• Fuzzy logic algorithm is realized by basic PLC instructions.

    模糊逻辑算法由基本的PLC指令来实现。

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  • In the adaptive algorithm, the parameter adjusting laws of the fuzzy logic systems are derived by the tracking error and the identification error.

    自适应算法中,不但跟踪误差而且辨识误差都参与模糊逻辑系统中的参数调节。

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  • The fuzzy logic and artificial neural network technologies are introduced into the algorithm for airbag deployment control, with a view to the appropriate and correct deployment of the airbag.

    为解决汽车安全气囊适时、正确触发问题,将模糊逻辑与人工神经网络技术引入汽车安全气囊触发控制算法研究。

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  • In this paper, the characteristics and advantages of neuro fuzzy intelligent control algorithm, which is an intersection of neural networks and fuzzy logic, are studied.

    研究了将神经网络与模糊逻辑融合交叉而形成的神经网络-模糊智能控制算法的特点和优越性。

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  • A peer to peer fuzzy power control algorithm of wireless sensor nodes is proposed by means of adding fuzzy logic controller to close loop power control technology.

    本文将模糊逻辑控制器加入到闭环功率控制技术中,并由此提出一种无线传感器网络中点对点的模糊功率控制算法。

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  • Based on analysis of the current congesting algorithm, a new congesting control mechanism is proposed, which employs SELA (stochastic estimator learning algorithm) and fuzzy logic controller.

    在分析了目前的拥塞控制算法的基础上,将随机估计学习算法(SELA)和模糊逻辑的知识引入拥塞控制,提出了新的拥塞控制模型。

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  • The simulation result is that the Fuzzy forward neural networks which is trained by this algorithm have good non-logic generalization and feature extraction ability, as well as fast learning speed.

    模拟结果表明利用该算法训练的模糊层次神经网络具有较好的非逻辑归纳能力和特征抽取能力,并且学习速度也大大加快。

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  • By using the control strategies of fuzzy logic and neural networks, a new control algorithm was designed to solve the control problems.

    采用模糊逻辑和神经元网络控制策略,设计了新的控制算法来解决阀控马达控制问题。

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  • Fuzzy logic expert algorithm can control the speed of the left and right track of the mining vehicle. Simulation result shows the feasibility and effectiveness of this project.

    采用模糊控制算法,对采矿车的左、右履带速度进行控制。仿真结果验证了该方案的可行性和有效性。

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  • A new neural network algorithm with fuzzy logic compensation was proposed and applied to an aero-engine rotating speed control system.

    提出了一种带模糊补偿的神经网络辨识器,并应用在某型涡扇发动机转速控制系统中。

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  • The neural network-based adaptive control and fuzzy logic are integrated based on feedback learning algorithm.

    在反馈学习算法的基础上,将模糊逻辑和神经网络自适应控制的结构结合在一起。

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  • This paper introduced firstly the basic knowledge of fuzzy logic and neural network, then the network structure and algorithm of the standard T-S fuzzy neural network were presented.

    本文首先介绍了模糊逻辑和神经网络的基本知识,并由此给出了标准的T - S模糊神经网络的网络结构及算法。

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  • This paper analyses mechanisms needed for a negative selection algorithm in an artificial immune system and defines fuzzy similarity using fuzzy logic.

    利用模糊思想,在定义了模糊相似度与背离度的基础上,提出了一种生成最有效检测器集的变阈值免疫阴性选择算法。

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  • Because of the limitation of end-to-end multicast congestion control, a Fuzzy Logic-based and Router-Assisted multicast congestion control (FLRA-MCC) algorithm is proposed in this paper.

    针对端到端组播拥塞控制的局限性,提出一种基于模糊逻辑和路由器辅助的组播拥塞控制算法flra - MCC。

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  • Using the monotonicity of a fuzzy logic controller, this paper puts forward a weighted average algorithm.

    本文利用模糊控制器的单调性,提出了一种加权平均算法。

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  • A fuzzy logic reasoning method is used to forecast traffic diversion volume and a fuzzy control algorithm is also applied to design the intersection signal setting of the route.

    在实现方法上,应用模糊推理技术对分流交通量进行了预测,并设计了路线交叉口信号灯配时方案调整的模糊控制算法,模拟结果验证了模糊逻辑推理技术的有效性。

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  • The control scheme adopts fuzzy logic based set-point weighing algorithm to enhance its robustness. The proposed algorithm has the advantages of less computation and easy engineering application.

    该方法能有效地提高系统的目标跟随特性、抗干扰性和鲁棒性,并且具有计算量小、工程容易实现的特点。

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  • This paper proposes a kind of fuzzy neural network control system based on learning algorithm and multi-valued function which derives from the fusion of the fuzzy logic and neural net…

    本文进行了模糊神经网络控制器的应用研究,经过仿真实验证明该控制器能够获得较理想的控制效果。

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  • This paper proposes a kind of fuzzy neural network control system based on learning algorithm and multi-valued function which derives from the fusion of the fuzzy logic and neural net…

    本文进行了模糊神经网络控制器的应用研究,经过仿真实验证明该控制器能够获得较理想的控制效果。

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