There is a complex relation of nonlinear function between the actual wind velocity and the output 's signals by the thermoelectric anemometers sensor.
热电式风速传感器感应输出的电信号与实际风速之间存在复杂的非线性函数关系。
Traditional optimizations have disadvantages such as local convergence, when they are used to solve function synthesis of planar 4-bar linkage, which is a complex nonlinear constraint problem.
传统优化算法对于解决平面四杆机构函数综合等复杂非线性约束优化问题存在局部收敛等不足。
In this paper, radial basis function neural network was employed to approximate the nonlinear complex relationship of all factors.
本文使用径向基神经网络确定各个因素之间的非线性复杂关系。
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