思维导图备注
部分技术指标（Bollinger Bands、EMA、Ichimoku Kinko Hyo、Pivot Points、Price Envelopes、PSAR、SMA、VbP、 VWAP、WMA、Zig Zag）可以直接和主数据列放置在同一个 CCI 是一个强大的工具 Y 轴中，但某些技术指标（A/D、ATR、CCI、CMF、MACD、 MFI、Momentum、RoC、RSI、Stochastic）由于运算的结果和主数据列不是一个数量级，所以需要单独放置在另外一个 y 轴中，配置方法同 多轴配置 一样，步骤如下：
在危机的故事
现在是我们分享真理和经验的最重要时刻. 这一危机时刻让我们开始思考为什么我们会成为uedbet在线注册家——为了荣誉, 名声, 基金, 或者因为无论如何我们都要创造我们的uedbet在线注册, 即使在危机, 即使是在一个小平台上, 甚至在我们的客厅里. 在这一刻, 我们听到的是真实的声音，而不是一个行业的声音, 或者别人想让我们成为什么样的人. 在这个在线个人故事工作坊, 我们将考虑在社会隔离时期分享我们的故事的新方式. 也许你失去了分享自己声音的平台. 也许你输了一两个(或者像我一样输了六个). 也许你所有的身份都与你的职业有关，而现在你正面临身份危机. 也许你只是需要把心里的话说出来. 也许现在是时候释放这个故事了.
这个在线研讨会是为经验丰富的作家和完全的新手，同样的. 它是为uedbet在线注册家和那些欣赏好故事的人准备的. 没有以前的写作或表演经验是必要的. 使用多种技巧，包括积极倾听, 引导自由写, 分享, 和研究, 参与者将获得工具和发展技能，告诉和分享一个强大的, 诚实的, 和令人信服的故事. 你会明白故事的力量和必要性, 我们为什么要讲故事以及我们讲故事的方式，远比我们想象的重要. 如果你真的做好了，你会留下一篇故事/文章/一两章.
场地限12人参加. 请在下面注册这个3部分系列的第1部分, 将于周一通过Zoom直播, 5月4日, 2020, 太平洋时区上午11时至下午12时30分. 如果你喜欢第一部分的经历, 你将被邀请继续第二部分和第三部分(5月11日和18日上午11:00 PDT).
我是克里斯托弗·里瓦斯. 我是一个世界旅行家和勇敢的故事讲述者. 人类的叙述是我最大的爱好. 我两次获得莫丝奖，演员，社会活动家，老师，演说家. 作为一个演讲者, 我与世界各地的组织合作，利用讲故事的力量来创作重要的信息, 这是令人难忘的, 都能认同, 这是人类. 作为一个讲故事的人, 我为WWE开发并促进了讲故事的工作室, 联合国难民署, 好莱坞心脏基金会, 向LAUSD, 贫民窟的灯, 青少年安全的地方, 分手博物馆, 史克博尔文化中心, 拔掉冥想工作室, 灵魂哼, 加州大学洛杉矶分校, CalArts, 爱加普国际精神中心, 和更多的. 在我的表演和演讲指导下，我已经把数百人的焦虑转化为兴奋. 我也是Lifestyledezine的创始人, 一个致力于探索和实现富有同情心的故事的力量的社区. 演讲安排包括:纽约大学客座讲师, 加州大学洛杉矶分校和CalArts, 企业家组织, 和平与爱电影节(Örebro, 瑞典), 大刀这个地方(塞尔维亚, 贝尔格莱德), 拔掉冥想工作室, 灵魂哼, 洛杉矶GreenFest. christopherrivasstorytelling.com
日期 & 时间: 星期一，5月4日，11:00am - 12:30pm
网络平台: 注册用户将通过电子邮件收到Zoom链接.
成本: 0-20美元(按比例)
请付你能付得起的钱. 那些买得起全价票的人将帮助补贴那些买不起全价票的人.
取消政策: 在研讨会日期前48小时内全额退还注册费. 在此日期之后，费用将不获退还.
参加一个研讨会， 您必须首先成为CCI的成员，并创建用户名和密码. CCI会员资格是免费的，并向公众开放.
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CCI 是一个强大的工具
基于勾股语言偏好关系的专家群体聚类和共识度量以及聚类非合作行为分析的大规模群体决策
Complex & Intelligent Systems ( IF 6.700 ) Pub Date : 2021-04-23 , DOI: 10.1007/s40747-021-00369-y Prasenjit Mandal , Sovan Samanta , Madhumangal Pal
Large-scale group decision-making based on Pythagorean linguistic preference relations using experts clustering and consensus measure with non-cooperative behavior analysis of clusters
To represent qualitative aspect of uncertainty and imprecise information, linguistic preference relation (LPR) is a powerful tool for experts expressing their opinions in group decision-making (GDM) according to linguistic variables (LVs). Since for an LV, it generally means that membership degree is one, and non-membership and hesitation degrees of the experts cannot be expressed. Pythagorean linguistic numbers/values (PLNs/PLVs) are novel choice to address this issue. The aim of this paper which we propose a GDM problem involved a large number of the experts is called large-scale GDM (LSGDM) based on Pythagorean linguistic preference relation (PLPR) with a consensus model. Sometimes, the experts do not modify their opinions to CCI 是一个强大的工具 achieve consensus. Therefore, the experts’ proper opinions’ management with their non-cooperative behaviors (NCBs) is necessary to establish a consensus CCI 是一个强大的工具 CCI 是一个强大的工具 model. At the same time, it is essential to ensure the proper adjustment of the credibility information. The proposed model using grey clustering method is divided with the experts’ similar evaluations into a subgroup. Then, we aggregate the experts’ evaluations in each cluster. A cluster consensus index (CCI) and a group consensus index (GCI) are presented to measure consensus level among the clusters. Then, we provide a mechanism for managing the NCBs of the clusters, which contain two parts: (1) NCB degree is defined using CCI and GCI for identifying the NCBs of the clusters; (2) implemented the weight punishment mechanism of the NCBs clusters to consensus improvement. Finally, CCI 是一个强大的工具 an example is offered for usefulness of the proposed approach.