地震属性协同的断层解释方法研究——以埕岛油田主体馆上段为例

油藏进入到精细开发阶段,对断层的描述提出更高的要求,一方面是对大断棱的精细刻画,另一方面是对低级序断层的有效识别及描述。基于此,以埕岛油田主体馆上段为例,利用本区丰富的地震资料,在合成地震记录标定的基础上,对研究区的各类属性特征分析,确定了研究区对断层的敏感属性为相干体属性和曲率属性,并在此基础上利用去除噪声,加强边界响应的蚂蚁体属性与相干、曲率相比较,蚂蚁体属性反映的断裂细节更丰富,断裂空间分布及平面组合形态更清晰,可有效提高断裂地震刻画精度。在地震剖面解释的基础上,结合研究区构造演化史,通过属性协同方法进行研究区断层的三维空间组合,最终明确了研究区的断裂系统发育。该研究成果为埕岛油田进一步挖潜剩余油、注采调整和开展化学驱研究提供了基础。

具有可撤销功能的属性协同访问控制方案

针对属性协同访问控制面临更复杂的权限动态更新问题,提出了具有属性即时撤销、属性级用户撤销和协同策略撤销的属性协同访问控制方案。所提方案给出了形式化定义与安全模型,以分组属性组内成员列表信息的变化反映用户权限的动态更新,进一步设计高效的重加密算法实现属性即时撤销和用户撤销。在协同策略撤销方面,利用转移节点的转移值特性,快速更新协同属性对应的密文以实现细粒度的协同策略撤销。安全证明表明,所提方案在选择明文攻击下能保证数据机密性,前向、后向安全性,并能抵抗共谋攻击。与已有方案相比,所提方案具有更完备的细粒度撤销功能以及更高的撤销运行效率。

基于云计算的多层量子精英属性协同约简算法

针对传统粗糙集属性约简算法无法高效处理日益增长的大数据问题,提出一种基于云计算的多层量子精英属性协同约简算法。该算法首先在云计算MapReduce模型下将大规模数据集划分到不同的进化蛙群中,分别获得各子种群最优解;然后构造一种基于多层量子蛙群精英向量的属性协同约简策略,挑选出具有全局搜索和局部精化最强优化能力的精英子种群向量,快速引导各子种群找到各自最小属性约简集,从而取得大规模数据集的全局最优属性约简集。实验结果表明,本文算法在大规模数据集上求解全局最优属性约简解的效率和精度具有明显优势,同时应用于电子病历数据库MRI分割效果表明其具有较强适用性。

直觉梯形模糊数航天项目组合配置属性协同研究

将直觉梯形模糊数和模糊测度引入航天型号项目组合配置领域,在定义项目组合配置正负协同概念的基础上定量描述了各决策属性之间的协同关系,提出了用不同情况下的属性协同Shapley值度量属性集对组合配置决策权重的方法,并构建了项目组合配置有序加权协同平均算子的决策模型,为解决航天企业多型号间的项目组合配置决策提供了一条有效途径。最后通过实例,对模型的有效性进行了检验。

一种灵活的多权威属性协同访问控制方案

属性协同访问控制是一种能解决多人协同访问的新型访问控制方案,但已有属性协同访问控制方案中的单个属性权威使其存在单点瓶颈问题,且协同功能缺乏灵活性。针对该问题,提出了一种更灵活的多权威属性协同访问控制方案。所提方案给出了协同访问结构的形式化定义,并引入多属性权威的概念,由多个属性权威负责管理属性和分发属性所对应的用户私钥,减轻了单个属性权威的计算负载。在实现协同时,利用密钥协商的思想,使得参与协同的任意两个属性权威仅需一次通信即可得到协同密钥。方案不需为参与协同的用户建立用户组,进一步使得协同更具灵活性、更贴合实际。安全性分析表明,所提方案能保证数据机密性、抵抗共谋攻击,与已有属性协同访问控制方案相比,具有更小的协同通信代价。

乡村基层法治建设中的弹性治理理念探析

当前乡村基层法治建设存在着“重资源整合,轻制度整合、模式整合”的治理趋势,以适应性与自主性为主要特征的弹性治理理念可以为乡村基层法治建设提供新的视角,对此趋势予以改善。弹性治理既能为乡村基层法治体系提供结构兼容、规则转化及理念补充的协同功能,又具备对乡村基层法治目标的实现具有切实效果和可行性、问题简易化及应用必要性等工具价值。将弹性治理理念融入乡村基层法治建设中,要遵循其自主性调适、兼容性创新、发展性规范与群众性监督的行动逻辑,并以组织弹性、目标弹性、规则弹性、方式弹性为抓手进行整体建构。

我国警察高等教育可拓特点与协同发展模式

本文基于我国警察高等教育改革与创新的研究实际,从理论与实践、学科与行业、专业与能力以及知识与经验的多属性角度,指出了目前警察高等教育存在的问题,提出了基于可拓知识的协同高等教育模式。运用系统理论、行为科学和社会选择理论,结合现代高等教育研究中具有可实现意义的理论和方法,对警察高等教育协同发展模式的基本框架、理论体系和实践过程进行了研究。结果表明:高等教育协同模式是学科与行业的协同、专业与职业能力的协同、教与学的协同。

B2B协同决策半自动一致性模型设计与实现

具有群一致特性的多属性协同决策(MACD)技术对于支持供应链中复杂多变、资源动态的大型群体供应商与客户B2B协同是十分重要的,现有的群一致性模型存在明显不足:难于管理较大群体,需要大量复杂手工操作以确保协同决策过程有效。提出了面向供应商与客户B2B协同的多属性协同决策半自动一致性模型(SACM)。SACM包括4阶段:(1)供应商与客户B2B协同资源数据初始化;(2)形成协同决策问题;(3)一致性达到过程及供应商与客户B2B协同计划生成;(4)协同计划执行实时监控分析及计划重构。研究结果描述了供应链中,供应商与客户B2B协同由单向、局部的优化扩展进化为具有多层一致性与抗风险性的闭环、反馈的计划与执行协同优化的有效方法,提出的方法深化了对供应商与客户B2B协同管理的理解。

Co-evolutionary cloud-based attribute ensemble multi-agent reduction algorithm

In order to improve the performance of the attribute reduction algorithm to deal with the noisy and uncertain large data, a novel co-evolutionary cloud-based attribute ensemble multi-agent reduction（CCAEMR） algorithm is proposed.First, a co-evolutionary cloud framework is designed under the M apReduce mechanism to divide the entire population into different co-evolutionary subpopulations with a self-adaptive scale. Meanwhile, these subpopulations will share their rewards to accelerate attribute reduction implementation.Secondly, a multi-agent ensemble strategy of co-evolutionary elitist optimization is constructed to ensure that subpopulations can exploit any correlation and interdependency between interacting attribute subsets with reinforcing noise tolerance.Hence, these agents are kept within the stable elitist region to achieve the optimal profit. The experimental results show that the proposed CCAEMR algorithm has better efficiency and feasibility to solve large-scale and uncertain dataset problems with complex noise.

Fuzzy multiple attribute decision-making model for synergic knowledge innovation in supply chain

The procedure of supply chain development is the process of continuously congregating knowledge and transforming knowledge.First,the precondition of synergic knowledge innovation in the supply chain is narrated.Then the characteristics of synergic knowledge innovation in the supply chain are analyzed,including complexity,accumulating and evolving process,and the cooperation of members and network integration.Due to the characteristics of multi-factors and uncertainties of the supply chain system,the fuzzy multi-attribution group decision-making model is introduced to solve the involved problem of synergic knowledge innovation in the supply chain.After elaborating on steps of using the fuzzy multiple attribute decision-making(MADM)model,the procedure of decision making for synergic knowledge innovation in the supply chain is explained from an example in the application of a fuzzy MADM model.The fuzzy MADM model,which amalgamates intuition and resolution decision-making can effectively improve the rationality of decision-making for synergic knowledge innovation in the supply chain.

Adaptive multicascade attribute reduction based on quantum-inspired mixed co-evolution

Due to the fact that conventional heuristic attribute reduction algorithms are poor in running efficiency and difficult in accomplishing the co-evolutionary reduction mechanism in the decision table, an adaptive multicascade attribute reduction algorithm based on quantum-inspired mixed co-evolution is proposed. First, a novel and efficient self- adaptive quantum rotation angle strategy is designed to direct the participating populations to mutual adaptive evolution and to accelerate convergence speed. Then, a multicascade model of cooperative and competitive mixed co-evolution is adopted to decompose the evolutionary attribute species into subpopulations according to their historical performance records, which can increase the diversity of subpopulations and select some elitist individuals so as to strengthen the sharing ability of their searching experience. So the global optimization reduction set can be obtained quickly. The experimental results show that, compared with the existing algorithms, the proposed algorithm can achieve a higher performance for attribute reduction, and it can be considered as a more competitive heuristic algorithm on the efficiency and accuracy of minimum attribute reduction.

Synergistically electronic tuning of metalloid CdSe nanorods for enhanced electrochemical CO_(2) reduction

Engineering the electronic properties of catalysts to target intermediate adsorption energy as well as harvest high selectivity represents a promising strategy to design advanced electrocatalysts for efficient CO_(2) electroreduction.Herein,a synergistical tuning on the electronic structure of the Cd Se nanorods is proposed for boosting electrochemical reduction of CO_(2) .The synergy of Ag doping coupled with Se vacancies tuned the electronic structure of the CdSe nanorods,which shows the metalloid characterization and thereby the accelerated electron transfer of CO_(2) electroreduction.Operando synchrotron radiation Fourier transform infrared spectroscopy and theoretical simulation revealed that the Ag doping and Se vacancies accelerated the CO_(2) activation process and lowered the energy barrier for the conversion from CO_(2) to;COOH;as a result,the performance of CO_(2) electroreduction was enhanced.The as-obtained metalloid Ag-doped CdSe nanorods exhibited a 2.7-fold increment in current density and 1.9-fold Faradaic efficiency of CO compared with the pristine CdSe nanorod.