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A nerve net controller have been designed on the basis of the hardware design of the AC servo system and system model. The controller include two forward nerve net with three layers . One is designed to identify the AC servo system model and another is to control. The controller use special learning algorithm which to control system at the same time and improve its constringency pace through introducing new MFBP algorithm. The intelligent control algorithmic is programmed using C++ language after the controller have been designed .

在该交流伺服系统硬件设计和系统数学建模的基础上,设计了神经网络自适应控制器,这个控制器包括两个三层的前馈神经网络,一个神经网络用于非线性系统的辨识,另一个神经网络作为控制器,此控制器采取边学习边控制的工作方式,并采用一种新型的MFBP算法实现了控制算法的快速性,在控制器设计完成的基础上,利用C++语言具体实现智能控制算法的编写。

By the same method, delta receptor was detected on the cerebral ganglia, pedal ganglia, visceral ganglia, coat ganglia and in the mouth, esophagus, craw, stomach, stomachic caecus, the epithelium of the intestines, sialoid gland, branchia, branchia gland, ventricle, branchial heart, kidneys, ovary, fallopian tube, back of mantle, abdomen of mantle, wrist, membrane of wrist, funnel and immunocytes of Octopus ocellatus.

2在短蛸的脑神经节、足神经节、脏神经节、外套神经节、口球、食道、嗉囊、胃、胃盲囊、肠、后唾液腺、鳃、鳃腺、心室、鳃心、肾静脉腺质附属物、卵巢、输卵管腺、外套膜背面、外套膜腹面、腕、腕间膜、漏斗中检测到呈不同阳性反应的δ受体。

A hybrid model of short-term load forecasting based on chaotic theory, correlation and neural networks is presented in this paper. Firstly, reconstruct attractors in phase spaces using chaotic theory, Secondly fit the attractor's evolvement using BP neural networks, because selecting neural network's input training data using Euclid distance and correlation, improve neural network's associative memory and ratiocinative ability, can better fit the attractor's evolvement.

提出一种将混沌理论、关联度和神经网络相结合的短期负荷预测模型,首先利用混沌理论重构负荷时间序列的相空间吸引子,然后用BP 神经网络来拟合空间吸引子的演化,由于使用空间欧氏距离和关联度联合来选取神经网络的训练样本,这样就提高了神经网络对负荷序列混沌特性的联想和泛化推理能力,能够更好的拟合吸引子的演化。

Firstly, reconstruct attractors in phase spaces using chaotic theory,Secondly fit the attractor s evolvement using BP neural networks, because selecting neural network s input training data using Euclid distance and correlation, improve neural network s associative memory and ratiocinative ability, can better fit the attractor s evolvement.

提出一种将混沌理论、关联度和神经网络相结合的短期负荷预测模型,首先利用混沌理论重构负荷时间序列的相空间吸引子,然后用BP神经网络来拟合空间吸引子的演化,由于使用空间欧氏距离和关联度联合来选取神经网络的训练样本,这样就提高了神经网络对负荷序列混沌特性的联想和泛化推理能力,能够更好的拟合吸引子的演化。

Nerve stem cell can be differentiation into astroblast, oligodendrocyte and nerve cell induced by factors.

神经干细胞的增殖分化可受各种因素的影响,目前已知,许多细胞因子,生长因子,营养因子以及细胞外环境等因素的作用,可诱导神经干细胞向不同的终末细胞分化,若能在体外分离培养神经干细胞并在促分化因子的作用下,诱导神经干细胞向某一特定方向分化,将为干细胞的分化机制提供有力的实验依据。

The design of transplanter for rice growing in cupulate tray is the critical link in rice growing in cupulate tray technology,the design method is not mature,for exploring a new design method,having discussed neural network s serviceability in agriculture machinery mechanism design with the theoretical basis of self-organizing feature mapand the back-propagation network,the integrated SOM-BP nerve network model is applied in the field of transplanter s critical mechanism design for rice growing,al...

水稻钵育栽植机的设计是实现水稻钵育栽培技术的关键环节,区别于传统的水稻栽植机其关键部件的设计方法还不成熟,在理论研究方面还不完善。为探索新的设计方法,论述了神经网络算法对农业机械设计的适用性,以自组织特征映射网络SOM 和误差反向传播网络BP为理论基础,将SOM-BP集成神经网络模型应用于水稻钵育栽植机关键部件设计领域,建立神经网络模型,通过集成网络训练,得到设计结果。验证了SOM-BP神经网络在农业机械机设计中的正确性和精确性。

It has been proved by previous studies that peripheral nerve injury can induce a series of changes of expression of some neural active material and their receptors either in the somata or in the terminals of the damaged primary afferent neurons and motoneurons. These changes may reflect a re-ordering of metabolic priorities so that the synthesis of trophic factors or growth-associated proteins augmented while that of neurotransmitter-related proteins decreased.

以往的研究表明,周围神经损伤能够引起受损神经元(包括初级传入神经元和运动神经元)的胞体或终末内某些神经活性物质及其受体的表达发生一系列变化,其中与神经生长和营养有关的物质常发生上调,而与神经传递有关的物质则发生下调;与此同时,受损神经元的周围常伴随发生胶质反应及神经胶质增生等变化。

Artificial neural network is a fast developing intercrossed subject. The theory of ANN make the transmitting of large information and complex calculation possible. ANN is not only a highly non-linear dynamics system but also a self-organization and self-improvement system. In the early 1980's, the appearance of ANN dramatically promote the primary research on understanding and intelligence of human-being as well as the computer industry.

人工神经网络是一门发展十分迅速的交叉学科,神经网络理论是巨量信息并行处理和大规模平行计算的基础,神经网络既是高度非线性动力学系统,又是自适应组织系统。80年代初,神经网络的掘起,已对认知和智力本质的基础研究乃至计算机产业都产生了空前的刺激和极大的推动作用。

Objective: Using neuropsychological tests to assess the cognitive functions of both major depression and dysthymia and analyse the relationship between the cognitive impairment and the alternation of peripheral blood concentration of hormones.

目的:采用目前国际上较为先进的神经心理检测工具对重性抑郁症、心境恶劣障碍及正常人群进行认知功能的评定,结合神经内分泌指标的监测,对比两种不同临床表现的抑郁障碍在神经心理学和神经内分泌指标方面的异同,为了解抑郁障碍的生物学发病机理提供依据。

The dissertation recommends some kinds of methods and measures: such as adjusting the network configuration, connecting value and threshold value by the total value of all stylebooks, adding part of the adjusting value of the last time to the current adjusting value, transforming the stylebooks to standard value, optimizing activation function, appending threshold value to the putout of the nerve cell and so on. Simultaneity, the author brings forward a new method to optimize the model of artificial neural network . It is using the automatically adaptive genetic algorithm to make the network configuration, connecting value and threshold value of artificial neural network better. The method can make the model better and improve the simulating effect and forecasting precision.Genetic algorithm is an arithmetic based on evolution and genetics used to search the optimization .

本文针对人工神经网络应用中存在的上述问题,介绍了各种改进方法与措施:如用所有样本的总效果对网络权值矩阵和阈值向量进行调整、调整量中加入动量项、标准化训练样本数据、优化激励函数以及给神经元的输出值添加偏置量等;同时还提出了一种新的优化人工神经网络模型的方法,即采用自适应遗传算法对人工神经网络模型的网络结构和权值阈值进行全局优化搜索,以提高大坝安全监测人工神经网络模型的拟合成果和预测精度。

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