本研究意圖建立一個可以解釋及預測現象的模型（Model），既而嘗試使用飛行模擬機，利用類神經網路理論，建立一套可以進行評估飛航訓練成效的模擬平台。
本研究首先定義包含位置變化量等四個參數P1～P4及角度變化量等五個參數D1~D5。在給定同樣操作課目之下，以學員操作落地階段之模擬機綜合飛行數據，配合學員實際操作飛機教官給予之綜合成績，再針對目視航線三邊、四邊及五邊到著陸階段，以37位操作者為實驗，各選取七個模擬機數據，透過資深教官訪談，定義教官評量學員實際操作成效之參數，透過類神經網路的學習，建立模擬機定義參數與學員完訓綜合成績的因果關係，如此即可建立一套可以客觀評估飛航訓練成效的研究模擬平台。
本模式可以跨越認知的限制，跳脫以往以心理學及純理論的觀點，並以量化的方式，提供執行飛行訓練的教官與單位，具代表性且客觀的訓練成效數值，此法屬極具代表性的嘗試。

This study intended to establish a set of flight training simulation platform, using the flight simulator create a model to explain and predict phenomena according to the theory of neural networks.
First, this study contains the location of the change in the definition of the four parameters P1 ~ P4 and the angle variation of five parameters D1 ~ D5. In the subjects given, learners operate an integrated simulator landing stage of flight data to meet the aircraft and instructors to give students hands-on consolidated results. And then for the visual route trilateral, quadrilateral, and five edge-to-landing phases, with 37 operators’ experiments through interviews with senior instructors, the instructors selected seven simulator modules to assess and define the effectiveness of the actual operation of the parameters. Through the way of neural network learning , the establishment of the definition of parameters of simulator training with the students finished the cause and effect comprehensive results relationship, so this research create a set of objective assessment of the effectiveness of flight training simulation platform.
The patterns are across cognitive limitations and beyond the past, psychology and purely theoretical point of view. Quantitative approach provide objective training method with the implementation of flight training instructor, it is a representative and effectiveness way to flight training.

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