基于EAHP的阿拉尔垦区水资源可持续开利用评价指标研究

根据阿拉尔垦区水资源开发现状,选取本地区水资源可持续开发利用评价指标,构建了阿拉尔垦区水资源可持续开发利用评价指标的层次结构模型.然后在专家打分基础上,应用可拓层次分析法求的各个影响水资源可持续开发利用评价指标的相对权重进行排序,最后对结果进行分析,为阿拉尔垦区水资源可持续开发利用提供理论依据.     

基于EAHP的阿拉尔垦区水资源可持续开发利用评价指标研究

根据阿拉尔垦区水资源开发现状,选取本地区水资源可持续开发利用评价指标,构建了阿拉尔垦区水资源可持续开发利用评价指标的层次结构模型.然后在专家打分基础上,应用可拓层次分析法求的各个影响水资源可持续开发利用评价指标的相对权重进行排序,最后对结果进行分析,为阿拉尔垦区水资源可持续开发利用提供理论依据.     

基于PSR-EAHP的农业生产活动的环境效应评价指标体系研究——以阿拉尔垦区为例

为了研究农业生产活动对环境的影响,以位于干旱区且生态环境极其脆弱的阿拉尔垦区为例,构建了农业生产活动的环境效应评价指标体系.首先在压力-状态-响应框架下选取指标,然后运用可拓层次分析法,在专家打分的基础上计算可拓区间数判断矩阵,求出其满足一致性条件的权重向量并进行层次单排序,层次单排序归一化结果即为各层级指标的权重向量.指标体系的建立对推动垦区经济、社会、生态的可持续发展、垦区产业结构发展战略的调整以及生态环境的保护和恢复政策的制定有一定的指导作用.     

基于可拓层次分析法的阿拉尔市生态指标体系构建

阿拉尔工业园的建立给阿拉尔市的经济发展带来了前所未有的机遇,然而工业化进程中出现的环境问题也是显而易见的.在分析阿拉尔市生态特征的基础上,首先建立了阿拉尔生态指标的层次结构模型,然后在专家打分的基础上通过可拓层次分析法构建了阿拉尔市生态指标体系.体系的构建有助于阿拉尔市城市环境问题进行准确的评价与定位,为阿拉尔工业园日后的发展起到一定的指导性作用.     

轴对称Navier-Stokes方程的一类正则性准则

龙卷风是一种严重的自然灾害,科学家们希望能够减少龙卷风造成的生命损失和财产损失.而Navier-Stokes方程的轴对称结构对龙卷风的数学分析和数值模拟都具有重要意义.考虑轴对称的三维不可压Navier-Stokes方程,得到了一类关于分量Γ的正则性准则.     

政府资本、农业技术投入与农业经济增长——基于广西96个县域面板门槛模型的实证

农业经济增长离不开政府资本支持,也离不开持续的农业技术投入.应用Hansen面板门槛模型,基于2004-2018年广西96个县域的面板数据,探究政府资本、农业技术投入对农业经济增长的影响.结果发现:1)政府资本、农业技术投入对农业经济增长的影响具有显著门槛特征,无论政府资本处于什么水平,农业技术投入均对农业经济增长有显...     

集体土地作价人股农业特色小镇路径演化分析

"乡村振兴战略"背景下农业特色小镇是辐射带动新农村发展的重要载体而土地是农业特色小镇建设需要解决的核心问题.针对农村集体经济组织在集体土地作价入股农业特色小镇策略选择问题,基于演化博弈思想,构建农村集体经济组织与企业的演化博弈模型,探究集体土地作价入股农业特色小镇路径演化问题,最后,利用Matlab工具对双方选择合作策略的影响因素进行数值仿真分析.研究发现:集体土地作价入股农业特色小镇,企业与农村集体经济组织的合作策略选择与集体土地的未来收益、奖惩机制、投入成本、运营风险有关.针对研究结果提出了相关政策建议,有利于促进双方合作,对激活农村存量土地、加强农村建设、发展特色农业、拉动农村经济、实现乡村振兴战略目标具有重要意义.     

我国农业技术扩散环境的评价研究

观察我国大陆地区31个省市(港、澳、台除外)的农业技术扩散环境,从自然环境、社会环境、科技环境、经济环境、政策环境等五个方面建立评价指标体系,运用熵权法与PROMETHEE II方法进行建模与实证分析,并进行了31省市的空间分布分析与分类研究.基于2014年的研究结果表明:农业科技环境、农业经济环境是影响农业技术扩散的重要因素;各省市在5方面农业技术扩散环境指标上有较大差异,总体而言,农业技术扩散环境可分为5种不同等级,北京、浙江、新疆等省市具有较为优越的环境条件,而安徽、山西、甘肃等地的农业技术扩散环境条件较差;全国农业技术扩散环境水平较为均衡,存在局部的区域聚集特征,但梯度转移规律不明显,省际间溢出效应不显著.根据研究结论,为全国以及各省市系统优化农业技术扩散环境提出了对策建议.     

农村劳动力资源可持续发展的层次分析

解决“三农”问题的关键是增加农民收入,而增收的主要办法,一是实现农业产业化增加农业收入;二是进行农村劳动力转移增加非农收入.大量的劳动力涌入大中城市对部分行业就业进行了关键的补偿,但同时对城市人口就业也造成了一定的压力,因此能否进行农村劳动力资源可持续的开发成为制约经济、社会、环境等协调发展的重要因素.文章根据可持续发展评估体系,把影响农村劳动力资源可持续发展的系统分为经济、社会、环境、支撑四个子系统,根据各子系统对其可持续开发的影响建立指标体系,用层次分析法分析得到各指标的权重,根据权重制定相应的农村劳动力资源可持续开发的策略.     

经济政策不确定性、区域差异与投资效率——基于固定效应面板模型

从区域差异视角出发,研究经济政策不确定性对我国农业上市公司投资效率的影响.研究发现,经济政策不确定性升高时农业上市公司投资效率降低,并且对于中西部地区农业上市公司这一效应更为明显.提出中西部地区农业上市公司要充分考虑市场中的经济因素,把握良好的投资机会并做出最优的投资决策,公司管理层应该正确判断投资项目未来前景,从而提高公司投资效率的建议.     

A longitudinal study of evolving networks in response to natural disaster

In this study, we present a longitudinal analysis of the evolution of interorganizational disaster coordination networks (IoDCNs) in response to natural disasters. There are very few systematic empirical studies which try to quantify the optimal functioning of emerging networks dealing with natural disasters. We suggest that social network analysis is a useful method for exploring this complex phenomenon from both theoretical and methodological perspective aiming to develop a quantitative assessment framework which could aid in developing a better understanding of the optimal functioning of these emerging IoDCN during natural disasters. This analysis highlights the importance of utilizing network metrics to investigate disaster response coordination networks. Results of our investigation suggest that in disasters the rate of communication increases and creates the conditions where organizational structures need to move at that same pace to exchange new information. Our analysis also shows that inter-organizational coordination network structures are not fixed and vary in each period during a disaster depending on the needs. This may serve the basis for developing preparedness among agencies with an improved perspective for gaining effectiveness and efficiency in responding to natural disasters.     

基于委托—代理理论的自然灾害保险模型

灾害保险是筹措防灾救灾资金的重要手段之一，文章运用博弈论中的委托—代理理论建立自然灾害的保险模型，对有关自然灾害的最优保险费率的确定及其特征进行了研究，为开展自然灾害的保险业务提供理论依据     

三峡库区地质灾害防治效果的评价与分析

三峡库区地质环境和地质条件十分复杂,是地质多灾并发较严重的地区之一.而地质灾害防治是一个世界性的难题,从灾害预警体系的建立、到工程治理和灾民避让搬迁,都需要消耗大量的人力、物力和财力.从三峡库区地质灾害防治的现状出发,在深入走访和调查研究的基础上,结合有关企业绩效评价和工程项目后评价的相关理论和方法,在优化、整合的基础上首次提出了三峡库区地质灾害防治效果的评价指标体系,并对指标进行细化分解,结合系统工程的有关理论,采用多层次模糊综合评价的方法对三峡库区地质灾害防治效果进行科学、系统的评价和分析,以便及时发现三峡库区地质灾害防治过程中存在的问题和不足,为今后三峡库区乃至全国的地质灾害防治工作提供借鉴和参考.     

OPTIMAL HARVESTING WITH DENSITY DEPENDENT RANDOM EFFECTS

We consider the effect of sudden large, randomly occurring density dependent disasters on the optimal harvest policy and optimal expected return for an exploited population. The population is assumed to grow logistically with disasters occurring on a time scale very short compared to the natural growth scale. The case of a density dependent disaster frequency is also treated. Stochastic dynamic programming is used in the optimization. For a set of realistic field data it is found that random effects typically have a significant effect on both optimal return and optimal effort levels. The effect of density dependence is far more pronounced for optimal return than for optimal effort levels.     

ARIMA(p,d,q)与GM(1,1)模型在洪涝灾害预测中之比较研究——以广东省做实证分析

运用经济时间序列ARIMA(p,d,q)模型与GM(1,1)模型对广东省的洪涝灾害进行了预测.研究结论显示,所建立的ARIMA(p,d,q)模型能够较好的对洪涝灾害进行预测,模型可以运用到各种主要气象灾害风险预测与管理中,但所建立的GM(1,1)模型虽然具有很好的精度,但预测效果并不好.这充分体现了模型选择在预测过程中的重要性.     

A lexicographical goal programming based decision support system for logistics of Humanitarian Aid

Each year people affected by disasters, either natural or human-made, can be counted by millions. When a major disaster strikes a country, local and international communities usually respond with an outpouring of assistance, which has to be efficiently managed in order to arrive where it is needed as soon as possible and under adverse conditions. Despite its importance, not until recently has Humanitarian Logistics received much attention as a specific field, and there is a lack of specific tools. In this work, a lexicographical goal programming model for distribution of goods to the affected population of a disaster in a developing country is presented, which sustains a decision support system currently in development.     

The detection and location estimation of disasters using Twitter and the identification of Non-Governmental Organisations using crowdsourcing

This paper provides the humanitarian community with an automated tool that can detect a disaster using tweets posted on Twitter, alongside a portal to identify local and regional Non-Governmental Organisations (NGOs) that are best-positioned to provide support to people adversely affected by a disaster. The proposed disaster detection tool uses a linear Support Vector Classifier (SVC) to detect man-made and natural disasters, and a density-based spatial clustering of applications with noise (DBSCAN) algorithm to accurately estimate a disaster’s geographic location. This paper provides two original contributions. The first is combining the automated disaster detection tool with the prototype portal for NGO identification. This unique combination could help reduce the time taken to raise awareness of the disaster detected, improve the coordination of aid, increase the amount of aid delivered as a percentage of initial donations and improve aid effectiveness. The second contribution is a general framework that categorises the different approaches that can be adopted for disaster detection. Furthermore, this paper uses responses obtained from an on-the-ground survey with NGOs in the disaster-hit region of Uttar Pradesh, India, to provide actionable insights into how the portal can be developed further.

     

Multi-criteria logistics modeling for military humanitarian assistance and disaster relief aerial delivery operations

Given that it is not always feasible to reach an affected area via land or sea within the first week following a natural disaster, aerial delivery provides the primary means to rapidly supply the affected population. Further, it is often the case that high density delivery of humanitarian aid supplies are taken over by non-friendly groups within the affected population. By using direct airdrop systems to deliver large quantities of individually wrapped food and water items, dispersion among the affected disaster relief population will occur more quickly. In this paper, we proffer a multiple criteria decision analysis (MCDA) framework to optimize the military humanitarian assistance/disaster relief (HA/DR) aerial delivery supply chain network. The model uses stochastic, mixed-integer, weighted goal programming to optimize network design, logistics costs, staging locations, procurement amounts, and inventory levels. The MCDA framework enables decision-makers to explore the trade-offs between military HA/DR aerial delivery supply chain efficiency and responsiveness, while optimizing across a wide range of real-world, probabilistic scenarios to account for the inherent uncertainty in the location of global humanitarian disasters as well as the amount of demand to be met.     

考虑双方感知满意度的应急资源再配置方法

突发事件常诱发次生灾害,在外界大规模应急资源配送前,发挥区域互救优势,共享原生灾害点应急资源进行资源再配置是及时响应次生灾害的重要手段之一。本文尝试将灾民心理因素融入到应急资源的再配置问题中,基于前景理论提出了原生灾害点灾民的感知满意度模型,结合生存概率曲线对次生灾害点灾民感知满意度进行刻画,构建了考虑双方灾民感知满意度的多目标优化模型。此外,引入缩放系数和违反约束检查函数,改进多目标粒子群算法以加快算法初始化,进而提升模型求解效率。最后,本文通过算例验证了模型和算法的可行性和科学性,并与传统资源配置问题进行了对比,为具有连锁反应的突发事件应急管理提供决策支持。