應用智慧型基因演算法(IGA)於造血幹細胞(HSCs)與粗糙度的建模與預測

Intelligent Genetic Algorithm (IGA) for modeling and prediction of hematopoietic stem cells (HSCs) and roughness

黃忠雄(Chung-Hsiung Huang)

指導教授 ： 何信璋

國立虎尾科技大學/工程學院/機械與機電工程研究所/碩士(2009年)

摘要

近年來基因演算法已經廣泛應用於工程等方面，包含自動控制、系統優化設計等。本文智慧型基因演算法(IGA)配合模糊神經網路(FNN)是用來預測工件端銑加工的表面粗糙度以及造血幹細胞生成。IGA是GA配合直交實驗設計的智慧型演算法，可有效推理出近似最佳解。
由於在製造業對於表面粗糙度相當重視，它是用來評估工件端銑加工的品質準則。例如在表面密封、滾珠軸承、凸輪、齒輪或軸頸等應用方面，表面粗糙度對於設備的性能影響很大。而巨核細胞(Mks)是一種極為罕見且非常重要的人體骨髓細胞，必須經過很複雜的演進過程才能生成造血幹細胞。
本文於粗糙度建模引用前人文獻中的48組訓練數據、24組驗證數據，使用FNN架構建模，總共有126個模型參數。由實驗結果得知，以FNN的架構配合IGA來搜尋最好的FNN模型參數，能夠準確的預測出誤差較小的表面粗糙度，並且優於前人的文獻及MATLAB的ANFIS 方法所預測出來的結果。
而對於造血幹細胞的生成預測，我們依舊採用FNN架構配合IGA的方法來建模與預測。以FNN的架構配合IGA來搜尋最好的FNN模型參數，能夠準確的預測出誤差較小的造血幹細胞，並且優於前人的文獻及MATLAB的ANFIS 方法所預測出來的結果。

關鍵字

造血幹細胞(HSCs) ； 粗糙度 ； 智慧型基因演算法(IGA) ； 建模 ； 預測

並列摘要

Genetic algorithm used in engineering widely, including automatic control, system optimization design in recent years. Intelligent Genetic Algorithm(IGA) with Fuzzy Neural Network(FNN) is used to model and predict the workpiece surface roughness for the end milling process. IGA is powerful by using the Orthogonal Experimental Design’s algorithm. It can effectively reason to near-optimal solutions.
Surface roughness is very important in the manufacturing industry. It is used to assess the workpiece in the end milling process of performance criterion. For example：surface seals, ball bearing, cam, gear and journal. Surface roughness has very great impact for the equipment. Megakaryocytes (Mks) are an considerably rare cell population that are very important in myeloid cells, and produced by Hematopoietic stem cells(HSCs) through complex development processes.
In this paper, the model of the FNN uses previously researcher’s 48 training data and 24 validation data. There are 126 parameters to be optimized. Experimental results show that IGA with FNN model can improve the accuracy for modeling and prediction of surface roughness, and outperforms the ANFIS methods by MATLAB and reported recently in the literature.
In this paper, IGA with FNN is used to model and predict the HSCs production. Experimental results show that IGA with FNN model can improve the accuracy for modeling and prediction of HSCs, and outperforms the ANFIS methods by MATLAB and reported recently in the literature.

並列關鍵字

Hematopoietic stem cells(HSCs) ； Roughness ； Intelligent Genetic Algorithm (IGA) ； Modeling ； Prediction

參考文獻

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