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今天小編為您帶來精讀複刻論文《基于CWPHM算子和C-DEMATEL的語言型多屬性決策方法》之代碼複刻（18）。
歡迎您的通路！
Share interest, spread happiness,
increase knowledge, and leave beautiful.
Dear, this is the LearingYard Academy!
Today, the editor brings the "intensive reading replica paper 'A linguistic Multi-Attribute Decision-Making approach based on the CWPHM operator and C-DEMATEL' for code reproduction (18)".
Welcome to visit!
一、内容摘要（Content Summary）
本期推文将從思維導圖、精讀内容、知識補充三個方面介紹精讀複刻論文《基于CWPHM算子和C-DEMATEL的語言型多屬性決策方法》的代碼複刻（18）。
In this issue, we will introduce the code replication (18) of the refined reading paper "Language Type Multi-Attribute Decision-Making Method Based on CWPHM Operator and C-DEMATEL" from three aspects: mind map, refined reading content, and supplementary knowledge.
二、思維導圖（Mind Mapping）
三、精讀内容（Detailed Reading Content）
根據文中CWAA算子的參考文獻，可以得到CWAA算子的定義以及舉例過程，如下圖所示。CWAA算子是根據一定的方式對雲的期望、熵和超熵進行權重相加來得到聚合資訊的特征值。
Based on the references in the paper, the definition and example process of the CWAA operator can be obtained, as shown in the figure below. The CWAA operator is a weighted aggregation of expectations, entropy, and hyperentropy of clouds in a certain way to obtain characteristic values of aggregated information.
運用CWAA算子對各幹部資訊集結的代碼及運算結果如下圖所示。
The code and calculation results of using the CWAA operator for the information aggregation of each cadre are shown in the figure below.
四、知識補充——雲逆向發生器（Supplementary Knowledge — Cloud Reverse Generator）
若需要将定量概念變換為定性概念則可以利用逆向雲發生算法事項，即正向運算法的逆向過程，從給定的雲滴樣本中根據逆向雲生成算法得到3個數字特征值，進而實作對樣本資料的定性評價，如下圖所示。依此思路，根據樣本即可得到雲的點估計值。
If it is necessary to transform quantitative concepts into qualitative concepts, the reverse cloud generation algorithm can be used, which is the reverse process of the forward operation method. Three numerical characteristic values can be obtained from the given cloud droplet samples based on the reverse cloud generation algorithm, thus achieving qualitative evaluation of sample data, as shown in the figure below. Following this approach, the point estimate of the cloud can be obtained based on the sample.
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讓我們相約明天，
祝您今天過得開心快樂!
That's all for today's sharing.
If you have a unique idea about the article,
please leave us a message,
and let us meet tomorrow.
I wish you a nice day!
參考資料：ChatGPT、百度百科
參考文獻：
王偉明, 徐海燕, 朱建軍等. 基于CWPHM算子和C-DEMATEL的語言型多屬性決策方法 [J/OL]. 中國管理科學, 2023, 1(1): 1-13.
本文由LearningYard學苑整理并發出，如有侵權請在背景留言！
文案| Ann
排版| Ann
稽核| Wei