查询词典 neural network

And the modeling of gasifier soft measurement is composed by two methods,which are fuzzy neural network and radial basic function network.

该系统在不增加设备投资的条件下，通过工厂信息集成处理和先进的监控技术，提高生产装置的工艺操作水平和管理水平为目的。

Study modelling thought, network configuration, majorize GNNM(1,1) mode method and learning algorithm of GNNM(1,1) mode combined grey system theory and neural network.

研究了灰色系统理论与神经网络组合的灰色神经网络GNNM(1，1)模型的建模思想、网络结构及其优化GNNM(1，1)模型的方法和学习算法

Study modelling thought, network configuration, majorize GNNM(1,1) mode method and learning algorithm of GNNM(1,1) mode combined grey system theory and neural network. Based on tunnel construction settlement monitoring of Nanjing Metro NO1, simulate and forecast monitoring data by GM(1,1) mode and GNNM(1,1) mode.

研究了灰色系统理论与神经网络组合的灰色神经网络GNNM(1，1)模型的建模思想、网络结构及其优化GNNM(1，1)模型的方法和学习算法；结合南京地铁一号线隧道结构沉降监测实例，分别运用灰色系统理论GM(1，1)模型和灰色神经网络GNNM(1，1)模型对监测数据进行了模拟与预报。

This research has proved that an artificial neural network is capable to differentiate the reactional enhancement of malignant intracranial gliomas in postoperative MR images and the enhancement caused by tumor residual. As a innovative differentiation approach, it requires further studies and researches to determine its applicability in practice, including the increase of training samples, image description standardization, effects to doctoral diagnosis, as well as parameter optimization. With improvements in these elements, the performance of the network will be optimized.

本研究成功地证明了人工神经网络能够鉴别颅内恶性胶质瘤术后磁共振图像的反应性强化与肿瘤残存所致的强化，为解决二者的鉴别这一复杂问题提供了一个新的方法，但是本研究只是初步的应用探讨，能否在实际中应用，还有待于进一步的研究，如训练样本的增加、图像描述的规范化、对医师诊断影响程度、参数的优化等，网络的性能会不断完善和提高。

This research has proved that an artificial neural network is capable to differentiate the reactional enhancement of malignant intracranial gliomas in postoperative MR images and the enhancement caused by tumor residual. As a innovative differentiation approach, it requires further studies and researches to determine its applicability in practice, including the increase of training samples, image de脚本ion standardization, effects to doctoral diagnosis, as well as parameter optimization. With improvements in these elements, the performance of the network will be optimized.

本研究成功地证明了人工神经网络能够鉴别颅内恶性胶质瘤术后磁共振图像的反应性强化与肿瘤残存所致的强化，为解决二者的鉴别这一复杂问题提供了一个新的方法，但是本研究只是初步的应用探讨，能否在实际中应用，还有待于进一步的研究，如训练样本的增加、图像描述的规范化、对医师诊断影响程度、参数的优化等，网络的性能会不断完善和提高。

If the collected study sample form practical project is reprehensive, precise, then select the right network calculate parameters; it is a feasible and accurate study method to forecast the fragment-size distribution by artificial neural network.

只要从工程实际中所收集的学习样本具有代表性、精确性，再正确选取网络结构计算参数，利用人工神经网络对中深孔台阶爆破块度分布预测是一种可行，准确的研究方法。

The main contributions of this thesis to neural network theory and application con- sist of the development of novel network mode...

论文从模型、学习和神经计算三个层次，研究分析了神经元网络的系统理论和应用发展。

Meanwhile, some weaknesses of neural network and fuzzy system can be made up, such as defining structure of network, giving initial weights, improving leafing speed, decreasing the dependence of fuzzy system on experience and so forth.

另一方面，作为智能控制的一个重要分支，模糊控制充分利用人的思维活动特点，用于实现难以建立精确数学模型的复杂对象的控制，已经获得了相当多的成功，并显示了其巨大的优越性。

With the help of case studies, it is shown that the "Fuzz-ART" network is able to predict liquefaction potentials much more satisfactorily than conventional artificial neural network methods.

经由案例分析结果显示，&Fuzz-ART&预估液化潜能可得到较传统类神经网路更为准确有效之评估结果。

After that, the neural network is retrained according to the fault rate corresponding to the inflection point of the fault curve of the network.

由于其产生于对人脑神经网络的模拟，因此，研究者们希望它能具有人脑的各种优良特性。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。