원문정보
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초록
영어
The paper demonstrates the forecasting of an aircraft trajectory in the vertical plane using gradient descent method for training a feed forward neural network system. For prediction of trajectory a neural networks system has been trained using a set of some arbitrary trajectories and then used to forecast for the new ones. Sliding Window method is being used for predictions, which is able to consider real points during flight to improve the precision in prediction. The results show that neural network can successfully be applied for such predictions
목차
Abstract
1. Introduction
2. Gradient Descent Learning Algorithm of Feed Forward Neural Networks
I. Initialize Weights and Offsets
II. Present Input and Desired Output Vector
III. Calculate Actual Outputs
IV. Adapt weights
V. Repeat by Going to Step 2
3. Prediction of Aircraft Trajectory using Feed Forward neural networks
4. Conclusion
References
1. Introduction
2. Gradient Descent Learning Algorithm of Feed Forward Neural Networks
I. Initialize Weights and Offsets
II. Present Input and Desired Output Vector
III. Calculate Actual Outputs
IV. Adapt weights
V. Repeat by Going to Step 2
3. Prediction of Aircraft Trajectory using Feed Forward neural networks
4. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보