关键词： “3S”技术   农业宏观决策系统   作用  

摘要： 依据天水农业现状及行业管理特点,研究开发农业宏观决策支持平台。本文从系统技术框架、业务流程和作用进行介绍,该系统使天水农业向国内农业方向发展,赶超世界农业先进水平,成为"科技天水"的良好示范,带动农业高新技术向全国辐射。

关键词： 医院管理   决策支持   数据仓库   数据主题   精细化管理  

摘要： 利用信息化手段,满足医院管理决策的需要。方法 建立基于数据仓库的管理决策系统,对医疗过程中的各项数 据进行抽取、存储、加工和展现。结果 辅助医院各级管理层逐步实现精细化管理。结论 基于数据仓库的决策支持系统在优 化业务流程、提高工作效率、改善服务质量、合理资源配置等方面都可以发挥其重要作用,提高了医院管理水平,增强了医 院核心竞争力。

关键词： 中原油田   勘探决策支持系统   数据集成管理   数据关联   多屏展示   异地通信  

摘要： 在调研国内外勘探决策支持技术基础上,确定了适合中原油田的勘探决策支持系统的总体思路,研究了勘探决策数据集成管理技术、多维海量异构数据关联技术、多块大屏幕无缝连接展示与异地井位论证通信技术等,并开发了适合中原油田的勘探决策支持技术系统,改变了传统纸质挂图井位论证模式。经过1年多的运行,该系统累计支持勘探井位部署论证决策会议89次,部署勘探井位85口,使用超过1 700次/人,决策论证时间缩短30%,并支持了远程异地论证会,为中原油田各区域勘探效率提供技术支撑。

关键词： 决策支持系统(DSS)模型   模型驱动   WF工作流   框架  

摘要： 在已知决策支持系统(DSS)模型表达形式的基础上,探索其计算机实现过程中的自动化。针对目前模型驱动工程中有关DSS模型的研究集中于领域模型构建机制及平台的搭建,而对模型复合及求解等生成机制方面的研究关注不足,本研究提出了一种基于WF工作流等技术来完成DSS模型从创建到复合运行的自动化策略,并实现了相应的框架原型。该框架提供了人性化的模型生成环境,所有实现细节对模型研究者而言均为黑盒抽象,使用者无需编程即可完成模型的生成。此策略为DSS模型构建的工程化、智能化提供了一种新的思路。

关键词： DARPA   美国国防部   五角大楼   军事系统   软件原型   近距离  

摘要： 2016年5月13日，是DARPA（美国国防部先进研究项目局）展示日，DARPA在五角大楼中心举办了一场展示，人们可以近距离接触各种尚处不同研发阶段的技术和军事系统（十七项），它们都是超未来、高风险、高回报的硬件和软件原型。

关键词： galatea   GDSS   GRiST   ADVANCE   OWL   SWRL  

摘要： Machines that provide decision support have traditionally used either a representation of human expertise or used mathematical algorithms. Each approach has its own limitations. This study helps to combine both types of decision support system for a single system. However, the focus is on how the machines can formalise and manipulate the human representation of expertise rather than on data processing or machine learning algorithms. It will be based on a system that represents human expertise in a psychological format. The particular decision support system for testing the approach is based on a psychological model of classification that is called the Galatean model of classification. The simple classification problems only require one XML structure to represent each class and the objects to be assigned to it. However, when the classification system is implemented as a decision support system within more complex realworld domains, there may be many variations of the class specification for different types of object to be assigned to the class in different circumstances and by different types of user making the classification decision. All these XML structures will be related to each other in formal ways, based on the original class specification, but managing their relationships and evolution becomes very difficult when the specifications for the XML variants are text-based documents. For dealing with these complexities a knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. The aim is to explore how semantic web technologies can be employed to help the knowledge engineering process for decision support systems based on human expertise, but deployed in complex domains with variable circumstances. The research evaluated OWL as a suitable vehicle for representing psychological expertise. The task was to see how well it can prov

关键词： Chaos-based communication   Frequency selective channels   Diversity combining   Multiple access techniques  

摘要： Analysis of communication systems with combiners, assuming flat fading channels, is well-known. However, this analysis for a chaos-based DSSS system with a frequency selective channel, giving proper mathematical model and derived expressions for the probability of error, practically does not exist. This paper presents the theoretical model of a chaos-based DSSS system assuming frequency selective channel that is composed of a primary channel and a number of secondary channels. In order to investigate the consequences of delays on signal transmission in these channels, this paper uses presentation of signals in discrete time domain and theoretical frame of discrete time stochastic processes. The channel is represented by a modified Saleh-Valenzuela model, which results in a number of delayed signal replicas at the receiver side. For the sake of explanation, the delays are assumed to remain in a chip interval. For the sake of comparison, the theoretical models and derived expressions are confirmed by the simulation of the system. (C) 2016 Elsevier B.V. All rights reserved.

关键词： decision support model   existing buildings   innovative approach   masonry   seismic strengthening technology  

摘要： When the decision has been made to seismically strengthen a building, in order to mitigate possible damaging effects of an earthquake, choice of seismic strengthening is entirely left to the expert. The choice is often made without any specific analyses of the need and implementation possibilities, but depends completely on the expert's knowledge and experience. The article presents the development of the innovative approach to strengthening technique selection for existing buildings that incorporates all important elements that influence the strengthening selection process. The presented model is simple, quick, precise, allowing analytically supported decision making. Although the developed model is designed particularly for masonry buildings, decision support model for strengthening technique selection is adaptable to any building type.

摘要： Objective: To determine if clinical decision support (CDS) malfunctions occur in a commercial electronic health record (EHR) system, characterize their pathways and explore methods of detection. Materials and Methods: We retrospectively examined the firing rate for 226 alert type CDS rules for detection of anomalies using both expert visualization and statistical process control (SPC) methods over a five year period. Candidate anomalies were investigated and validated. We defined an anomaly as alert firing rates which deviated from historical or expected trends. A CDS malfunction was defined as a CDS alert which was not functioning as designed or intended. A false positive CDS anomaly was an alert that altered firing from an intentional change. Results: In 8,300 alert-months twenty-one candidate CDS anomalies were identified. Of these candidate anomalies, four were confirmed as CDS malfunctions, eight as false-positives, and nine could not be classified. The four CDS malfunctions were a result of errors in knowledge management: (1) inadvertent addition and removal of a medication code to the electronic formulary list; (2) a seasonal alert which was not activated; (3) a change in the base data structures; (4) direct editing of an alert related to its medications. 154 CDS rules were amenable to SPC methods and the test characteristics were calculated as a sensitivity of 95%, positive predictive value of 29% and F-measure 0.44. Discussion: CDS malfunctions were found to occur in our EHR. All of the pathways for these malfunctions can be described as knowledge management errors. Expert visualization is a robust method of detection, but is resource intensive. SPC-based methods, when applicable, perform reasonably well retrospectively. Conclusion: CDS anomalies were found to occur in a commercial EHR and visual detection along with SPC analysis represents promising methods of malfunction detection.

摘要： It is a global challenge to produce enough healthy food to a growing world population. By moving industrial fish farming to exposed lo- cations, the farmers can possibly satisfy the dietary requirements of the future by expanding the production. The environment at exposed locations is rough, and conditions like harsh wind, large waves and strong currents are present. On the positive side, there are better wa- ter flow and distribution of waste. Exposed locations are also further away from natural salmons, which might reduce negative environmen- tal effects. The production plants for fish farming are designed to be flexible and adaptive to waves and sea currents. Monitoring of the health and condition of these structures will be more important regarded reducing cost of operations and maintenance. This data can be combined with historical data and expert knowledge to support the operators decision about acting upon a possible problematic situation. Our goal in this MSc thesis is to study the method of implement- ing a decision support system for predictive maintenance of exposed aquaculture structures, based on a previously proposed architecture from the specialisation project. The architecture is based on the fields of Machine Learning, Structural Health Monitoring and Case-Based Reasoning. This thesis describes the work done in order to achieve our goals, which includes the work of researching the relevant domains, con- ducting a data analysis, creating models with the resulting data sets, revising the previously proposed architecture and implementing a pro- totypical decision support system. At last we conclude and discuss the future work. The work with this thesis shows that our prototype of a decision support system is able to support an operator with advice about what to do, if a situation similar to previously experienced situations occur.