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Introduction for Volume 9, Issue 4 第9卷第4期简介
Pub Date : 2020-01-01 DOI: 10.2991/jracr.k.200120.001
Chongfu Huang, Gordon H. Huang
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引用次数: 0
Introduction for Volume 10, Issue 1 第10卷第1期简介
Pub Date : 2020-01-01 DOI: 10.2991/jracr.k.200415.003
Chongfu Huang, Gordon H. Huang
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引用次数: 0
Introduction for Volume 10, Issue 2 第10卷第2期介绍
Pub Date : 2020-01-01 DOI: 10.2991/jracr.k.200720.001
Chongfu Huang, Gordon H. Huang
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引用次数: 0
Meteorological Risk Assessment of Rooftop Solar Resource Development in Inner Mongolia 内蒙古屋顶太阳能资源开发气象风险评价
Pub Date : 2020-01-01 DOI: 10.2991/jracr.k.200117.005
亚男 Yanan胡Hu, 兴华 Xinghua李Li
Due to the long and narrow regional characteristics of Inner Mongolia, there are obvious climatic differences between the east and the west, and various meteorological factors have different influences on the development and utilization of solar energy. The abundance and stability index of solar energy resources are relatively high in the central and western region of Inner Mongolia, but there are more sandstorms, high temperature and strong wind. The eastern region is greatly affected by cloud cover, relative humidity and snowfall, which weakens the solar radiation. Through the comprehensive evaluation of the solar energy resources and meteorological elements, it is found that from the Alashan League to the west of Xilin Gol League, and the most of the Chifeng City are low-risk areas, which are relatively suitable for the development and utilization of rooftop solar energy. The central and northern areas of hulunbuir are high-risk areas, which is not suitable for that. Based on the meteorological industry standard “Solar Energy Resource Assessment Method”, we calculate the solar energy resources abundance and stability index, combined with the annual surface meteorological data of 119 meteorological stations in Inner Mongolia from 1988 to 2018. The distribution characteristics of solar energy resources and meteorological elements in Inner Mongolia is analyzed and the suitability and meteorological risks of rooftop solar resources development and utilization are evaluated.
内蒙古由于狭长的地域特征,东西气候差异明显,各种气象因素对太阳能开发利用的影响也不尽相同。内蒙古中西部地区太阳能资源丰度和稳定性指数较高,但沙尘暴、高温、大风天气较多。东部地区受云量、相对湿度和降雪影响较大,使太阳辐射减弱。通过对太阳能资源和气象要素的综合评价发现,从阿拉善盟到锡林郭勒盟西部,赤峰市大部分地区为低风险区,相对适合屋顶太阳能的开发利用。呼伦贝尔的中部和北部地区是高风险地区,不适合这样做。依据气象行业标准《太阳能资源评价方法》,结合内蒙古119个气象站1988 - 2018年全年地面气象资料,计算了内蒙古地区太阳能资源丰度和稳定性指数。分析了内蒙古地区太阳能资源和气象要素的分布特征,对屋顶太阳能资源开发利用的适宜性和气象风险进行了评价。
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引用次数: 0
Prospects of Guizhou Province’s Ecological Agriculture Benefit Evaluation Index System 贵州省生态农业效益评价指标体系展望
Pub Date : 2020-01-01 DOI: 10.2991/jracr.k.200117.002
Jian He, Hongmei Zhang
Ecological agriculture is developed using modern scientific and technological achievements and modern management methods, drawing on the effective experience of traditional agriculture, using ecological principles and economic principles. Ecological agriculture is a modernization that can obtain higher economic, ecological and social benefits of agriculture. Eco-agriculture requires that chemical fertilizers and chemical pesticides are not used, and that the use of farm manure increases soil fertility, uses biological methods to control crop diseases and insect pests, and protects the living environment.
生态农业是利用现代科技成果和现代管理方法,借鉴传统农业的有效经验,运用生态学原理和经济学原理发展起来的农业。生态农业是一种能够获得较高经济效益、生态效益和社会效益的现代化农业。生态农业要求不使用化肥和化学农药,使用粪肥增加土壤肥力,用生物方法防治作物病虫害,保护生存环境。
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引用次数: 1
The Harmonious Development of Big Data Industry and Financial Agglomeration in Guizhou 贵州大数据产业与金融集聚的和谐发展
Pub Date : 2020-01-01 DOI: 10.2991/dramclr-19.2019.40
L. Pang, Mu Zhang
In order to promote the coordinated development of big data industry and financial agglomeration, according to the characteristics of big data industry and financial agglomeration in Guizhou at this stage, the paper first understands the relevant literature of big data industry and financial agglomeration. Then, using the original data of nine cities in Guizhou from 2013 to 2017, we measure the development level of big data industry and financial agglomeration level of nine cities in Guizhou by using the hesitant fuzzy linguistic TOPSIS method and hesitant fuzzy linguistic PROMETHEE method respectively. Finally, the coupling coordination degree of big data industry and financial agglomeration in nine cities of Guizhou is calculated by using the coupling coordination model, and relevant policy recommendations are put forward. The empirical results show that Guiyang city is moderately coordinated development of big data industry and financial agglomeration, Zunyi city is reluctantly coordinated development, Liupanshui, Bijie and Southwest Guizhou are slightly maladjusted recessions, and the remaining cities are moderately maladjusted recessions. During the sample period, the degree of coupling and coordination between big data industry and financial agglomeration in Guizhou has been continuously improved, but the phenomenon of regional imbalance is more obvious. Keywords—Big Data Industry; Financial Agglomeration; Coupling and Coordination; Hesitant Fuzzy Linguistic TOPSIS Method; Hesitant Fuzzy Linguistic PROMETHEE Method 摘要—为了促进大数据产业与金融集聚协调发展,针对现 阶段贵州大数据产业和金融集聚的特点,文章首先了解了大 数据产业与金融集聚相关文献;然后,选取 2013-2017 年贵 州九个地州市的指标原始数据,分别运用犹豫模糊语言 TOPSIS 法和犹豫模糊语言 PROMETHEE 方法对贵州九个 地州市的大数据产业发展水平和金融集聚水平进行测度;最 后运用耦合协调模型计算贵州九个地州市的大数据产业与金 融集聚的耦合协调度,并提出相关政策建议。实证结果表 明:贵阳市为大数据产业与金融集聚中度协调发展,遵义市 为勉强协调发展,六盘水、毕节、黔西南是轻度失调衰退, 剩余州市为中度失调衰退。样本期间内,总体上贵州大数据 产业与金融集聚耦合协调程度不断提高,但区域间不均衡现 象较为明显。 关键词—大数据产业,金融集聚,耦合协调,犹豫模糊语 言 TOPSIS 法,犹豫模糊语言 PROMETHEE 法 I. 引言 围绕实施国家大数据战略,加强大数据在金融行业 领域的深入应用,促进跨行业大数据融合创新,推动大 数据与金融行业领域的融合发展,对促进经济转型和创 新发展有重大意义。贵州正在建立大数据产业投融资体 系,鼓励金融机构为符合条件的大数据企业给予信贷支 持,围绕大数据产业开发和创新金融产品,延伸服务网 络,为贵州大数据项目融资提供支撑 [1] 。贵州建成全国 领先的大数据资源集聚地和大数据应用服务示范基地, 需要财政金融的大力支持和健全大数据产业投融资机 制,大数据产业的发展也有利于金融行业改变传统的运 行方式和运行机制,促进大数据金融服务业的发展。因 此,对大数据产业与金融集聚协调发展现状进行分析, 有利于把握大数据产业与金融行业发展差异,促进行业 大数据应用发展。 目前而言,国内外学者大多集中于对金融集聚与产 业发展之间关系的研究。国外研究中,Rajan 和 Zingales (1998)[1]通过建立理论模型研究金融发展到一定程度 形成的金融集聚与产业结构之间的关系;Carlin 和 Mayer(2003)[2]从不同类型的金融结构角度出发,研 究其对产业的影响;Audress 等(2006)[3]阐述了金融集 聚带来的溢出效应显著提高了地区间的技术创新和产业 升级;Cotugno 等(2013)[4]认为金融集聚下,产业结 构升级出现的空间溢出效用不但促进本地区的产业升 级,同时也促进了周边地区产业的发展。国内研究中, 陈峰(1991)[5]最早研究了金融发展与产业发展之间的 关系;孙晶和蒋伏心(2013) [6]借助空间滞后模型和空间 误差模型进行研究发现,金融集聚对区域产业结构升级 存在空间溢出效应;杨义武和方大春(2013)[7]运用面 板向量自回归模型研究金融集聚与产业结构变迁的互动 关系;邓向荣和刘文强(2013)[8]实证分析了金融集聚 对产业结构升级作用;郭露和丁峰(2015)[9] 运用协调 发展度评价的改进模型对长三角地区 16 个地级市的三 大产业结构与金融集聚的分布进行综合评价与比较;何 宜庆等(2015)[10]运用物理学中的三者耦合模型,将金 融要素集聚、区域产业结构和生态效率三个系统相结 合,进行了耦合协调实证研究;于斌斌(2017)[11]认为 金融集聚对经济增长的影响是通过促进产业结构升级实 Fourth Symposium on Disaster Risk Analysis and Management in Chinese Lit
为了促进大数据产业与金融集聚的协调发展,根据现阶段贵州大数据产业与金融集聚的特点,本文首先了解了大数据产业与金融集聚的相关文献。然后,利用贵州9个城市2013 - 2017年的原始数据,分别采用犹豫模糊语言TOPSIS法和犹豫模糊语言PROMETHEE法对贵州9个城市的大数据产业发展水平和金融集聚水平进行测度。最后,利用耦合协调模型计算贵州9个城市大数据产业与金融集聚的耦合协调度,并提出相关政策建议。实证结果表明,贵阳市为大数据产业与金融集聚适度协调发展,遵义市为勉强协调发展,六盘水、毕节和黔西南为轻度失调衰退,其余城市为中度失调衰退。样本期内,贵州大数据产业与金融集聚的耦合协调程度不断提高,但区域不平衡现象较为明显。关键词:大数据产业;金融集聚;耦合与协调;犹豫模糊语言TOPSIS方法犹豫模糊语言PROMETHEE法方法摘要——为了促进大数据产业与金融集聚协调发展,针对现阶段贵州大数据产业和金融集聚的特点,文章首先了解了大数据产业与金融集聚相关文献,然后,选取2013 - 2017年贵州九个地州市的指标原始数据,分别运用犹豫模糊语言TOPSIS法和犹豫模糊语言PROMETHEE法方法对贵州九个地州市的大数据产业发展水平和金融集聚水平进行测度;最后运用耦合协调模型计算贵州九个地州市的大数据产业与金融集聚的耦合协调度,并提出相关政策建议。实证结果表 明:贵阳市为大数据产业与金融集聚中度协调发展,遵义市 为勉强协调发展,六盘水、毕节、黔西南是轻度失调衰退, 剩余州市为中度失调衰退。样本期间内,总体上贵州大数据 产业与金融集聚耦合协调程度不断提高,但区域间不均衡现 象较为明显。 关键词——大数据产业,金融集聚,耦合协调,犹豫模糊语言TOPSIS法,犹豫模糊语言PROMETHEE法法即引言围绕实施国家大数据战略,加强大数据在金融行业领域的深入应用,促进跨行业大数据融合创新,推动大数据与金融行业领域的融合发展,对促进经济转型和创新发展有重大意义。贵州正在建立大数据产业投融资体 系,鼓励金融机构为符合条件的大数据企业给予信贷支 持,围绕大数据产业开发和创新金融产品,延伸服务网 络,为贵州大数据项目融资提供支撑 [1] 。贵州建成全国 领先的大数据资源集聚地和大数据应用服务示范基地, 需要财政金融的大力支持和健全大数据产业投融资机 制,大数据产业的发展也有利于金融行业改变传统的运 行方式和运行机制,促进大数据金融服务业的发展。因 此,对大数据产业与金融集聚协调发展现状进行分析, 有利于把握大数据产业与金融行业发展差异,促进行业 大数据应用发展。 目前而言,国内外学者大多集中于对金融集聚与产 业发展之间关系的研究。国外研究中,Rajan和Zingales(1998)[1]通过建立理论模型研究金融发展到一定程度形成的金融集聚与产业结构之间的关系,卡林和梅耶(2003)[2]从不同类型的金融结构角度出发,研究其对产业的影响,Audress等(2006)[3]阐述了金融集聚带来的溢出效应显著提高了地区间的技术创新和产业升级,卡徒诺等(2013)[4]认为金融集聚下,产业结构升级出现的空间溢出效用不但促进本地区的产业升级,同时也促进了周边地区产业的发展。国内研究中,陈峰(1991)[5]最早研究了金融发展与产业发展之间的关系,孙晶和蒋伏心(2013)[6]借助空间滞后模型和空间误差模型进行研究发现,金融集聚对区域产业结构升级存在空间溢出效应,杨义武和方大春(2013)[7]运用面板向量自回归模型研究金融集聚与产业结构变迁的互动关系,邓向荣和刘文强(2013)[8]实证分析了金融集聚对产业结构升级作用,郭露和丁峰(2015)[9]运用协调发展度评价的改进模型对长三角地区16个地级市的三大产业结构与金融集聚的分布进行综合评价与比较,何宜庆等(2015)[10]运用物理学中的三者耦合模型,将金融要素集聚,区域产业结构和生态效率三个系统相结合,进行了耦合协调实证研究,于斌斌(2017)[11]认为金融集聚对经济增长的影响是通过促进产业结构升级实第四次研讨会上灾害风险分析和管理在中国沿海地区(DRAMCLR 2019)版权©2019年,作者。亚特兰蒂斯出版社出版。这是一篇基于CC BY-NC许可(http://creativecommons.org/licenses/by-nc/4.0/)的开放获取文章。智能系统研究进展,第171卷
{"title":"The Harmonious Development of Big Data Industry and Financial Agglomeration in Guizhou","authors":"L. Pang, Mu Zhang","doi":"10.2991/dramclr-19.2019.40","DOIUrl":"https://doi.org/10.2991/dramclr-19.2019.40","url":null,"abstract":"In order to promote the coordinated development of big data industry and financial agglomeration, according to the characteristics of big data industry and financial agglomeration in Guizhou at this stage, the paper first understands the relevant literature of big data industry and financial agglomeration. Then, using the original data of nine cities in Guizhou from 2013 to 2017, we measure the development level of big data industry and financial agglomeration level of nine cities in Guizhou by using the hesitant fuzzy linguistic TOPSIS method and hesitant fuzzy linguistic PROMETHEE method respectively. Finally, the coupling coordination degree of big data industry and financial agglomeration in nine cities of Guizhou is calculated by using the coupling coordination model, and relevant policy recommendations are put forward. The empirical results show that Guiyang city is moderately coordinated development of big data industry and financial agglomeration, Zunyi city is reluctantly coordinated development, Liupanshui, Bijie and Southwest Guizhou are slightly maladjusted recessions, and the remaining cities are moderately maladjusted recessions. During the sample period, the degree of coupling and coordination between big data industry and financial agglomeration in Guizhou has been continuously improved, but the phenomenon of regional imbalance is more obvious. Keywords—Big Data Industry; Financial Agglomeration; Coupling and Coordination; Hesitant Fuzzy Linguistic TOPSIS Method; Hesitant Fuzzy Linguistic PROMETHEE Method 摘要—为了促进大数据产业与金融集聚协调发展,针对现 阶段贵州大数据产业和金融集聚的特点,文章首先了解了大 数据产业与金融集聚相关文献;然后,选取 2013-2017 年贵 州九个地州市的指标原始数据,分别运用犹豫模糊语言 TOPSIS 法和犹豫模糊语言 PROMETHEE 方法对贵州九个 地州市的大数据产业发展水平和金融集聚水平进行测度;最 后运用耦合协调模型计算贵州九个地州市的大数据产业与金 融集聚的耦合协调度,并提出相关政策建议。实证结果表 明:贵阳市为大数据产业与金融集聚中度协调发展,遵义市 为勉强协调发展,六盘水、毕节、黔西南是轻度失调衰退, 剩余州市为中度失调衰退。样本期间内,总体上贵州大数据 产业与金融集聚耦合协调程度不断提高,但区域间不均衡现 象较为明显。 关键词—大数据产业,金融集聚,耦合协调,犹豫模糊语 言 TOPSIS 法,犹豫模糊语言 PROMETHEE 法 I. 引言 围绕实施国家大数据战略,加强大数据在金融行业 领域的深入应用,促进跨行业大数据融合创新,推动大 数据与金融行业领域的融合发展,对促进经济转型和创 新发展有重大意义。贵州正在建立大数据产业投融资体 系,鼓励金融机构为符合条件的大数据企业给予信贷支 持,围绕大数据产业开发和创新金融产品,延伸服务网 络,为贵州大数据项目融资提供支撑 [1] 。贵州建成全国 领先的大数据资源集聚地和大数据应用服务示范基地, 需要财政金融的大力支持和健全大数据产业投融资机 制,大数据产业的发展也有利于金融行业改变传统的运 行方式和运行机制,促进大数据金融服务业的发展。因 此,对大数据产业与金融集聚协调发展现状进行分析, 有利于把握大数据产业与金融行业发展差异,促进行业 大数据应用发展。 目前而言,国内外学者大多集中于对金融集聚与产 业发展之间关系的研究。国外研究中,Rajan 和 Zingales (1998)[1]通过建立理论模型研究金融发展到一定程度 形成的金融集聚与产业结构之间的关系;Carlin 和 Mayer(2003)[2]从不同类型的金融结构角度出发,研 究其对产业的影响;Audress 等(2006)[3]阐述了金融集 聚带来的溢出效应显著提高了地区间的技术创新和产业 升级;Cotugno 等(2013)[4]认为金融集聚下,产业结 构升级出现的空间溢出效用不但促进本地区的产业升 级,同时也促进了周边地区产业的发展。国内研究中, 陈峰(1991)[5]最早研究了金融发展与产业发展之间的 关系;孙晶和蒋伏心(2013) [6]借助空间滞后模型和空间 误差模型进行研究发现,金融集聚对区域产业结构升级 存在空间溢出效应;杨义武和方大春(2013)[7]运用面 板向量自回归模型研究金融集聚与产业结构变迁的互动 关系;邓向荣和刘文强(2013)[8]实证分析了金融集聚 对产业结构升级作用;郭露和丁峰(2015)[9] 运用协调 发展度评价的改进模型对长三角地区 16 个地级市的三 大产业结构与金融集聚的分布进行综合评价与比较;何 宜庆等(2015)[10]运用物理学中的三者耦合模型,将金 融要素集聚、区域产业结构和生态效率三个系统相结 合,进行了耦合协调实证研究;于斌斌(2017)[11]认为 金融集聚对经济增长的影响是通过促进产业结构升级实 Fourth Symposium on Disaster Risk Analysis and Management in Chinese Lit","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80291783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Interannual Variation and Hazard Analysis of Meteorological Disasters in East China 中国东部气象灾害年际变化及危害分析
Pub Date : 2020-01-01 DOI: 10.2991/jracr.k.200117.004
Jun Shi, L. Cui, Zhongping Shen
Meteorological disaster is one of the natural disasters that cause the most casualties and losses in the world [1–3]. In recent years, due to global warming and the intensification of human activities, meteorological disasters (such as floods, droughts, hurricanes, extreme heat or cold, snowstorms, etc.) in many countries have become more frequent [4–7]. These disasters pose a serious threat to people’s life and property security, agricultural production, water resources and ecosystems [8–11]. China is one of the countries in the world with frequent meteorological disasters, various kinds of disasters and severe losses from disasters. The losses caused by meteorological disasters account for about 70% of the total losses of all kinds of natural disasters in China [1]. Wu et al. [12] showed that meteorological disasters accounted for 55% of the deaths and 87% of the direct economic losses caused by natural hazards in China during 1994–2013. Hence, the variations and trends of meteorological disasters are of great significance to people’s life and property, national economic construction and ecological security in China [13–15].
气象灾害是世界上造成人员伤亡和损失最多的自然灾害之一[1-3]。近年来,由于全球变暖和人类活动的加剧,许多国家的气象灾害(如洪水、干旱、飓风、极热或极冷、暴风雪等)更加频繁[4-7]。这些灾害对人民生命财产安全、农业生产、水资源和生态系统造成严重威胁[8-11]。中国是世界上气象灾害频发、灾害种类繁多、灾害损失严重的国家之一。气象灾害造成的损失约占中国各类自然灾害总损失的70%。Wu等[b[12]]研究表明,1994-2013年,气象灾害占中国自然灾害死亡人数的55%,直接经济损失的87%。因此,气象灾害的变化和趋势对中国人民生命财产、国家经济建设和生态安全具有重要意义[13-15]。
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引用次数: 3
Re-examining Political Risk Assessments in Volatile Regions 重新审视动荡地区的政治风险评估
Pub Date : 2019-11-01 DOI: 10.2991/jracr.k.191024.001
Ghaidaa Hetou
Political risk assessments are increasingly becoming a business imperatives for corporations interested in expanding their business operations into developing and emerging markets, which usually exhibit political uncertainty. Political risk associated with market entry and subsequent business operations is a slowly evolving subcategory of risk analysis, and one that has not lent itself to strict mathematical modeling and probability assessments. To counter the subjective nature of non-scientific assessments, conventional political risk analysis and country risk indexes aimed at standardizing the process within formulas to account for political and social factors, mimicking thereby a standardized approach, applicable to all countries. The persisting shortcoming in this process is that political and social factors are necessarily context specific, i.e. interconnected and part of a complex adaptive system, thereby cannot be correctly evaluated as independent static variables. The resulting indexes hence remained at an artificial interval level spanning from low to high risk, and in most cases devout of valuable and relevant content for the private sector or government agencies.
政治风险评估正日益成为有兴趣将业务扩展到发展中国家和新兴市场的公司的商业必需品,这些市场通常表现出政治不确定性。与市场进入和随后的业务操作相关的政治风险是风险分析的一个缓慢发展的子类别,它还不适合严格的数学建模和概率评估。为了克服非科学评估的主观性质,传统的政治风险分析和国家风险指数的目的是在考虑政治和社会因素的公式内使过程标准化,从而模仿一种适用于所有国家的标准化方法。这一过程中持续存在的缺点是,政治和社会因素必然是特定于环境的,即相互关联的,是复杂适应系统的一部分,因此不能作为独立的静态变量进行正确评估。因此,得出的指标保持在从低到高的人为区间水平,并且在大多数情况下对私营部门或政府机构没有价值和相关的内容。
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引用次数: 0
A Game Theory Approach for Multi-agent System Resources Allocation against Outside Threats 外部威胁下多智能体系统资源分配的博弈论方法
Pub Date : 2019-11-01 DOI: 10.2991/jracr.k.191024.003
Cheng-Kuang Wu, Xingwei Hu
Emergency Response Systems (ERS) and Homeland Security Advisory Systems (HSAS) are both centralized Multiagent Systems (MASs) which delegate multiple interacting agents to resist outside attacks. However, the effectiveness of these MASs as a means to defend entire large-scale geographic regions is constrained by the available resources. The system administrator faces a density of agent deployment dilemmas, where the disposition of more agents easily leads to higher costs. These systems also lack specific measures for rational decision-making, and do not apply mathematical models to capture the interactions between attacker and defender. The administrator of a MAS should have a tool to measure the strength of the attacks and the resistance capability of the response agents. By considering the utilities of moves available to the attacker and the defender, we can find a way to build a rating system for decision making [1].
应急响应系统(ERS)和国土安全咨询系统(HSAS)都是集中式多智能体系统(MASs),它委托多个相互作用的智能体来抵御外部攻击。然而,这些群众作为保护整个大规模地理区域的手段的有效性受到现有资源的限制。系统管理员面临代理部署密集的困境,部署更多的代理很容易导致更高的成本。这些系统也缺乏理性决策的具体措施,并且不应用数学模型来捕捉攻击者和防御者之间的相互作用。MAS的管理员应该有一个工具来测量攻击的强度和响应代理的抵抗能力。通过考虑攻击者和防御者可用的移动效用,我们可以找到一种方法来构建决策的评级系统[1]。
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引用次数: 2
Evaluation on Technology Innovation Efficiency of Big Data Enterprises Based on DEA 基于DEA的大数据企业技术创新效率评价
Pub Date : 2019-11-01 DOI: 10.2991/jracr.k.191024.004
Xinpu Wang, Mu Zang
Data become the basic strategic resources of the country. The Platform for Action to Promote Big Data Development and the Big Data Industry Development Plan (2016–2020) issued by the State Council and the Ministry of Industry and Information Technology in 2015 have aroused strong repercussion. “Outline” points out that encouraging financial institution to strengthen and improve financial services, increase support for big data enterprises, and continue to enhance the prosperity of the big data industry. The Development Planning of Big Data Industry (2016–2020) [1] proposes that promoting the development of big data industry is of great significance to improving government governance ability, optimizing public services for people’s livelihood, promoting economic transformation and innovation and development; studying and establishing an evaluation system for the development of big data industry is of great significance to the construction of big data resources, the degree of openness and sharing, the ability of industrial development and the level of application in China and other regions. It is of great significance to monitor, analyze and evaluate the development of the big data industry, compile and publish the development index of the big data industry, and guide and evaluate the development of the national big data.
数据成为国家的基本战略资源。2015年国务院、工业和信息化部发布的《促进大数据发展行动纲要》和《大数据产业发展规划(2016-2020年)》引起强烈反响。《纲要》指出,鼓励金融机构加强和改进金融服务,加大对大数据企业的支持力度,持续促进大数据产业繁荣发展。《大数据产业发展规划(2016-2020年)》[1]提出,推进大数据产业发展,对提高政府治理能力、优化公共民生服务、促进经济转型和创新发展具有重要意义;研究建立大数据产业发展评价体系,对中国和其他地区大数据资源建设、开放共享程度、产业发展能力和应用水平具有重要意义。对大数据产业发展进行监测、分析和评价,编制和发布大数据产业发展指标,指导和评价国家大数据发展具有重要意义。
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引用次数: 2
期刊
Journal of Risk Analysis and Crisis Response JRACR
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