| 1. | Finally the control result is improved by the output of fnnc . another neural network called pnn is introduced to finish constructing and renovating the knowledge database
本文主要对模糊神经网络自组织控制器在自动舵中的应用进行了研究，综合了模糊控制和神经网络的应用。 |
| 2. | The application of fuzzy neural network controller ( fnnc ) in automatic steer is mainly discussed in the paper , which integrates the way of fuzzy logical control and the use of neural network
而人脑思维的容错能力，正是源于这两个方面的综合?思维方法上的模糊性以及大脑本身的结构特点。 |
| 3. | The fuzzy deduction and anti - fuzzy in fuzzy systems are finished by fnnc . off - line training the fnnc let it study and remember the experiential knowledge . then the fnnc can simulate the people ' s control actions
模糊神经网络是一种集模糊逻辑推理的强大结构性知识表达能力与神经网络的强大自学习能力于一体的新技术，它是模糊逻辑推理与神经网络有机结合的产物。 |
| 4. | At the end of the paper , programming with vc + + and matlab did the simulation of fnnc . fnnc has a lot of advantages by the comparison of pid controller and adaptive controller . but the ai control is only a new thing . it is restricted by hardware in the real application obviously
最后通过用vc + +和matlab编程对模糊神经网络控制器在船舶操纵中的应用进行了计算机仿真，通过与pid和自适应的控制效果相比较，说明了模糊神经网络控制的优势所在。 |
| 5. | An indirect self - adaptive fuzzy - neural network controller ( fnnc ) has been proposed with its parameters and the structure tuned simultaneously by ga in virtue of the powerful optimization property of ga . the structure of the controller is based on the radical basis function ( rbf ) neural network with gaussian membership functions . the performance of the proposed fnnc is compared with a conventional fuzzy - pid controller and the simulation results show that the fnnc presents encouraging advantages
针对神经网络采用一维反向传播训练算法速度较慢且易于陷入局部极小点的不足，设计了一种间接自校正模糊神经网络控制系统，利用遗传算法( ca )对隶属度函数的结构和参数进行优化，仿真比较表明该控制比模糊pid控制具有更优的性能。 |
| 6. | Avoiding the use of mathematic models , the fuzzy logical control ( flc ) system meets the control demands of the tunnel ventilation process well which is a nonlinear distribution system . but because of its lacking of learning and adaptive ability , many problems has emerged when using flc : the membership functions of the fuzzy variables cannot be changed , the fuzzy logical rules cannot be modified automatically when environmental variables such as traffic model , average exhaust , etc , are changed . for this reason , the paper uses fuzzy neural network control ( fnnc ) system to improve the control process
模糊控制系统避开了数学模型，能很好适应公路隧道通风系统非线性和分布式参数特征，但是模糊控制系统本身的学习和适应能力差，导致了模糊变量各语言值隶属函数和控制规则不能随着环境参数(如交通量、基准排放量等)的改变而自动调整和修改等问题，本文将具有强大学习能力的神经网络融合到模糊控制系统中，研究和探讨了隧道通风模糊神经控制方法。 |
| 7. | The simulation result reveals the pollutant concentration fluctuates near the control goal as closely as possible . the fnnc system can modify the logical rules and regulate the parameters of membership functions automatically . compared with the flc system , the control process becomes more automatic , the time and the energy consumption becomes less
本文提出基于模糊神经网络模型的隧道通风控制方法，能自动修改规则库和调整隶属函数，与单纯的模糊控制方法相比，提高了控制系统的自动化程度，节省了调整时间，降低了电能消耗。 |
| 8. | In the procedure of control , pnn studies on - line and gives the signals to fnnc . one of the algorithms to train networks is genetic algorithm which is based on darwinism . to avoid converge ahead of schedule or enter into the super - plane , the ratio of intercross and aberrance is self - adaptive to enhance the efficiency
在神经网络离线训练时应用了基于达尔文进化论的遗传算法，为了解决一般遗传算法的早期收敛和陷入超平面等问题，采取对交叉和变异率自适应调整的方法来提高搜索效率。 |
