模糊神经网络在电容成象中的应用

Application of Neural Fuzzy Network in Capacitance Tomography

描述了基于电容层析成象，采用模糊逻辑和神经网络对静态火焰进行闭环控制过程．以神经元形式将专家知识和训练类型融合到模糊规则中．采用神经网络使得增加被控制参数数量较为容易并使得系统自动调整参数较为容易．

Describes a capacitance tomography based on closed loop control over stationary flames using fuzzy logic and neural networks. Experts'knowledge and training patterns can be incorporated into fuzzy rules with neurons.The use of neural network makes it easy to increase the number of control parameters and for the system to adjust its performance automatically.