation than methodological. In the article we introduce two ways of system implementation by JADE platform： the first one-using communicating agents, and the second one-using mobile agents.

A New Approach for Knowledge Discovery in Distributed Databases Using Fragmented Data Storage Model

Since the early 1990, significant progress in database technology has provided new platform for emerging new dimensions of data engineering. New models were introduced to utilize the data sets stored in the new generations of databases. These models have a deep impact on evolving decision-support systems. But they suffer a variety of practical problems while accessing real-world data sources. Specifically a type of data storage model based on data distribution theory has been increasingly used in recent years by large-scale enterprises, while it is not compatible with existing decision-support models. This data storage model stores the data in different geographical sites where they are more regularly accessed. This leads to considerably less inter-site data transfer that can reduce data security issues in some circumstances and also significantly improve data manipulation transactions speed. The aim of this paper is to propose a new approach for supporting proactive decision-making that utilizes a workable data source management methodology. The new model can effectively organize and use complex data sources, even when they are distributed in different sites in a fragmented form. At the same time, the new model provides a very high level of intellectual management decision-support by intelligent use of the data collections through utilizing new smart methods in synthesizing useful knowledge. The results of an empirical study to evaluate the model are provided.

大数据技术在流域梯级水电企业的应用

随着信息技术的不断发展，传统行业也能够生产出与大型电商企业同样数量级的数据。一方面，原始数据背后的巨大价值等待着人们去挖掘，另一方面，对于数据处理的难度也是制约这一进程的关键因素。大数据技术的出现，改变了人们认识客观事物规律的方法，即从以前的对事物由大到小的逐步剖析演变为将事物放到更大的环境中去寻找共性、特性与趋势。新一轮数字化浪潮已经到来，作为传统行业的水电企业，如何把握住历史机遇、利用大数据技术将企业经营管理水平提高到一个新的高度，值得所有从业人员的思考。