查询词典 neural network

With introducing the Proportional to Population Size Sampling technique into resample for the problem of specimen reconstruction effectiveness and rationality, a neural network ensemble method based on the PPS technique was proposed, which could improve the accuracy of individual network and the differences among individual networks; and a new dynamic selection approach of individual network in a neural network ensemble was put forward.

针对样本重组的有效性和合理性问题，将PPS抽样技术引入样本重构，提出了基于PPS抽样的集成神经网络算法，以提高个体神经网络的准确性与差异度，并实现动态选择个体神经网络的神经网络集成新方法。

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。

The practicality of using rough set to reduce the date was discussed, in this paper, and the interval-valued continuous attribute discretization by applying self-organizing map neural network clustering was proposed, too. This article proposes a simplified indiscernible matrix's method, which reduces the example's condition attribute and eliminates the redundant information of the date. What's more, it provides the methods used to diagnosis compressor's faults based on the intelligence hybrid system by adopting the MATLAB neural network workbox. At last, the functional modules which make up into intelligence hybrid system for fault diagnosis was introduced, including: data acquisition module, date preprocessor module, date reduction module, neural network module, fault diagnosis module and fault expressing module. Here, the article also gives the flow of work of all the above modules.

论文论述了应用粗集对故障数据进行约简的可行性，并应用自组织映射神经网络的聚类功能，来实现连续属性值的离散化方法；给出了简化的分明矩阵法，并用该方法实现了样本条件属性的约简，消除了样本数据中的冗余信息；采用MATLAB神经网络工具箱建立了压缩机的部分故障类型的智能混合诊断系统；最后介绍了智能混合故障诊断系统的功能模块组成，各功能模块分别为：数据采集模块，数据预处理模块，数据约简模块，神经网络模块，故障诊断模块，故障解释模块；并给出了各功能模块的工作流程。

The model of Protein Secondary Structure based on the multi-modal neural network This paper proposed a multi-modal neural network predictable model that synthesizes by 7 BP neural network group in protein secondary structure prediction, this model use "profile" encoding method and "the distance" between the amino acid for the excitory input information, has carried on the prediction to the protein secondary structure prediction.

3基于多神经网络的蛋白质二级结构预测模型论文提出了一个由 7 个 BP 神经网络组合成的多神经网络的蛋白质二级结构预测模型，该模型采用&profile&编码方式和氨基酸间的&距离&为激励输入信息，对蛋白质二级结构进行了预测。

Fifth, it is very promising to combine neural network or fuzzy neural network and adaptive control theory into a adaptive neural network system, aiming at solving the problems of non linearity and nondetermination.

第五，为了较好地解决系统非线性、不确定性的问题，将神经网络、模糊神经网络与自适应控制理论相结合形成自适应神经网络系统是一条有广阔前景的途径。

This paper first introduces the basic principle and concept of data fusion, summarizes levels and model structure of data fusion, summarizes common algorithms and sorts them, separately expounds data fusion algorithms, neural network and evidence theory, and lucubrates the structure design of neural network. And then, the advantages and disadvantages of neural network and the evidence theory are discussed. In order to colligate the two algorithms strongpoint and increase the fault diagnosis accuracy, fault diagnosis method using data fusion integrated Ann and evidence theory is presented and diagnosis approach of this method is expatiated on.

本文首先对数据融合的基本原理、基本概念进行了阐述，总结了数据融合的层次和模型结构形式，并对常用的融合算法进行了总结分类；分别对数据融合算法—神经网络方法和证据理论方法—进行了详细的阐述，同时对神经网络的结构设计进行了深入研究；然后对神经网络和证据理论方法优缺点进行了分析，在此基础上为了实现两种算法优势互补，提高诊断的准确率，提出了神经网络和证据理论集成的数据融合故障诊断法，并详细阐述了这种方法的诊断原理。

A neural network predictive control based on neural network multistep prediction and a neural network predictive control for autopilots of ships based on fuzzy predictive model are proposed.

提出了基于神经网络多步预测输出的船舶航行神经网络预测控制。提出了基于模糊预测模型的船舶航行神经网络预测控制。

Firstly, This text has described information fusion technology characteristic, form structure and concrete processing method, and application of information fusion in fault diagnosis proves the feasibility and validity from the angle of information theory. Based on this,it is combined the fault diagnosis of aeroengine with Information fusion, a method and model which the fault diagnosis of aeroengine information fusion is brought forward. a research which combined neural networks with D-S evidence is brought forward. Based on the analysis of single neural network characteristic, the model of roted neural network is put forward. With the simulation based on the example, we can know evidence theory fusion improved the fault diagnosis It is hard to give the basic probability function in the process of using the evidence theory, So the model based on network and D-S evidence is put forword.

本文首先论述了信息融合技术的特点、形式结构和具体的处理方法，并从信息论的角度论证了信息融合技术在故障诊断中的可行性和有效性；在此基础上，将航空发动机故障诊断与信息融合相结合，提出了一种基于信息融合技术的发动机故障诊断模型和方法，并在此基础上，提出和分析了基于人工神经网络和D-S证据理论的信息融合故障诊断，研究了神经网络的建模方法、组建原则和实现策略，并结合诊断实例进行了分析；提出了基于D-S证据理论的决策融合，阐述了D-S证据理论的方法，模型，并结合算例进行了分析。

According to the characteristic of wavelet packet transformation and fuzzy neural network, this paper proposed a new method of discriminating fault line for single-phase ground in distribution system based on the wavelet packet transformation and fuzzy neural network. The wavelet packet fuzzy neural network trained by the post fault zero sequence current is used to discriminate the fault line.

根据小波包变换和模糊神经网络的特点，提出了基於小波包变换模糊神经网络的一种小电流接地系统单相接地故障选线方法，即利用经过接地后零序电流训练的小波模糊神经网络来判别接地线路。

According to the study result of the recognizers based on Hidden Markova Model and on distance classification respectively,in this paper we introduce two handwriting recognition systems based on neural network ensemble,the comparison neural network recognition system and the permutation neural network recognition system.

国家自然科学基金项目（40776044）；上海市自然科学基金（08ZR1404600）马婉婕，硕士，主研领域：人工智能，图像处理在研究基于隐马尔可夫模型的识别器和基于距离分类器的识别器的识别结果基础上，提出两种基于集成神经网络的手写识别系统：比较神经网络识别系统和全排列神经网络识别系统。

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。