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本文给出基于属性不等权重的等级反应模型(Grade Response Model, GRM)的属性层级方法(Attribute Hierarchy Method, AHM), 简记为属性不等权重的GRM-AHM。在属性层级结构下, 本文利用贝叶斯网与最小二乘两种方法, 提出了被试掌握属性的条件概率与属性权重的计算方法, 发现并解决了属性在不同的项目内权重有可能不相等的问题。本研究进一步将认知诊断推广到多级评分的情形。试验证明, 属性不等权重的GRM-AHM具有较高的判准率。 相似文献
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Many researchers have long observed some cases in which certain ranking irregularities can occur when the original analytic hierarchy process (AHP), or some of its variants, are used. This paper presents two new categories of ranking irregularities which defy common intuition. These ranking irregularities occur when one decomposes a decision problem into a set of smaller problems each defined on two alternatives and the same criteria as the original problem. These irregularities are possible when the original AHP, or some of its additive variants, are used. Computational experiments on random test problems and an examination of some real‐life case studies suggest that these ranking irregularities are dramatically likely to occur. This paper also proves that these ranking irregularities are not possible when a multiplicative variant of the AHP is used. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
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Oliver Chikumbo Erik Goodman Kalyanmoy Deb 《Journal of Multi-Criteria Decision Analysis》2015,22(3-4):133-159
A land use many‐objective optimization problem for a 1500‐ha farm with 315 paddocks was formulated with 14 objectives (maximizing sawlog production, pulpwood production, milksolids, beef, sheep meat, wool, carbon sequestration, water production, income and Earnings Before Interest and Tax; and minimizing costs, nitrate leaching, phosphorus loss and sedimentation). This was solved using a modified Reference‐point‐based Non‐dominated Sorting Genetic Algorithm II augmented by simulated epigenetic operations. The search space had complex variable interactions and was based on economic data and several interoperating simulation models. The solution was an approximation of a Hyperspace Pareto Frontier (HPF), where each non‐dominated trade‐off point represented a set of land‐use management actions taken within a 10‐year period and their related management options, spanning a planning period of 50 years. A trade‐off analysis was achieved using Hyper‐Radial Visualization (HRV) by collapsing the HPF into a 2‐D visualization capability through an interactive virtual reality (VR)‐based method, thereby facilitating intuitive selection of a sound compromise solution dictated by the decision makers' preferences under uncertainty conditions. Four scenarios of the HRV were considered emphasizing economic, sedimentation and nitrate leaching aspects—giving rise to a triple bottomline (i.e. the economic, environmental and social complex, where the social aspect is represented by the preferences of the various stakeholders). Highlights of the proposed approach are the development of an innovative epigenetics‐based multi‐objective optimizer, uncertainty incorporation in the search space data and decision making on a multi‐dimensional space through a VR‐simulation‐based visual steering process controlled at its core by a multi‐criterion decision making‐based process. This approach has widespread applicability to many other ‘wicked’ societal problem‐solving tasks. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献