仿真结果表明，所设计的模糊神经网络控制器能有效地减少单交叉口平均车辆延误，具有较强的学习和泛化能力。
Results of simulation show that the fuzzy neural controller can not only decrease the average vehicle delay but also possesses excellent abilities of learning and generalization.
目的针对铝电解故障发生机理及特点，提出采用层次模块化模糊神经网络实现对铝电解故障快速、有效检测的新方法。
This paper proposes a new method, which is a layer construction of Modular Fuzzy Neural Network according to the mechanism and characteristic of Aluminum Electrolysis Fault Diagnosis.
与多元线性回归、模糊回归和自适应模糊神经网络相比，该模型学习精度高且具有较好的泛化能力，能取得较好的预测效果。
Comparing with the models based on multiple statistic analysis, generalized regress-ion neural network or adapted fuzzy neural network model, it shows better learning precision and generalization.
结果符合试验要求，成功地实现了利用模糊优选BP神经网络进行智能化选煤。
Result is recorded with requirement of testing. And coal intelligently processing realize successfully through utilizing BP neural network theory of fuzzy optimization.
该系统依靠模糊控制理论提高了灵敏度，减少了误报率，并结合神经网络具有自学习功能的特点，提高了整个系统的智能化程度。
The system would reduce the malfunction rate with high sensitivity. Also the neural network has function of self-learning, which would raise the degree of intelligence of the system.
讨论了利用模糊神经网络技术与虚拟仪器技术相结合实现仪器智能化的原理、意义和方案。
The principle, significance and implementation of instrument intelligence are discussed, which combines the Virtual Instrument (VI) and the Fuzzy Neural Network (FNN) technology.
应用一种变结构神经网络算法对初始化的模糊规则进行调整，提高模糊控制规则的自学习和自适应能力。
A kind of variable structure neural network algorithm is adopted to adjust fuzzy rules, and improves the ability of self-studying and self-adjusting in fuzzy control rules.
选取的隶属函数使神经网络权值有一定的知识表示意义，并通过模糊化层将输入特征量转化为模糊量。
The selected membership function made neural network weight values have definite knowledge meaning, and the input characteristic variables were translated into fuzzy variables by fuzzy layer.
本文在综合评价体系结构基础上，应用模糊神经网络技术，建立了湖泊富营养化程度模糊神经网络评价系统。
Based on overall evaluation system and fuzzy neural network technology, fuzzy neural network evaluation system of eutrophication of lakes was established.
由于模糊神经网络具有很强的自学习、泛化和模糊逻辑推理功能，它可以有效地映射出钻芯、回弹数据间复杂的非线性关系。
FNN efficiently maps the complex non-linear relationship between data by drill and rebound methods for its automatic learning, generation and fuzzy logic inference.
提出一种基于模糊-神经网络的多探测器信息模糊化智能型火灾报警监测系统的新方案。
A new design of intelligent fire alert detecting system on multi detector signal fuzzification technic is presented in this paper.
把模糊理论与神经网络理论相结合，构造了一个正规化模糊神经网络NFNN，并应用于无人小车自动轨迹跟踪的控制。
Normal fuzzy neural network (NFNN) was constructed by integrating fuzzy theory and neural network technology in this paper. It has been used in unmanned driving car along a predefined track.
把模糊理论与神经网络理论相结合，构造了一个正规化模糊神经网络NFNN，并应用于无人小车自动轨迹跟踪的控制。
Normal fuzzy neural network (NFNN) was constructed by integrating fuzzy theory and neural network technology in this paper. It has been used in unmanned driving car along a predefined track.
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