基于数据仓库和数据挖掘技术的温室决策支持系统(简报)

农业领域的专家知识多是描述性和经验性的知识,难以进行精确的数学描述,这给农业决策支持系统的构建带来了一定的困难。为解决这种传统的决策支持系统的不足,介绍了基于数据仓库技术和数据挖掘技术构建的温室决策支持系统。该系统通过建立数据仓库来存储各种来自异质的信息源的数据,利用联机分析处理实现多维数据分析,然后通过数据挖掘技术从数据仓库中获得新的农业知识,以丰富决策支持系统的知识库。在系统的实现过程中,采用了SQL Server分析服务,实现数据挖掘与数据仓库以及应用程序的紧密耦合,从而大大提高了数据挖掘效率。将数据仓库、联机分析处理、数据挖掘三者结合起来形成了一种新的温室决策支持系统。     

基于DSS的1978－2005年中国区域农田生态系统氮平衡

该文建立了养分平衡决策支持系统,并利用该系统对中国国家及分省层次上的农田生态系统氮养分平衡情况进行了研究。研究表明：1）从1978到2005年,全国氮素养分盈余量不断上升,从1978年的1054.66×104 t一直上升到2005年的2867.12×104 t,平均年增量约为64.7×104 t;2）区域之间氮素盈亏量存在着显著差异。粮食主产区的省份如山东、河南和四川的养分氮盈余量一直都较高,而西部省份如新疆、西藏等养分氮盈余量较低。中国粮食主产区农田生态系统氮素平衡呈现出持续盈余且逐年上升的态势,显示出以化肥氮为主体的氮素养分投入量已经长时间高于作物的需求量,这些盈余的氮素养分在农田中累积,并通过多种途径进入到水体及大气环境中,不但造成了氮素化肥的浪费,更会对环境造成较大的压力。     

畜禽养殖业污染控制决策支持系统的构建

决策支持系统能提供可靠的信息服务和科学计算,人机交互性好.文章针对我国畜禽养殖业污染严重、产排污量难以计算的现状,建立了由产排污模型、处理技术选用模型组成的污染控制决策系统.产排污模型应用产污系数、削减比例实现了污染物的定量核算.处理技术选用模型把处理技术分为粪便及污水处理、厌氧消化液再处理、达标处理三级,根据规模、经济水平等因素选择不同处理技术组合,将污染物逐级削减掉.系统应用ASP·NET技术设计了网页界面,实现了污染物产排量计算、不同粪污处理技术选择和用户浏览、查询等功能,为用户提供决策与建议.     

农业R＆D系统分析与决策支持系统的设计与实现

设计并实现了农业R＆D系统分析与决策支持系统,该系统在总体框架设计、数据接口和模型接口设计方面具有特色,对推动我国农业R＆D问题决策分析与支持系统的建立有积极的意义。     

数据仓库技术在水稻栽培管理决策支持系统中的应用

农业与其他行业相比,涉及的因素极其繁杂,如土壤、气象、环境等,且时空差异和变异性大,病虫灾害频繁,生产稳定性和可控程度差。农业自身的这些特点,决定了农业信息技术应用的复杂性和难度。文章结合水稻管理的实际情况,给出数据仓库在水稻栽培管理决策支持系统中的初步设计方案,探索了该技术在水稻生产中的应用,解决出现的相关技术问题。     

决策支持系统在精准农业和温室工程中的运用及前景

综述了决策支持系统在发展我国精准农业和温室工程中的地位,及目前国内外决策支持系统的发展和运用现状,进一步提出现阶段我国开展温室生产管理智能决策支持系统研究的若干方法,并展望了决策支持系统在我国发展精准农业和智能温室工程中的应用前景.     

The decision‐making environment at different hierarchical levels in timber procurement

Research into decision‐making processes is necessary for the successful construction of a decision support system (DSS). Consequently, the primary aim of this study was to analyse timber procurement decision‐making at the various managerial levels of an organizational hierarchy. A secondary aim was to pinpoint those areas of procurement where managers need decision support most urgently. The study was executed in the form of a mail‐survey questionnaire. The research results obtained indicated that the decision‐making environment of managers responsible for timber procurement is in a constant state of flux and that these managers regarded this to be the worst problem affecting decision‐making. In particular, those decision‐makers who claimed to often base their decisions on “soft” data (experience, intuition, or judgement) clearly demanded more DSSs. There were no significant differences in results among the different hierarchical levels. Procurement managers estimated that they desired an average increase of approximately 20% in the availability of DSSs and they, described several procurement functions where they hoped for more powerful computer‐based support systems. One prominent finding in this connection was the need for a “customer‐satisfaction DSS” that would help managers in their timber dealings with forest owners.     

Emerging consensus on desirable characteristics of tools to support farmers’ management of climate risk in Australia

The prospect that decision support systems (DSS) can help farmers adjust their management to suit seasonal conditions by putting scientific knowledge and rational risk management algorithms at farmers’ fingertips continues to challenge the science and extension community. A number of reviews of agricultural DSS have called for a re-appraisal of the field and for the need to reflect on past mistakes and to learn from social and management theory. The objective of this paper was to investigate whether there is an emerging consensus, among stakeholders in DSS for Australian agriculture, about the lessons learned from past experience with DSS tools. This investigation was conducted in three parts. The first part was a distillation of suggestions for best practice from the relevant literature. The second part was a reflection on what the champions of five current DSS development and delivery efforts in Australia learned from their recent efforts. The third part tested the level of support for the combined findings from the first and second approaches by surveying 23 stakeholders in the research, development, delivery and funding of DSS.The key propositions relating to best practice that were supported by the survey, listed according to the strength of support, were: 1. It is essential to have a plan for delivery of the DSS beyond the initial funding period. 2. DSS need to be embedded in a support network consisting of farmers, consultants and researchers. 3. DSS development requires the commitment of a critical mass of appropriately skilled people. 4. A DSS should aim to educate farmers’ intuition rather than replace it with optimised recommendations. 5. A DSS should enable users to experiment with options that satisfy their needs rather than attempt to present ‘optimised’ solutions. 6. DSS tools stand on the quality and authority of their underlying science and require ongoing improvement, testing and validation. 7. DSS development should not commence unless it is backed by marketing information and a plan for delivery of the DSS beyond the initial funding period.While the DSS stakeholders supported the proposition that it is essential to have a plan for delivery of a DSS beyond the funding period, the majority resisted the notion of DSS development being market-driven and especially commercial delivery of DSS. We argue that since public funding of the delivery of DSS for farmers’ management of climate risk is highly unlikely, reaping the benefits of lessons learned from past efforts will require that DSS stakeholders change their perception of the commercial delivery model or find an alternative way to fund the delivery of DSS beyond the R&D phase.     

基于GIS的专家系统和决策支持系统在林业中的应用研究综述

基于GIS的专家系统和决策支持系统应用研究,极大地提高了数字林业信息化水平。介绍和评述了当前地理信息系统(GIS)、专家系统(ES)、决策支持系统(DSS)在森林防火、营造林、森林病虫害防治和森林资源管理等领域的应用;分析了GIS,ES和DSS在林业中应用所存在或面临的主要问题;提出了在林业应用中的发展前景。     

决策支持系统在机械工业科技人才管理中的应用

根据机械工业科技人才队伍管理的要求，建立了“三库一体的总体结构。