基于埃及畜牧生产长远视角的智能推荐系统

Ahmed Mohamed Omran , Motaz Khorshid
{"title":"基于埃及畜牧生产长远视角的智能推荐系统","authors":"Ahmed Mohamed Omran ,&nbsp;Motaz Khorshid","doi":"10.1016/j.aasri.2014.05.015","DOIUrl":null,"url":null,"abstract":"<div><p>Research on the Egyptian food security, is a crucial subject of a huge studies and debates. The gap between the Egyptian domestic milk production and consumption is translated into high import costs. Also, all policy analysis and evaluation methods in literature conduct for the current /short-term policies to help policy/decision makers in strategic decisions. The core idea of our research paper is to develop an intelligent recommender system (IRS) to generate more justifiable estimates to evaluate of the suggested long-term policies. In addition, our IRS supports policy/decision makers to reduce the future uncertainty and stimulates the domain experts to anticipate the futures impacts and evaluate their suggested policies. This support deals with providing new levels of awareness situation that may lead to more efficient and effective decision making process. Final, our IRS integrates Trend Impact Analysis, RT-Delphi, Knowledge-Based, Explanation and Mathematical forecasting models to generate large-scale participatory approach to help policy/decision makers for long-term strategic planning.</p></div>","PeriodicalId":100008,"journal":{"name":"AASRI Procedia","volume":"6 ","pages":"Pages 103-110"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.aasri.2014.05.015","citationCount":"6","resultStr":"{\"title\":\"An Intelligent Recommender System for Long View of Egypt's Livestock Production\",\"authors\":\"Ahmed Mohamed Omran ,&nbsp;Motaz Khorshid\",\"doi\":\"10.1016/j.aasri.2014.05.015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Research on the Egyptian food security, is a crucial subject of a huge studies and debates. The gap between the Egyptian domestic milk production and consumption is translated into high import costs. Also, all policy analysis and evaluation methods in literature conduct for the current /short-term policies to help policy/decision makers in strategic decisions. The core idea of our research paper is to develop an intelligent recommender system (IRS) to generate more justifiable estimates to evaluate of the suggested long-term policies. In addition, our IRS supports policy/decision makers to reduce the future uncertainty and stimulates the domain experts to anticipate the futures impacts and evaluate their suggested policies. This support deals with providing new levels of awareness situation that may lead to more efficient and effective decision making process. Final, our IRS integrates Trend Impact Analysis, RT-Delphi, Knowledge-Based, Explanation and Mathematical forecasting models to generate large-scale participatory approach to help policy/decision makers for long-term strategic planning.</p></div>\",\"PeriodicalId\":100008,\"journal\":{\"name\":\"AASRI Procedia\",\"volume\":\"6 \",\"pages\":\"Pages 103-110\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.aasri.2014.05.015\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AASRI Procedia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S221267161400016X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AASRI Procedia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S221267161400016X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

关于埃及粮食安全的研究,是一个巨大的研究和争论的关键主题。埃及国内牛奶产量和消费量之间的差距转化为高昂的进口成本。此外,文献中所有的政策分析和评估方法都是针对当前/短期政策进行的,以帮助政策/决策者进行战略决策。我们的研究论文的核心思想是开发一个智能推荐系统(IRS),以产生更合理的估计来评估建议的长期政策。此外,我们的IRS支持政策/决策者减少未来的不确定性,并激励领域专家预测未来的影响并评估他们建议的政策。这种支持涉及提供新的认识水平,这可能导致更有效和更有效的决策过程。最后,我们的IRS集成了趋势影响分析,RT-Delphi,知识基础,解释和数学预测模型,以产生大规模的参与式方法,以帮助政策/决策者进行长期战略规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Intelligent Recommender System for Long View of Egypt's Livestock Production

Research on the Egyptian food security, is a crucial subject of a huge studies and debates. The gap between the Egyptian domestic milk production and consumption is translated into high import costs. Also, all policy analysis and evaluation methods in literature conduct for the current /short-term policies to help policy/decision makers in strategic decisions. The core idea of our research paper is to develop an intelligent recommender system (IRS) to generate more justifiable estimates to evaluate of the suggested long-term policies. In addition, our IRS supports policy/decision makers to reduce the future uncertainty and stimulates the domain experts to anticipate the futures impacts and evaluate their suggested policies. This support deals with providing new levels of awareness situation that may lead to more efficient and effective decision making process. Final, our IRS integrates Trend Impact Analysis, RT-Delphi, Knowledge-Based, Explanation and Mathematical forecasting models to generate large-scale participatory approach to help policy/decision makers for long-term strategic planning.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信