Design and development of a generic spatial decision support system, based on artificial intelligence and multicriteria decision analysis

GeoResJ Pub Date : 2017-12-01 DOI:10.1016/j.grj.2017.08.003
Muhammad Irfan , Aleksandra Koj , Majid Sedighi , Hywel Thomas
{"title":"Design and development of a generic spatial decision support system, based on artificial intelligence and multicriteria decision analysis","authors":"Muhammad Irfan ,&nbsp;Aleksandra Koj ,&nbsp;Majid Sedighi ,&nbsp;Hywel Thomas","doi":"10.1016/j.grj.2017.08.003","DOIUrl":null,"url":null,"abstract":"<div><p><span>A new integrated and generic Spatial Decision Support System (SDSS) is presented based on a combination of Artificial Intelligence and Multicriteria Decision Analysis techniques. The approach proposed is developed to address commonly faced spatial decision problems of site selection, site ranking, impact assessment and spatial knowledge discovery under one system. The site selection module utilises a theme-based </span>Analytical Hierarchy Process<span>. Two novel site ranking techniques are introduced. The first is based on a systematic neighbourhood comparison of sites with respect to key datasets (criterions). The second utilises multivariate ordering capability of one-dimensional Self-Organizing Maps. The site impact assessment module utilises a new spatially enabled Rapid Impact Assessment Matrix. A spatial variant of General Regression Neural Networks is developed for Geographically Weighted Regression (GWR) and prediction analysis. The developed system is proposed as a useful modern tool that facilitates quantitative and evidence based decision making in multicriteria decision environment. The intended users of the system are decision makers in government organisations, in particular those involved in planning and development when taking into account socio-economic, environmental and public health related issues.</span></p></div>","PeriodicalId":93099,"journal":{"name":"GeoResJ","volume":"14 ","pages":"Pages 47-58"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.grj.2017.08.003","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GeoResJ","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214242817300384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

A new integrated and generic Spatial Decision Support System (SDSS) is presented based on a combination of Artificial Intelligence and Multicriteria Decision Analysis techniques. The approach proposed is developed to address commonly faced spatial decision problems of site selection, site ranking, impact assessment and spatial knowledge discovery under one system. The site selection module utilises a theme-based Analytical Hierarchy Process. Two novel site ranking techniques are introduced. The first is based on a systematic neighbourhood comparison of sites with respect to key datasets (criterions). The second utilises multivariate ordering capability of one-dimensional Self-Organizing Maps. The site impact assessment module utilises a new spatially enabled Rapid Impact Assessment Matrix. A spatial variant of General Regression Neural Networks is developed for Geographically Weighted Regression (GWR) and prediction analysis. The developed system is proposed as a useful modern tool that facilitates quantitative and evidence based decision making in multicriteria decision environment. The intended users of the system are decision makers in government organisations, in particular those involved in planning and development when taking into account socio-economic, environmental and public health related issues.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于人工智能和多准则决策分析的通用空间决策支持系统的设计与开发
提出了一种基于人工智能和多准则决策分析技术相结合的综合通用空间决策支持系统(SDSS)。该方法旨在解决在同一系统下常见的选址、选址排序、影响评估和空间知识发现等空间决策问题。网站选择模块采用基于主题的层次分析法。介绍了两种新的网站排名技术。第一种方法是根据关键数据集(标准)对站点进行系统的邻域比较。第二种是利用一维自组织映射的多元排序能力。场地影响评估模块采用新的空间快速影响评估矩阵。本文提出了一种广义回归神经网络的空间变体,用于地理加权回归(GWR)和预测分析。所开发的系统是一种有用的现代工具,有助于在多准则决策环境中进行定量和基于证据的决策。该系统的预期用户是政府组织中的决策者,特别是那些在考虑到社会经济、环境和公共卫生相关问题时参与规划和发展的决策者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Editorial Board Soil legacy data rescue via GlobalSoilMap and other international and national initiatives Design and development of a generic spatial decision support system, based on artificial intelligence and multicriteria decision analysis A re-evaluation of the basal age in the DSDP hole at Site 534, Central Atlantic The application of machine learning for evaluating anthropogenic versus natural climate change
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1