查詢結果分析
來源資料
相關文獻
- Artificial Neural Network for Business Manpower Requirement Forecast
- Application of Back-Propagation Neural Network for Predicting the Manpower Demands of Labor Market in Taiwan
- 人力訓補專案管理之研究
- 手寫數字辨識模式之建立--結合遺傳演算法與類神經網路
- Form Segmentation and Component Classification for Clinic Document Image Analysis
- 倒傳遞類神經網路在波浪時序列預報之應用
- 達成中央空調舒適度與省能控制之研究
- 應用於洪水演算類神經倒傳遞網路法最適參數推估
- 類神經網路應用於房地產估價之研究
- 人力資源發展與人力規劃
頁籤選單縮合
題名 | Artificial Neural Network for Business Manpower Requirement Forecast=以類神經網路預測企業人力需求預測 |
---|---|
作者姓名(中文) | 蔡智勇; 薛義誠; | 書刊名 | 德明學報 |
卷期 | 21 2003.06[民92.06] |
頁次 | 頁1-11 |
分類號 | 494.3 |
關鍵詞 | 人力規劃; 人力需求預測; 倒傳遞類神經網路; Manpower planning; Manpower requirement forecast; Back-Propagation neural network; |
語文 | 英文(English) |
中文摘要 | 根據相關文獻顯示,類神經網路可以使用在預測功能上。因為,類神經網路本身具有分析模組優點,所以它可以調整模組複雜度去配合複雜的人力資源歷史記錄,因此,只要將人力資源歷史記錄輸入,類神經網路模組就可以自動產生內部人力資源預測模組以及人力資源分類模組,而且不需要任何假設前題,所以,它比一般的預測分析模組更加正確。 本研究將以企業的財務報表作為人力需求預測的參數變數,經由倒傳遞類神經網路建立人力需求預測模式。在測試範例中,本研究發現預測準確率均在可接受範圍,再進一步與其他人力需求預測方法相互比較,發現倒傳遞類神經網路比其他方法的準確率較高,因此作為企業人力需求預測,將會是一項好的方法。 |
英文摘要 | According to relative research show using neural networks to prediction. Because neural network models have an advantage over analysis models, so it adjusts model complexity to match the complexity of the manpower resources history. Therefore, using manpower resources history as input, no assumption, the neural network model automatically develops its own internal model of the manpower resources of predict and classify. So it can be more accurate than some commonly used analytic models. The purpose of this research, using financial statements of a business as the parametric variable in forecasting its need for manpower, is to establish models for forecasting the need for manpower through back propagation neural network. In experimenting with testing examples, this research found that the accuracy of prediction falls within the acceptable range. It further compared back propagation neural network with other forecasting methods and found that it is better than others in terms of accuracy. Therefore, back propagation neural network, if applied to predicting the need for manpower, will be a contribution to practical application. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。