An Intelligent Decision Support System Generator

The focus of this paper is on a new concept framework and an architecture of an intelligent decision support syetem generator (DSSG). The framework results from a synthesis of two existing frameworks: Spragae and Bonczek, while the architecture is a rooted partial order network. From our experience which comes out of the project of DSSG, we consider that they are keys of further research and development of DSS.

Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

Method for designing organization decision support system framework

The concept of organization decision support system （ODSS） is defined according to practical applications and novel understanding. And a framework for ODSS is designed. The framework has three components： infrastructure, decision-making process and decision execution process. Infrastructure is responsible to transfer data and information. Decision-making process is the ODSS＇s soul to support decision-making. Decision execution process is to evaluate and execute decision results derived from decision-making process. The framework presents a kind of logic architecture. An example is given to verify and analyze the framework. The analysis shows that the framework has practical values, and has also reference values for understanding ODSS and for theoretical studies.

Applying the Technology Acceptance Model (TAM) in Information Technology System to Evaluate the Adoption of Decision Support System

With the beginning of the information systems’ spreading, people started thinking about using them for making business decisions. Computer technology solutions, such as the Decision Support System, make the decision-making process less complex and simpler for problem-solving. In order to make a high-quality business decision, managers need to have a great deal of appropriate information. Nonetheless, this complicates the process of making appropriate decisions. In a situation like that, the possibility of using DSS is quite logical. The aim of this paper is to find out the intended use of DSS for medium and large business organizations in USA by applying the Technology Acceptance Model (TAM). Different models were developed in order to understand and predict the use of information systems, but the information systems community mostly used TAM to ensure this issue. The purpose of the research model is to determine the elements of analysis that contribute to these results. The sample for the research consisted of the target group that was supposed to have completed an online questionnaire about the manager’s use of DSS in medium and large American companies. The information obtained from the questionnaires was analyzed through the SPSS statistical software. The research has indicated that, this is primarily used due to a significant level of Perceived usefulness and For the Perceived ease of use.

Design and Implementation of the Employment Management Decision Support System based on Machine Learning

To address the challenges of current college student employment management,this study designed and implemented a machine learning-based decision support system for college student employment management.The system collects and analyzes multidimensional data,uses machine learning algorithms for prediction and matching,provides personalized employment guidance for students,and provides decision support for universities and enterprises.The research results indicate that the system can effectively improve the efficiency and accuracy of employment guidance,promote school-enterprise cooperation,and achieve a win-win situation for all parties.

Analysis and Study of Parallel Processing Mode inVLDB Decision Support System

Nowadays, many kinds of computer network data management systems have been built widely in China. People have realized widely that management information system (MIS) has brought a revolution to the management mechanism. Moreover, the managers of company need wide-range and comprehensive decision information more and more urgently which is the character of information explosion era. The needs of users become harsher and harsher in the design of MIS, and these needs have brought new problems to the general designers of MIS. Furthermore, the current method of traditional database development can't solve so big and complex problems of wide-range and comprehensive information processing. This paper proposes the adoption of parallel processing mode, the built of new decision support system (DSS) is to discuss and analyze the problems of information collection, processing and the acquirement of full-merit information with cross-domain and cross-VLDB (very-large database).

DEVELOPING EXPERT DECISION SUPPORT SYSTEM WTH VP-EXPERT AND LOTUS 1-2-3 IN RE-BLENDING BY USE

An expert decision support system (EDSS) for multi-bins balance and contro1 of orequality in production ore bins of some large-scale open pit iron mine in China has been developed byexpert svitem tool software VP-EXPERT and integration software LOTUS 1-2-3 in this paper. Itis known by practicing that a medium-scale EDSS constructed on microcomputer is completcly, feaasible by means of VP-EXEPERT to construct knowledge base system (KBS), LOTUS 1-2-3 tomake decision support system (DSS) and link them with BAT.

Research and Application of Maize Precision Intelligence Spatial Decision Support System

In order to solve the problem of the maze precision fertilizer,soil fertility evaluation,soil fertility classify and yield projections,the geographic information system with spatial information processing functions,spatial data mining techniques with spatial information analysis capabilities,expert system technology in the field of artificial intelligence,traditional information management systems and decision support system were effectively integrated in this study,and the statistical analysis method of GIS and data visualization were combined to design and implement the maize precise intelligent space decision-making system.This system had greatly improved the decision-making ability in agricultural production carried out by agricultural management.

The Implementation of Decision Support System for Realizing Effective Usability of CNC Operator Knowledge Capturing System

This article describes experimental evaluations of the authors＇ previous studies on the knowledge-based system （KBS） aimed at capturing and managing CNC （Computer Numerical Control） operator knowledge. The proposed KBS follow thinking steps of CNC operators when they assess machining parameters described in the CAM （Computer Aided Manufacturing） file before proceeding to CNC machining processes. Also, the decision support system equipped with expert system （ES） has been proposed to realize efficient knowledge capturing system and effective usability of captured knowledge, and to recommend actions and decisions. From the viewpoint of providing useful information, the KBS should be aware of context or constraints in which the user has to deal with. In this study, the usefulness of DSS （Decision Support System） and ES is experimentally evaluated using real cases. Comparing the results of the testing participants with and without the DSS and ES, the effectiveness and usefulness were demonstrated. In addition, it was shown that the proposed system is also useful to narrow the discrepancies between CAM and CNC operators, focusing on CNC milling operations.

A Model-Based, Aspiration-Led Decision Support System NY-IEDSS

An AI-aided simulation system embedded in a model-based, aspiration-led decision support system NY-IEDSS is reported. The NY-IEDSS is designed for mid-term development strategic study of the Nanyang Region in Henan, China, and is getting beyond its prototype stage under the decision maker's (the end user) orientation. The integration of simulation model system, decision analysis and expert system for decision support in the system implementation was reviewed. The intent of the paper is to provide insight as to how system capability and acceptability can be enhanced by this integration. Moreover, emphasis is placed on problem orientation in applying the method.

Method of Establishing Object-Oriented System Structure for Decision Support System

In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.

Multi-agent decision support system for missile defense based on improved PSO algorithm

Ballistic missile defense system (BMDS) is important for its special role in ensuring national security and maintaining strategic balance. Research on modeling and simulation of the BMDS beforehand is essential as developing a real one requires lots of manpower and resources. BMDS is a typical complex system for its nonlinear, adaptive and uncertainty characteristics. The agent-based modeling method is well suited for the complex system whose overall behaviors are determined by interactions among individual elements. A multi-agent decision support system (DSS), which includes missile agent, radar agent and command center agent, is established based on the studies of structure and function of BMDS. Considering the constraints brought by radar, intercept missile, offensive missile and commander, the objective function of DSS is established. In order to dynamically generate the optimal interception plan, the variable neighborhood negative selection particle swarm optimization (VNNSPSO) algorithm is proposed to support the decision making of DSS. The proposed algorithm is compared with the standard PSO, constriction factor PSO (CFPSO), inertia weight linear decrease PSO (LDPSO), variable neighborhood PSO (VNPSO) algorithm from the aspects of convergence rate, iteration number, average fitness value and standard deviation. The simulation results verify the efficiency of the proposed algorithm. The multi-agent DSS is developed through the Repast simulation platform and the constructed DSS can generate intercept plans automatically and support three-dimensional dynamic display of missile defense process.

Review of state-of-the-art decision support systems (DSSs) for prevention and suppression of forest fires

Forest ecosystems are our priceless natural resource and are a key component of the global carbon budget. Forest fires can be a hazard to the viability and sustainable management of forests with consequences for natural and cultural environments, economies, and the life quality of local and regional populations. Thus, the selection of strategies to manage forest fires, while considering both functional and economic efficiency, is of primary importance. The use of decision support systems(DSSs) by managers of forest fires has rapidly increased. This has strengthened capacity to prevent and suppress forest fires while protecting human lives and property. DSSs are a tool that can benefit incident management and decision making and policy, especially for emergencies such as natural disasters. In this study we reviewed state-of-the-art DSSs that use: database management systems and mathematical/economic algorithms for spatial optimization of firefighting forces; forest fire simulators and satellite technology for immediate detection and prediction of evolution of forest fires; GIS platforms that incorporate several tools to manipulate, process and analyze geographic data and develop strategic and operational plans.

Fuzzy Comprehensive Evaluation for Decision Making of Water Saving Irrigation System

A model of fuzzy comprehensive evaluation for water saving irrigation system (WSIS) decision making is proposed based on establishing an index system affected by six kinds of basic factors including qualitative and quantitative indexes. The object function of WSIS is set up by using the concept of fuzzy membership degree, it is to transform characteristic vector matrix into unify membership matrix and extending the least square method to the least of weighted distance square. The optimum weighted membership degree and the inferior weighted membership degree are used to solve the object function. This method effective solves the problem of classify for fuzzy attributive indexes and the problem of optimum for the set of different attributive indexes. A case study shows that the fuzzy comprehensive evaluation model is reasonable and effective in decision making for water saving irrigation system planning.

Study on the Decision Support System for Northing of Winter Wheat Cultivation in Hebei Province

[Objective] This study was to provide methods to improve the scientificity and informatization level of agricultural decision-making system based on the study of Decision Support System for ＂Northing of Winter Wheat＂ in Hebei Province （DSS- NWWH）. [Method] The functions, development process, operation guidance as well as input and output modes of DSSNWWH were introduced, and the simulated results of the system were verified by comparing with the actual situations. [Result] The decision support system established in this study could predict whether a wheat variety could live through the winter in a certain area of northern Hebei Province, as well as the growth conditions based on the previous meteorological data or local weather forecast, and provided corresponding cultivation and management measures, making it possible for the user to determine whether the variety could be planted in the region based on the predictions. [Conclusion] The established DSSNWWH in this study can effectively help decision makers make decisions, providing scientific instructions for the northing of winter wheat.

Importance Analysis of a Multi-state System Based on Direct Partial Logic Derivatives and Multi-valued Decision Diagrams

Importance analysis quantifies the critical degree of individual component. Compared with the traditional binary state system,importance analysis of the multi-state system is more aligned with the practice. Because the multi-valued decision diagram( MDD) can reflect the relationship between the components and the system state bilaterally, it was introduced into the reliability calculation of the multi-state system( MSS). The building method,simplified criteria,and path search and probability algorithm of MSS structure function MDD were given,and the reliability of the system was calculated. The computing methods of importance based on MDD and direct partial logic derivatives( DPLD) were presented. The diesel engine fuel supply system was taken as an example to illustrate the proposed method. The results show that not only the probability of the system in each state can be easily obtained,but also the influence degree of each component and its state on the system reliability can be obtained,which is conducive to the condition monitoring and structure optimization of the system.

Application of geographical information system technology to epidemiological surveillance and prevention and cure decision-making for SARS

Objective:To expound geographical information system (GIS) technology is a very important tool when it was employed to assist to present the distribution by time and place and the model of transmission of infectious disease. Methods: We illustrated the assistant decision-making support function of GIS with an example of the spatial decision support system for SARS controlling in Shaanxi province of China which was developed by us. Results: The spatial decision support system established by applying GIS technology fulfilled the needs of real-time collection and management and dissemination SARS information and of surveillance and analysis the epidemic situation of SARS. Conclusion: Occurrence and epidemic of diseases, implement prevention and intervention measures and collocation hygienic resources are all with the characteristic of the variation of time and space, therefore, GIS technology has become a powerful tool for identifying risk factors of diseases, providing clues of causation of diseases , evaluating the effects of intervention measures and drawing a health management plan.

Electronic market models for decision support systems on the Web

With the prevalence of the Web, most decision-makers are likely to use the Web to support their decision-making. Web-based technologies are leading a major stream of researching decision support systems (DSS). We propose a formal definition and a conceptual framework for Web-based open DSS (WODSS). The formal definition gives an overall view of WODSS, and the conceptual framework based on browser/broker/server computing mode employs the electronic market to mediate decision-makers and providers, and facilitate sharing and reusing of decision resources. We also develop an admitting model, a trading model and a competing model of electronic market in WODSS based on market theory in economics. These models reveal the key mechanisms that drive WODSS operate efficiently.

Feed back Mechanism in Decision Support Systems

Feedback mechanism is a specific feature of control systems, however, the similarity has been found in decision support systems. Just because of this, the DSS can provide a flexible learning and thinking environment, and help decision maker to solve semistructured and unstructured problems actively and creatively. In this paper, the role and type of the feedback in decision making are discussed from different point of view. This is also true in DSS because it supports decision making. The feedback design, especially the feedback interface design, is described through a case of practice DSS. Based on these points, the feedback mechanism is an important feature of DSS, and it is one of the differences between DSS and MIS.

Researches on an expert decision-making system of technology reformation schemes of a colliery

In this paper, an expert decision-making system of technology reformation schemes of a colliery (for short EDSTRC) is researched by comprehensively using ES and DSS principles and computer technique. The functional and logical structures of EDSTRC as well as its sub-systems are mainly designed, and its development and application environment are simply introduced. EDSTRC is consisted of eight main parts, i.e. data base (DB), knowledge base (KB), model base (MB), approach base (AB), graph base (GB), result base (RB), man-compute system (MCS), and problem-solved system (PSS). Through application of practical examples, it is proved that the EDSTRC’s prototype design is correct, its man-computer interface is amicable, and its applicable prospect is wider.