基于空间拟合和神经网络的机场噪声预测集成模型

将集成学习方法引入到机场噪声预测中,提出一种基于空间拟合和神经网络的机场噪声预测集成模型.该模型采用空间拟合算法和BP神经网络算法构建基学习器,然后通过所提出的基于观察学习的异构集成算法将基学习器集成起来,获得集成的机场噪声预测结果.该模型通过集成多个异构机场噪声预测基学习器,能够有效提升预测准确率.实验结果表明,本文所提出的基于观察学习的异构集成算法,较之其他异构集成算法,在解决机场噪声预测问题上准确性更高、容错性更强.

Airport noise prediction ensemble model based on space fitting and neural network.

This paper proposes an airport noise ensemble prediction model based on space fitting and neural network by introducing ensemble learning method. Space fitting and BP neural network is used respectively to create the base learner and a heterogeneous ensemble algorithm based on observational learning is used to integrate these base learners. The final ensemble model thus can improve prediction accuracy effectively by integrating multiple heterogeneous base prediction learners. The experimental results shows that the proposed heterogeneous ensemble algorithm based on observational learning is better than other heterogeneous ensemble algorithms on accuracy and tolerance for solving the airport noise prediction problem.