村庄布局优化DSS与GIS的系统集成

通过村庄布局优化决策支持系统案例着重讨论了ＧＩＳ与ＤＳＳ的系统集成。介绍了通过地理信息库与数据库和模型库的链接实现地图上村庄信息的显示和查询,以及村庄合并搬迁后在地图上的动态变化。使用户的决策活动更直观方便,具有较强的实用性和创新性。该系统不仅在实际应用中取得了良好的效果,而且具有一定的扩展前景。     

Searching for simplified farmers' crop choice models for integrated watershed management in Thailand: A data mining approach

This study used the C4.5 data mining algorithm to model farmers' crop choice in two watersheds in Thailand. Previous attempts in the Integrated Water Resource Assessment and Management Project to model farmers' crop choice produced large sets of decision rules. In order to produce simplified models of farmers' crop choice, data mining operations were applied for each soil series in the study areas. The resulting decision trees were much smaller in size. Land type, water availability, tenure, capital, labor availability as well as non-farm and livestock income were found to be important considerations in farmers' decision models. Profitability was also found important although it was represented in approximate ranges. Unlike the general wisdom on farmers' crop choice, these decision trees came with threshold values and sequential order of the important variables. The decision trees were validated using the remaining unused set of data, and their accuracy in predicting farmers' decisions was around 84%. Because of their simple structure, the decision trees produced in this study could be useful to analysts of water resource management as they can be integrated with biophysical models for sustainable watershed management.     

A framework for integrated catchment assessment in northern Thailand

Experience in northern Thailand suggests that rapid commercialisation of upland catchments can have significant, and often unpredictable, social, economic and biophysical impacts. The purpose of this paper is to describe a multi-disciplinary methodology that is being used to assess water resource management in northern Thailand. The methodology identifies and integrates contributions from biophysical, economic and socio-cultural disciplines in the development of a scenario-modeling Decision Support System (DSS). The key modeling “unit” in the DSS is the “Resources Management Unit” (RMU). The RMU situates the socially and economically constituted agricultural household (the main decision maker) in its biophysical environment. This paper describes the application of the methodology to a case study of water allocation between upstream and downstream villages in the small subcatchment of Mae Uam in northern Thailand. It concludes with an indication of the potential for the methodology to be applied in other catchments.     

基于辅助决策支持的虚拟经济性运行系统的设计

火力发电厂机组经济性运行辅助决策系统采用了多元非线性回归数学模型和模型优化技术建立虚拟经济性运行机组,实时动态的优化机组的经济性运行参数,该设计思想在决策分析方面的研究和应用中有一定的特色。在分析、设计阶段中,使用了统一建模语言UML来简单描述其过程。     

基于GIS的土地适宜性评价模型的改进

首先介绍了基于GIS的常规土地适宜性评价模型(LSEM),并指出它有两个主要缺点:一是同一级别内的不同类别没有显示出评分的区别;二是不同级别的分界处评分差别过份拉大。然后,利用专家系统中确信度(Certainty Factor)概念对其进行了改进。研究表明,经过改进的LSEM具有包含信息更丰富、更精确的特点,能为决策者提供更多的选择余地。     

Integrating scientific modeling and supporting dynamic hazard management with a GeoAgent-based representation of human–environment interactions: A drought example in Central Pennsylvania, USA

Recent natural disasters indicate that modern technologies for environmental monitoring, modeling, and forecasting are not well integrated with cross-level social responses in many hazard-management systems. This research addresses this problem through a Java-based multi-agent prototype system, GeoAgent-based Knowledge System (GeoAgentKS). This system allows: (1) computer representation of institutional regulations and behavioral rules used by multiple social institutions and individuals in cross-level human–environment interactions, (2) integration of this representation with scientific modeling of dynamic hazard development, and (3) application of automated reasoning that suggests to users the appropriate actions for supporting cooperative social responses. This paper demonstrates the software architecture of GeoAgentKS and presents such an integrated approach by modeling the drought management processes in Central Pennsylvania, USA. The results show that it is possible to use GeoAgentKS to represent multilevel human–environment interactions and to use those interactions as input to decision making in hazard management.     

Contracting cleaning services in a European public underground transportation company with the aid of a DSS

This paper deals with the selection of a supplier for cleaning services in a European public underground transportation company as established in the European Community directives, where several conflicting criteria, such as improving service levels and reducing total service costs, must be taken into account simultaneously. The problem is analyzed in depth using the decision analysis methodology, and a decision support system, the Generic Multi-Attribute Analysis system, is used to allay the operational difficulties involved. This system can deal with incomplete information about decision-maker preferences, accounts for uncertainty about offer performance, and uses so-called decision-making with partial information to identify the best offer, taking advantage of imprecise inputs.     

Development of a decision support system for service delivery

Most traditional service delivery models were developed to solve single objective problems. While the disaster recovery task usually needed the consideration of multiple objectives (e.g. the total waiting time, the total weighted time of travelling, the fairness of resource distribution). Therefore, the traditional models can't completely support the disaster recovery task. In the real world, the assignments of service delivery are always performed by the vehicle dispatchers or truck drivers based on their experiences. However, the intuitive assignment methods are lacking a mathematic basis. They may be efficient but not necessarily effective. In order to provide an efficient and effective decision support system, this study has focused on the general expression of performances for service delivery and modifies the traditional delivery models by rule-inference techniques. The objective of this paper is to describe how a decision support system has been developed to achieve the performance requirement in emergency service delivery tasks, while traditional routing algorithms are modified and software techniques are utilized under a PC-based environment. Furthermore, some directions for future improvement are proposed.     

A simulation-based risk network model for decision support in project risk management

This paper presents a decision support system (DSS) for the modeling and management of project risks and risk interactions. This is a crucial activity in project management, as projects are facing a growing complexity with higher uncertainties and tighter constraints. Existing classical methods have limitations for modeling the complexity of project risks. For example, some phenomena like chain reactions and loops are not properly taken into account. This will influence the effectiveness of decisions for risk response planning and will lead to unexpected and undesired behavior in the project. Based on the concepts of DSS and the classical steps of project risk management, we develop an integrated DSS framework including the identification, assessment and analysis of the risk network. In the network, the nodes are the risks and the edges represent the cause and effect potential interactions between risks. The proposed simulation-based model makes it possible to re-evaluate risks and their priorities, to suggest and test mitigation actions, and then to support project manager in making decisions regarding risk response actions. An example of application is provided to illustrate the utility of the model.     

Development of a decision support system for supplier evaluation and order allocation

This study aims to develop models and generate a decision support system (DSS) for the improvement of supplier evaluation and order allocation decisions in a supply chain. Supplier evaluation and order allocation are complex, multi criteria decisions. Initially, an analytic hierarchy process (AHP) model is developed for qualitative and quantitative evaluation of suppliers. Based on these evaluations, a goal programming (GP) model is developed for order allocation among suppliers. The models are integrated into a DSS that provides a dynamic, flexible and fast decision making environment. The DSS environment is tested at the purchasing department of a manufacturer and feedbacks are obtained.     

Model management system for IRT-based test construction decision support system

Decision support system (DSS) has become widespread for some specific domains in recent years. However, DSS for IRT-based (item response theory) test construction has not yet been developed. This domain basically imposes a semi-structured or unstructured decision and, therefore, involves a very complex modeling process. This study develops a model management system (MMS) architecture to assist a non-expert user in manipulating test construction process efficiently and effectively. This architecture consists of four components: problem analysis, model type selection, model formulation and solver. The model type selection subsystem is further organized into three levels of hierarchy, i.e., environment, structure and parameter. A prototype is presented to demonstrate the feasibility of this architecture. The results indicate that this approach can be applied for providing an integrated, flexible and user-friendly DSS environment for producing better quality of results in less solution time.     

Risk management for laboratory automation projects

This tutorial outlines some of the common risks that may be associated throughout the development and implementation of a laboratory automation project such as a laboratory information management system (LIMS) or another automation project. It presents a scheme for undertaking risk management to help assess and mitigate the degree of risk associated with each of these factors. In the case of high-risk factors, suggestions are presented to manage or help avoid the problem.Risk management is an ongoing process. It begins at the start of a project and should be reassessed at intervals throughout the project to re-evaluate existing risks and to see if any factors have changed or new ones have emerged.     

Implementation and evaluation of an Asbru-based decision support system for adjuvant treatment in breast cancer

The domain of cancer treatment is a promising field for the implementation and evaluation of a protocol-based clinical decision support system, because of the algorithmic nature of treatment recommendations. However, many factors can limit such systems’ potential to support the decision of clinicians: technical challenges related to the interoperability with existing electronic patient records and clinical challenges related to the inherent complexity of the decisions, often collectively taken by panels of different specialists. In this paper, we evaluate the performances of an Asbru-based decision support system implementing treatment protocols for breast cancer, which accesses data from an oncological electronic patient record. Focusing on the decision on the adjuvant pharmaceutical treatment for patients affected by early invasive breast cancer, we evaluate the matching of the system's recommendations with those issued by the multidisciplinary panel held weekly in a hospital.     

A decision-oriented model to evaluate the effect of land use and agricultural management on herbicide contamination in stream water

Modelling stream water pollution by herbicides in agricultural areas is a critical issue since numerous and incompletely known processes are involved. A decision-oriented model, SACADEAU-Transf, which represents water and pesticide transfer in medium-sized catchments (10–50 km²) is presented. This model aims at evaluating the effect of land use, agricultural practice and landscape on the contamination of stream water in rural catchments. The processes are represented in an easily understandable way with a moderate amount of information, producing semi-quantitative and spatialized outputs. Modelling focuses on the first few months after herbicide application when high levels of contamination are generally observed, by considering transfer through the catchment area via surface and subsurface flow. The surface flow, based on a tree plot network representation of the catchment, is controlled by soil-surface properties and saturated conditions. The subsurface flow based on Topmodel concepts is controlled by the topography. Herbicide transfer is coupled to water transfer by taking into account the main characteristics of the chemicals. The model simulates the daily water and herbicide outflow at the outlets of the farmers' fields as well as from the catchment. Preliminary results on maize herbicide transfer are presented for an agricultural catchment with an area of 17 km² located in north-western France. The relevance of SACADEAU-Transf model is discussed in view of the qualities required for the decision-oriented models developed for improving agro-environmental management.     

Decision support for risk analysis on dynamic alliance

Dynamic alliance has been considered a temporary organization of member enterprises formed to pool their core competencies and exploit fast changing market opportunities. Although many problems on dynamic alliance such as partner selection, operation management, information exchanges and their standards, etc., have been investigated, the risk management of dynamic alliance has not received deserved attention until now. For risk evaluation is the most important phase of risk management, so this paper is mainly concerned with the risk evaluation problem. Various kinds of risk factors that affect the operation of alliance are identified, and their levels are measured by three parameters such as risk occurrence likelihood, consequence severity and risk control degree. These parameters are expressed by trapezoidal fuzzy numbers. Furthermore, risk evaluation is regarded as a multiattribute decision-making (MADM) problem with uncertainty. A new evaluation approach based on the framework of the evidential reasoning (ER) is proposed. Finally, a numerical example is given to illustrate the application of this approach in the process of risk evaluation.     

An incident information management framework based on data integration, data mining, and multi-criteria decision making

An effective incident information management system needs to deal with several challenges. It must support heterogeneous distributed incident data, allow decision makers (DMs) to detect anomalies and extract useful knowledge, assist DMs in evaluating the risks and selecting an appropriate alternative during an incident, and provide differentiated services to satisfy the requirements of different incident management phases. To address these challenges, this paper proposes an incident information management framework that consists of three major components. The first component is a high-level data integration module in which heterogeneous data sources are integrated and presented in a uniform format. The second component is a data mining module that uses data mining methods to identify useful patterns and presents a process to provide differentiated services for pre-incident and post-incident information management. The third component is a multi-criteria decision-making (MCDM) module that utilizes MCDM methods to assess the current situation, find the satisfactory solutions, and take appropriate responses in a timely manner. To validate the proposed framework, this paper conducts a case study on agrometeorological disasters that occurred in China between 1997 and 2001. The case study demonstrates that the combination of data mining and MCDM methods can provide objective and comprehensive assessments of incident risks.