volvo tw的問題,透過圖書和論文來找解法和答案更準確安心。 我們找到下列包括價格和評價等資訊懶人包

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國立臺北商業大學 資訊與決策科學研究所 楊東育、李興漢所指導 柯廷叡的 應用深度學習方法探討企業流程異常檢測之研究 (2021),提出volvo tw關鍵因素是什麼,來自於流程稽核、異常檢測、深度學習、遞迴神經網路、長短期記憶神經網路。

而第二篇論文南臺科技大學 商管學院全球經營管理碩士班 周德光所指導 杜永仁的 Environmental, Social, and Corporate Governance (ESG) – Demand Analysis of Retail Investors in Taiwan and Germany (2021),提出因為有 ESG的重點而找出了 volvo tw的解答。

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應用深度學習方法探討企業流程異常檢測之研究

為了解決volvo tw的問題,作者柯廷叡 這樣論述:

企業流程是營運核心價值,對企業而言,管理、制度、工作流程、開發等都有相對應的流程表現。流程會留下執行軌跡,也就是所謂工作日誌,傳統日誌分析仰賴逐步定點式檢測,除工作量大外,也只對固定內容報錯進行改進,許多未報錯的錯誤於流程系統中未被注意。本研究將採用深度神經網路(Deep Neural Network)中的遞迴神經網路(Recurrent Neural Networks ,RNN)、適合時間序列資料的長短期記憶(Long Short-Term Memory, LSTM)方式進行建模,建置的模型會根據日誌內容預測接下來會發生的事情,由於本身文字並不能直接拿來訓練,於是在資料前處理的過程中,將使

用Label Encoding的方式將日誌文本轉換為鍵值,而建構的模型可以透過測試時的loss值異常升高來尋找可能異常的流程內容,也可以透過Decode後的實際日誌鍵與真實日誌鍵進行比對,藉此分析是流程異常或是判斷錯誤,作為改善流程的參考依據,模型中以該模型以LSTM模型有較佳的表現。另以VOLVO公司提供於9th International Workshop on Business Process Intelligence 2013的服務流程資料集進行分析,藉此做為驗證,其流程預測最終結果準確率71.57%,也意味可降低傳統逐筆檢查日誌的數量至28.43%,另延伸使用Kaggle上的系統流程

資料集來延伸測試該模型可應用於不同型態資料,並有一定效果預測及檢測異常。

Environmental, Social, and Corporate Governance (ESG) – Demand Analysis of Retail Investors in Taiwan and Germany

為了解決volvo tw的問題,作者杜永仁 這樣論述:

There is a recent financial market transformation with an observable shift of awareness towards environmental, social, and corporate governance (ESG). Investors increasingly demand that their money is saved with less risk of externalities.Various rating agencies with proprietary frameworks emerged,

leading to conflicting corporate sustainability information. Two companies were analyzed to showcase rating divergence: Taiwan Semiconductor Manufacturing Company (TSMC) and Volkswagen (VW). Both had above-average ESG performance with headroom for improvements in transparency and environmental aspe

cts.This thesis contributes to the academic literature by exploring the status of ESG awareness through a survey of 547 individuals in Germany and Taiwan. Predictors of knowledge and interest in ESG were tested, including investment experience, time frame, income, age, education, and information beh

avior.A partial least squares structural equation model (PLS-SEM) was created to visualize correlations, measure path weights, and test reliability & validity; this enabled a data-driven exploration of this novel research field.Most respondents had little or no knowledge of ESG and did not know the

rating of their investments. However, 72% claimed to have moderate to high levels of interest. Top exclusion categories included weapons, pornography, and animal testing.More than half of respondents expected companies with ESG agenda to be more profitable than benchmarks in the long run.Environment

al aspects ranked as the most demanded corporate improvements with a share of 62%. Social engagement came second, governance third, and more profit was last with only 2.7% of votes. Companies’ responses had opposed priorities in literature.More retail investors admitted to following recommendations,

ratings, and financial advice instead of researching information themselves.