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1·RailsBench helps create artificial load against a target Rails application.

RailsBench是帮助针对目标Rails应用创建一个非实际环境下的加载。

2·The objective function was described by artificial spring model and dummy load method and the sensitivity was analyzed by the adjoint sensitivity analysis method.

通过人工弹簧模型和虚拟载荷法描述柔性机构设计的目标函数，采用伴随敏度分析法进行了敏度分析。

3·In this paper, the application of artificial neural network (ANN) for short - term load forecasting and mid - long - term load forecasting are analyzed and compared.

本文分别对人工神经网络(ANN)在短期负荷预测和中长期负荷预测中的应用进行了分析、对比。

4·The paper based on increased the low-constant temperature test box on the electronic universal testing machines, has finished the uniaxial load strength test of artificial freshwater ice.

通过对电子万能试验机增加低温恒温试验箱，实现了人工淡水冰的单轴加载强度试验。

5·The paper presents a method of changing topological artificial neural network (ANN) to forecast the load of power system.

提出变拓扑人工神经网络（ANN）预报电力系统负荷的方法。

6·Based on experiment data, a model for the relationship between the rolling load of an open mill and its affected factors was built with artificial neural networks.

在实验数据的基础上，利用人工神经网络建立开炼机横压力与其影响因素之间对应关系的数学模型。

7·Shaking table experiment not only has great load factor, but also can simulate crude seismic wave and artificial wave to load tested object.

地震模拟振动台试验不仅负载量大，而且能模拟天然地震波和人工地震波对试件加载。

8·Based on the artificial neural networks, a inverse analysis method is presented to identify both the magnitude and location of the load on bridge structure.

提出了一种智能桥梁结构的智能计算方案，并利用人工神经网络法，建立一种识别作用在桥梁结构上荷载的力学反分析法，以此初步实现该方案。

9·There are many load forecasting methods based on artificial intelligence and also based on statistical methods.

电力系统负荷预测的方法有很多，有基于人工智能方法，也有基于统计学方法的。

10·In this paper we propose a method for short-term load forecasting using artificial neural network.

本文提出了一种应用人工神经网络进行电力系统短期负荷预测的方法。