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Estimation of priority weights based on a resampling technique and a ranking method in analytic hierarchy process

机译：基于重采样技术的优先级权重和分析层次结构中的排序方法估算

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Abstract >Individual judgments are sought in order to elicit values of the entries of pairwise comparison matrices in analytic hierarchy process. Some of these matrices are more consistent than others. But throwing out inconsistent matrices reduces the number of matrices. In this article, we propose a resampling technique to generate sets of pairwise comparison matrices, which pass the consistency check. The advantage of the resampling technique is that one can generate as many sets of pairwise comparison matrices as needed to select the ones that satisfy the consistency requirement. Based on these selected matrices, the priority weights of the alternatives are then estimated. We propose rank‐based statistical procedures to check the significance in the difference between estimated priorities of the alternatives to establish their most significant rank order. </abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> <div class="translation abstracttxt"> <span class="zhankaihshouqi fivelineshidden" id="abstract"> <span>机译：</span><Abstract Type =“Main”XML：Lang =“EN”XML：ID =“MCDA1664-ABS-ABS-ABS-0001”> <标题类型=“main”>抽象</ title> >寻求个别判断，以便在分析层次过程中引出成对比较矩阵条目的值。这些矩阵中的一些比其他矩阵更加一致。但抛出不一致的矩阵减少了矩阵的数量。在本文中，我们提出了一种重采样技术来生成一组成对比较矩阵，它通过一致性检查。重采样技术的优点是，可以根据需要生成多组成对比较矩阵，以选择满足一致性要求的那些。基于这些所选矩阵，然后估计备选方案的优先级重量。我们提出基于等级的统计程序，以检查估计替代品的估计优先级之间的重要性，以建立其最重要的排名顺序。</ p> </摘要> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> </div> <div class="record"> <h2 class="all_title" id="enpatent33" >著录项</h2> <ul> <li> <span class="lefttit">来源</span> <div style="width: 86%;vertical-align: text-top;display: inline-block;"> <a href='/journal-foreign-35605/'>《Journal of Multi-Criteria Decision Analysis》</a> <b style="margin: 0 2px;">|</b><span>2020年第2期</span><b style="margin: 0 2px;">|</b><span>共4页</span> </div> </li> <li> <div class="author"> <span class="lefttit">作者</span> <p id="fAuthorthree" class="threelineshidden zhankaihshouqi"> </p> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zkzz" style="display: none;">展开▼</span> </div> </li> <li> <div style="display: flex;"> <span class="lefttit">作者单位</span> <div style="position: relative;margin-left: 3px;max-width: 639px;"> <div class="threelineshidden zhankaihshouqi" id="fOrgthree"> </div> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zhdw" style="display: none;">展开▼</span> </div> </div> </li> <li > <span class="lefttit">收录信息</span> <span style="width: 86%;vertical-align: text-top;display: inline-block;"></span> </li> <li> <span class="lefttit">原文格式</span> <span>PDF</span> </li> <li> <span class="lefttit">正文语种</span> <span>eng</span> </li> <li> <span class="lefttit">中图分类</span> <span><a href="https://www.zhangqiaokeyan.com/clc/44.html" title="心理学">心理学;</a></span> </li> <li class="antistop"> <span class="lefttit">关键词</span> <p style="width: 86%;vertical-align: text-top;"> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=bootstrap&option=203" rel="nofollow">bootstrap;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Kruskal‐Wallis statistic&option=203" rel="nofollow">Kruskal‐Wallis statistic;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=priority weights&option=203" rel="nofollow">priority weights;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=rank‐based hypothesis testing&option=203" rel="nofollow">rank‐based hypothesis testing;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=resampling method&option=203" rel="nofollow">resampling method;</a> </p> <div class="translation"> 机译：Bootstrap;Kruskal-Wallis统计;优先权;基于秩的假设测试;重采样方法; 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