神经网络的训练采用一阶梯度优化算法，利用点堆中子动力学模型产生训练样本。
The first order gradient optimization algorithm is employed to train the network. The training samples stem from the neutron kinetics of the point-reactor.
利用防抱制动系统（ABS）液压实验台，进行了ABS压力梯度多种工况的实验测试，包括普通制动、长加长减制动和阶梯增压、减压制动等工况研究。
The pressure gradient of the anti-lock braking system (ABS) was experimentally studied using an ABS hydraulic test bench for various conditions including normal brake, on-off brake, and step brake.
预测了台阶梯度洗脱条件下待分离物质的保留体积。
The retention volume of targeted compounds was predicted in the step gradient elution conditions.
应用推荐