anns
英
美
网络 人工神经网络; 安百慧; 神经网络; 神经外科协会; 类神经网路
双语例句
- Inspired from modular programming, we proposed a module based evolutionary programming of ANNs, which puts emphasis on inheriting from the learned networks of small scale problem.
提出一种新的模块化进化神经网络方法，用于大规模或复杂问题的神经网络设计。 - Application of Two ANNs to Fault Diagnosis of Gas Chromatograph in Transformer Oil
两种神经网络在变压器油色谱故障诊断中的应用 - The paper combines artificial neural networks ( ANNs) with Kalman filter real-time adjustment technique in order to improve traditional ANNs model.
为改进神经网络模型算法，将神经网络技术与卡尔曼滤波技术进行耦合。 - Recognition and forecasting are two of the basic functions of the ANNs.
识别和预测是人工神经网络的两大主要功能。 - The basic principle and method of4D geological modeling using Artificial Neural Network System ( ANNS) are discussed in the paper.
论述了用人工神经网络系统建立储层四维地质模型的原理和方法。 - The advantages and disadvantages were analyzed for ANNs and mathematical simulation. A foundation was kid on the establishment of cross over method.
并对神经元网络方法和数学模拟方法进行讨论，分析了两种方法的优缺点，分“互补法”的建立奠定了基础。 - The efficiency and advantage of the method is proved by the prediction results for the activity of herbicide based on the improved and traditional BP ANNs.
在人工神经网络用于除草剂化合物活性预测的研究中，和传统BP算法的对比试验显示，本文的改进BP网络具有更快的收敛速度和更高的精度。 - A method which applied Artificial Neural Nets ( ANNs) to evaluation synthetic economic efficiency of business firm is proposed here.
本文提出了应用人工神经经网络的ART模型进行企业综合经济效益评估的方法。 - A Fault Diagnostic Method of Circuit Board Based on Magnetic Field Image and ANNs
基于磁场映像和人工神经网络的电路板故障诊断 - This paper focuses on application of ANNS in the study of the karst basin and its low flow.
本文主要讨论人工神经网络在喀斯特流域及其枯水径流研究中的应用。 - In this paper, ANNs are applied to study of the bandgap characteristic of DGS.
本文针对神经网络在DGS滤波特性中的应用进行了研究。 - A data-analysis model system Based on BP ANNs ( Artificial Neural Networks) technology is developed. Three BP knowledge models, which reflect relations between emulsion quality parameters and raw materials parameters are given based on the system.
基于BP神经网络技术，设计开发了感光材料数据分析原型系统，利用该系统对GBR100彩色胶卷乳剂生产数据进行分析，得到了三个映射乳剂数据相关性的BP网络知识模型。 - Experimental data for heatiing and cooling modes were used with both the ANN and a traditional mathematical method to determine the time delay, The results show that ANNs can be used to effectively determine the time delay for HVAC systems.
对制热和制冷两种工作方式的实验数据，采用ANN和传统算法两种方法确定时间迟延，并进行比较。结果表明ANN可以有效地用于确定HVAC系统的时间迟延。 - Research About Color Film Emulsion Data Analysis Based on BP ANNs Model
BP神经网络模型在彩色胶卷乳剂数据分析中的应用 - The faster convergence speed and higher prediction precision of the improved algorithm compared with the traditional BP ANNs is proved by the results of simulation tests of nonlinear function and the prediction results of short-term load.
在非线性函数仿真和短期负荷预测的研究中，该算法和传统BP算法的对比试验显示，改进算法的收敛速度更快、预测精度更高。 - The greatest advantage of ANNs is that no prior knowledge of migration behavior and separation system is needed.
人工神经元网络具有很强的非线性校正能力，其最大优点是无须对分离体系及组分的迁移行为预先予以了解。 - Then the study algorithm is improved to enhance the identification result of the aerodynamic derivatives, and different BP ANNs are built to identify the static coefficients.
然后改进了学习算法以识别桥梁模型的气动导数，并采用了不同的BP网络识别桥梁模型的静力三分力系数。 - Through analyzing the limitations of CAD expert systems, this paper studies the theories and methods of applying artificial neural networks ( ANNs) in intelligent CAD.
通过分析目前CAD专家系统中存在的问题，对人工神经网络在智能CAD中应用的理论和方法进行了探讨。 - The results show that ANNs can be used effectively determining the delay time for AVAC systems.
结果表明ANN可以有效地用于确定HVAC系统的延迟时间。 - Support Vector Machine recognition model was also established. This paper proposes the fusion model of SVM and ANNs that have different mathematical characteristics.
本文还建立了基于支持向量机的识别模型，并将这两类具有不同数学特性的智能监测模型进行决策融合，实现对刀具磨损状态的精确识别。 - In practical applications, people carry out the function of the ANNs by using electronic. Time delays are inevitably encountered in neural networks because of the artificial factors, the finite switching speed of amplifiers and technical level, and so on.
在实际应用中，人们通过电子电路来实现神经网络的功能，由于受认知因素以及神经元放大器有限转化速度和技术水平等客观因素的影响，时滞现象不可避免的。 - Learning algorithm is the bottleneck in employing artificial neural networks ( ANNs). This dissertation analyzes the problems of learning rate adaptation in the learning algorithms of multi-layer feedforward ANNs and then proposes a scheme of adapting learning rate.
学习算法一直是人工神经网络应用中的一个瓶颈，本文分析了多层前馈神经网络学习算法在学习率自调整中存在的问题，提出了一种学习率的自适应方案。 - Artificial Neural Networks ( ANNs) are parallel computational systems comprised of densely interconnected neurons.
人工神经网络（ANNs）是一个由大量相互连接的神经元组成的并行计算系统。 - Cross-validations of FAN model and ANNs ( Artificial Neural Networks) were conducted on two different sample datasets.
在两个干扰性不同的样本集上，分别对FAN模型和人工神经网络模型进行交叉验证。 - This paper is based pedagogical method. Although there are several approaches proposed for classification rules extraction from ANNs, this present approach is fundamentally different from them.
虽然已经有了一些从神经网络中进行分类规则提取的文章，但本文与这些文章本质上有所不同。本文提出的是一种基于改良蚁群算法的神经网络分类规则提取方法。 - Two intelligent models with different mathematical characteristics ( ANNs and SVM) are applied separately to recognize tool wear states and the results are fused to make the final decision.
以两种具有不同数学特性的智能识别模型ANN和SVM，分别对刀具磨损状态进行识别，并将识别结果进行融合得出最终决策。 - Experimental results showed that the improved D-S evidence theory fusion model for SVM and ANNs successfully solved the tool wear recognition problem in the full life span of the cutting tool.
实验结果表明基于ANN和SVM的改进D-S证据论融合模型成功地解决了刀具全寿命周期内磨损状态的精确识别问题。 - In this paper, to take predicting the wheel-rail force as a goal, four predicting method based on ANNs are discussed.
本文以精确预测轮轨力为目的，主要讨论了基于多种人工神经网络的轮轨力预测方法，并提出一种适用大型NARX神经网络结构的训练算法。 - The FPGA-based hardware implementation method can not only improve processing speed, but also to save hardware resources. Firstly, introduced the methods and meaning of hardware implementation of ANNs, as well as the typical BP and RBF neural network algorithm.
基于FPGA的神经网络硬件实现方法不仅能够提高处理速度，而且还能够节省硬件资源。首先介绍了人工神经网络硬件实现的方法和意义，以及典型的BP神经网络算法和RBF神经网络算法。 - ANNs are now being used in signal processing, medicine, control system, business, pattern recognition, speech recognition and much more areas.
如今，人工神经网络已经在信号处理、医疗、控制系统、商业、模式识别、语音识别等多个领域得到了广泛的应用。