Evaluation of Productive Plant Landscapes in Cold Regions Based on a Multiple Cropping Model

Four varieties of each rapeseed and buckwheat were planted in different sowing periods to explore a variety of planting patterns.A theoretical foundation was provided for the innovative application of cold region productive plant landscapes.The analytic hierarchy process was employed to develop a model for the evaluation of multiple cropping systems.A comprehensive evaluation was conducted to study 10 indicators in plant type,flower color,flowering period,flower volume,branch coverage,plot average yield,number of grains per plant,yield per plant,thousand-grain quality and ecological adaptability in four different varieties of each rapeseed and buckwheat.The results indicated that flower color,ecological adaptability,plot average yield and flower volume were the most important indicators for the value of productive plant landscapes in cold regions.Concerning the sowing period,the optimal combination of varieties and planting times were March 31 for Qingza No.5(rapeseed)and July 18 for Xinong T1211(buckwheat).

Multiple-Attribute and Multilevel Synthetic Evaluation Model and Its Application

On the basis of analyzing the flaws of present multiple-attribute and multilevel evaluation methods, concerning the problem of characteristics of the multiple-attribute and multilevel system s appraisal and the particular emphasis on the respective attributes in the evaluation process, as well as its relevance to the environment, an optimal attribute system is proposed, and the multiplicative analytic hierarchy process (MAHP) is used to obtain subjective weight coefficients and the objective weight coefficient evaluating method is given. The deviation between the index value of each level and the values of the same index of other levels are formulated, and an optimal model is gained, thus establishing the weight coefficients of the whole optimal attribute system. Furthermore, the detailed implementation procedure of this method is introduced. Besides, favorable results have been gained by applying the model to the practical problems of economic evaluation.

New approach to multiple attribute decision making with interval numbers

In an ambiguous decision domain, the evaluation values of alternatives against attributes would be interval numbers because of the inherent, uncertain property of the problems. By using a number of linear programming models, Bryson and Mobolurin propose an approach to compute attribute weights and overall values of the alternatives in the form of interval numbers. The intervals of the overall values of alternatives are then transformed into points or crisp values for comparisons among the alternatives. However, the attribute weights are different because of the use of linear programming models in Bryson and Mobolurin＇s approach. Thus, the alternatives are not comparable because different attribute weights are employed to calculate the overall values of the alternatives. A new approach is proposed to overcome the drawbacks of Bryson and Mobolurin＇s approach. By transforming the decision matrix with intervals into the one with crisp values, a new linear programming model is proposed, to calculate the attribute weights for conducting alternative ranking.

Method for multiple attribute decision making based on incomplete linguistic judgment matrix

With respect to the multiple attribute decision making problems with linguistic preference relations on alternatives in the form of incomplete linguistic judgment matrix, a method is proposed to analyze the decision problem. The incomplete linguistic judgment matrix is transformed into incomplete fuzzy judgment matrix and an optimization model is developed on the basis of incomplete fuzzy judgment matrix provided by the decision maker and the decision matrix to determine attribute weights by Lagrange multiplier method. Then the overall values of all alternatives are calculated to rank them. A numerical example is given to illustrate the feasibility and practicality of the proposed method.

The Discussion of Analytic Hierarchy Process for Quantitative Type Multiple Attribute Decision Systems Analysis

In this paper,we discussed quantitative type multiple attribute decision problem with rank scale and Analytic Hierarchy Process. It not only is a reasonable generalization of Analytic Hierarchy Process in multiple attribute decision problem, but also provide a effective method for quantitative type multiple attribute decision problem.

Maintenance Decision Making Model with Multiple Attribute Optimization

An effective maintenance schedule can largely improve productivity and reduce maintenance costs for enterprises. Many factors, such as resource, production, cost and crew, should be considered when we make maintenance plans. However, it is difficult to meet all requests of the production targets in practical engineering.The multiple attribute decision making for equipment maintenance is proposed in this paper, and the multiple objectives decision making method is utilized to solve the problem in the maintenance process. In the particular environment and resources, a case is studied to illustrate the model and methods. The model gives the optimal maintenance plan with the analytic hierarchy process method in accordance with the particular criteria. It has been proved that this model and decision methods are scientific and operable.

密室逃脱类场所人员疏散影响因素研究

准确识别火灾等突发事件时影响密室逃脱类场所人员疏散的因素,并客观系统分析因素间的层次关系和重要程度,对密室逃脱类场所的应急疏散至关重要。基于密室逃脱类场所行业规范和现状,从人员、建筑结构、环境、消防管理4个维度提取了26个影响因素,采用AISM(对抗解释结构模型)及MICMAC(交叉影响矩阵相乘法)构建密室逃脱类场所人员疏散影响因素3级递阶结构模型,综合分析因素间作用关系,并分析因素与管理层、运营层、玩家层3类主体对应责任关系,然后联合ANP(网络层次分析法)确定各影响因素的权重和排序。结果表明:影响密室逃脱类场所人员疏散的深层根本因素主要为制度与规程编制完备性、密室剧情类型、空间组合形式、空间嵌套层数等,其可通过驱动密室场所经营位置、门锁联动性、空间内部昏暗度、道具种类与数量、NPC(非玩家角色)疏散引导能力等中层特性影响因素优化,规范消防设施完备性、应急预案编制情况、安全教育与培训情况等关键共性影响因素,最终提升玩家应急疏散能力。

CMIP6模式模拟的人类活动和自然强迫对全球地表气温多尺度变化的影响

量化人类活动在气候变化中的定量贡献是气候变化检测归因研究的核心科学问题,也是提高气候变化预测和预估水平的重要科学基础.本文基于最新的第6次国际耦合模式比较计划(CMIP6)多模式历史归因模拟试验(DAMIP),检测了人为因素(ANT)和自然因素(NAT)对近百年(1915—2014年)全球地表气温多尺度变化的影响,归因了温室气体(GHG)、气溶胶(AA)、土地利用(LU)等不同人为因素对全球地表气温长期变化的相对贡献及南北半球差异.结果显示,近百年来人为因素引起的全球陆地实际增温约为1.1℃(0.8℃~1.3℃),对南北半球的贡献则分别约为0.7℃和1.2℃;全球大多数区域人为排放GHG和AA的显著作用在1960—1980年期间就能够被检测到,其中北半球AA的冷却作用要超前于GHG的增温效应;气候系统内部自然变率是调制大多数区域气温年代际(10~30年)及多年代际变率(30~60年)的主导因子,而人为和自然外强迫在全球地表气温年代际变率中的方差贡献约为5%~20%,但二者在北半球尤其在东亚和欧洲中高纬度地区地表气温多年代际变率中的方差贡献可达50%.人为因素强迫可使近50年(1965—2014)极端高温事件的发生风险概率增加3倍,其中北半球发生风险要高于南半球.

Continuous Multiplicative Attribute Graph Model

Network modeling is an important approach in many fields in analyzing complex systems. Recently new series of methods have emerged, by using Kronecker product and similar tools to model real systems. One of such approaches is the multiplicative attribute graph(MAG) model, which generates networks based on category attributes of nodes. In this paper we try to extend this model into a continuous one, give an overview of its properties, and discuss some special cases related to real-world networks, as well as the influence of attribute distribution and affinity function respectively.

优化逆序发生率的RED-TOPSIS模型

为解决TOPSIS模型中存在的逆序问题,本文提出一种基于纪录值的TOPSIS模型,称为RED-TOPSIS模型,该模型针对有纪录值数据的多属性决策问题,采用区间化公式或最大最小化公式作无量纲化处理,利用纪录值构造理想解。由于纪录客观存在且有不易打破的特点,以此确定的理想解具有近似于绝对理想解的稳定性兼具相对理想解的客观性,使得RED-TOPSIS模型理论上仅当纪录被打破时才可能产生逆序,从而在实际应用中易于操作且能大幅降低逆序现象的发生。

A Quantity Model for Controlling and Measuring Software Quality Based on the Expert Decision-Making Algorithm

Researchers have been active in the field of software engineering measurement over more than 30 years. The software quality product is becoming increasingly important in the computerized society. Target setting in software quality function and usability deployment are essential since they are directly related to development of high quality products with high customer satisfaction. Software quality can be measured as the degree to which a particular software program complies with consumer demand regarding function and characteristics. Target setting is usually subjective in practice, which is unscientific. Therefore, this study proposes a quantity model for controlling and measuring software quality via the expert decision-making algorithm-based method for constructing an evaluation method can provide software in relation to users and purchasers, thus enabling administrators or decision makers to identify the most appropriate software quality. Importantly, the proposed model can provide s users and purchasers a reference material, making it highly applicable for academic and government purposes.

面向矿产资源储量计算的三维训练图像构建方法

矿产资源储量计算有助于合理开发利用矿产资源,目前多点地质统计学是矿产资源储量计算的热门技术,但多点地质统计学中高质量三维训练图像构建较为困难。因此,提出了一种面向矿产资源储量计算的三维训练图像构建方法。该方法首先基于原始钻孔等数据构建三维地质模型,并对其使用不规则四面体网格剖分得到体元模型;然后基于钻孔属性数据采用插值算法构建规则体元品位模型,并对体元模型进行欧氏距离的属性赋值得到三维训练图像;最后采用多点地质统计学改进的Snesim算法构建搜索树获取条件概率,并进行相关性的属性融合给矿体待估值体元模型赋属性,进而计算矿产资源储量。以黑牛洞Ⅰ-3号矿体为例,计算得到该矿体铜平均品位为2.90%,与开采后的铜平均品位2.33%相比,相差仅0.57个百分点,证明了所提方法的正确性和有效性。

基于自然语言云化的TOPSIS方法及其应用

针对兼具自然语言标度和主观评分的复杂多属性决策问题,结合云模型理论构建了基于自然语言云化的TOPSIS方法。首先,通过设计非线性规划改进云模型熵的计算,利用云雾化性质得到超熵,将自然语言标度转换为云模型。其次,将主观评分转换为评价云,得到多属性决策云矩阵,根据TOPSIS定义建立多属性评价方法。最后,将所提方法应用于物流园区选址方案评估问题,通过与已有文献中的方法和传统TOPSIS方法进行对比,验证了所提方法的有效性。

基于多属性决策模型的传统长柄农具改良设计方法

目的 提出一种多属性决策模型,进行以人为本的传统长柄农具改良设计研究,旨在改善农民在从事农业生产活动中的使用体验,减轻身体负担,提升工作效率。方法 首先,以农民用户为中心,以JACK人机仿真数据为依据提出具体需求,利用层次分析法对需求权重进行计算,明确设计目标和亟需解决的设计问题;其次运用TRIZ工具中的物场模型分析问题,根据对应的标准解决设计问题,以此为依据完成改良设计方案,最后通过JACK仿真软件验证该方法的合理性。结论 构建了融合层次分析法、TRIZ理论、JACK仿真评估的多属性决策模型,完成了传统长柄农具改良方法研究,并且以铁锨为例进行了设计验证,为传统长柄农具的改良设计提供了一条有效路径和实施策略。

考虑因素属性及层级关系的十字路口汽车事故致因分析

为了从层次划分的角度分析十字路口汽车交通事故发生的深层原因,引入解释结构模型和交叉影响矩阵相乘法模型并加以改进,利用国家车辆事故深度调查体系中4个省份共290起十字路口汽车交通事故数据,建立事故致因体系。通过构建改进灰色关联度矩阵与解释结构模型并进行混合建模,揭示各因素间的层级作用关系。同时,采用交叉影响矩阵相乘法构建驱动力依赖性坐标图以进一步分析各致因因素间的相互作用关系。结果显示:十字路口汽车交通事故致因可划分为6级3阶的递阶结构,其中道路状况和交通管理因素是最根本因素,道路设施因素是最关键的间接因素,人的影响是最直接因素。这表明优先解决不良道路状况和其他驱动力因素会明显减少汽车事故发生,提高道路交通安全水平。

渝东鄂西地区下组合复杂构造速度建模技术及应用

针对复杂构造区地震资料叠前深度偏移速度建模这一问题,充分认识到速度模型是制约复杂构造地震资料成像的关键,在速度模型的建立过程中需要地质认识的指导,采用了浅、中、深层速度融合建模技术、多信息约束的网格层析技术、嵌入填充速度体建模技术等建模方法,提高速度模型精度,改善偏移剖面的成像质量。该速度建模技术的应用,为渝东鄂西地区下组合复杂构造精细解释工作提供良好的资料基础,证实了该复杂构造速度建模技术的有效性。

Regression model for estimation of attribute reliability

In this paper,a regression model is developed to estimate attribute reliability in the evidential reasoning(ER)context.By analysing the difference between attribute weight and attribute reliability,a general qualitative definition of attribute reliability is provided.The reliability of an attribute is quantitatively measured in consistence with the qualitative definition in the context of the ER approach.A regression model is then constructed to generate attribute reliabilities by minimising the maximum differences between the real value of attribute reliability and its estimation.Within the post-optimal solution space of attribute reliabilities,an optimisation model is constructed to determine the expected utilities of each alternative in order to generate solutions to multiple attribute decision analysis problems.Asale place selection problem in Qingyang County of Chizhou in Anhui province of China is analysed using the proposed regression model to demonstrate its detailed implementation process,validity and applicability.

应用多属性决策的威胁评估方法

威胁评估是作战系统需要完成的功能之一 ,对实现指挥控制系统自动化是非常重要的。威胁评估涉及的因素比较多 ,目前还没有统一的方法。威胁评估实际上是一个推理、决策的行为 ,而决策理论为推理、决策提供了理论方法。根据威胁评估和多属性决策的特点 ,提出了基于多属性决策的威胁评估模型和方法 ,应用隶属函数及逼近于理想的排序法 (TOPSIS)分析 ,并通过示例说明应用多属性决策的威胁评估方法。

高维云模型及其在多属性评价中的应用

提出核空间高维云模型并将其应用于多属性评价问题.基于样本取值范围计算云模型的数字特征,生成云模型表达样本属性值与其属于期望值的隶属度之间的关系.在一维云模型的基础上,建立样本的多属性核空间高维云模型.对核空间内的样本,高维云模型的隶属度取值为1;基于样本在核空间高维云模型中的隶属度对样本进行多属性评价;应用核空间高维云模型,对地理信息系统内选定区域进行评价,选出适合作为观察所的位置,并对选取结果进行分类.该模型的多属性评价效果良好.

基于灰色关联度求解指标权重的改进方法

针对决策过程中指标权重的确定问题,在分析现有权重确定方法不足的基础上,提出了一种基于灰色关联度求解指标权重的改进方法,并对其性质进行了研究。该方法是对决策者给出的主观权重经验判断矩阵进行充分挖掘,提取出一个公共比较权重数列,并建立一个简易的数学模型,使确定的权重同时反映主观程度和客观程度。算例分析说明了该改进方法的简单性与实用性。