This article introduces a predictive model of Artificial Neural network of red tide biology density and environment factors by use of the back propagation (BP) network.
本文利用人工神经网络中的BP网络，建立赤潮生物密度与环境因子的人工神经网络的预报模型。
To enhance the validity of evaluation, based on ANN(artificial neural network), a comprehensive evaluation model of the safety of road traffic based on BP(back propagation) neural network was built.
为了提高评价的准确性，采用人工神经网络技术，建立了基于BP神经网络的道路交通安全综合评价模型。
Combined Genetic Algorithms (ga) and back-propagation neural network (BP), an optimized GA-BP model was established to predict phosphorus content. Some data were chosen to train the network model.
结合遗传算法(GA)和误差反馈型神经网络(BP)，建立了优化的GA - BP神经网络预测模型，预测转炉炼钢过程钢液终点磷含量。
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