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自适应神经网络在确定落煤残存瓦斯量中的应用
- 落煤残存瓦斯量的确定是采掘工作面瓦斯涌出量预测的重要环节,它直接影响着采掘工作面瓦斯涌出量预测的精度,并与煤的变质程度、落煤粒度、原始瓦斯含量、暴露时间等影响因素呈非线性关系。人工神经网络具有表示任意非线性关系和学习的能力,是解决复杂非线性、不确定性和时变性问题的新思想和新方法。基于此,作者提出自适应神经网络的落煤残存瓦斯量预测模型,并结合不同矿井落煤残存瓦斯量的实际测定结果进行验证研究。结果表明,自适应调整权值的变步长BP神经网络模型预测精度高,收敛速度快 该预测模型的应用可为采掘工作面瓦斯涌
QuantitativeAnalysisofGasMixtureUsinganArtificialN
- 优选了分析CO、H2和CH4混合气体的传感器阵列,构造了传感器信号预处理和神经网络 训练算法,从而建立了用于混合气体定量分析的人工嗅觉系统。实验结果证明,系统能够以较高的 精度分辨出3种气体的浓度。 -Optimization of the analysis of CO, H2 and CH4 mixed gas sensor array, constructs a sensor signal pre-processing and neural network training al
R36clusterings
- function in R software to calculate 36 clusterings of a data matrix (clusterings are in columns), using hierarchical average, cosine, centroid and single linkages, pam and neural gas and applying the Euclidean distance to the data. Clusterings can
aaa
- 基于吸收峰混叠的红外混合气体分析方法的研究。关于红外气体分光法检测时，相关气体吸收混叠情况的神经网络算法-Based on the infrared absorption peak aliasing hybrid gas analysis studies. With regard to detection of infrared gas spectroscopy, the relevant gas absorption-aliasing of neural network algorithm
ccc
- 基于神经网络技术提高红外气体分析器的选择性，关于神经网络算法研究-Based on neural network technology to improve the selectivity of infrared gas analyzer on the study of neural network algorithm
2009.12.31
- 该文件中有大量有关无线传感器网络方面的相关论文，有加权组合三边气体源定位算法、分布式射频干涉定位法、以及人工神经网络定位等方面的论文。希望对研究无线传感器网络的朋友们有所帮助。-The document contains a lot of information related to wireless sensor networks, papers, there is a weighted combination of the trilateral gas source localization
BP
- 这是基于单片机结合人工神经网络进行气体浓度检测设计里的关于人工神经网络程序设计的代码-This is based on the microcomputer with the artificial neural network design in gas concentrations detected on the artificial neural network programming code
my_ga
- Rudolph G. Convergence analysis of canonical genetic algorithms. IEEE Trans. On Neural Networks, 1994,5:96~101 [36] Rudolph G. Asymptotic convergence rates of simple evolutionary algorithms with Cauchy mutations. IEEE Transactions on Evoluti
neural_gas2
- neural gas algorithm is used in applications of artificial intelligence
wavelet-transform
- 基于最佳小波变换和神经网络的气体非线性荧光光谱的识别-Based on best wavelet transform and neural network non-linear fluorescence spectra of the gas identification
005
- 基于EMD、关联维数及神经网络理论，采用UbVIEW虚拟仪器开发平台 研制了一套内燃机燃气系统无拆卸故障诊断的虚拟仪器，该系统采用模块化结构， 具有快速可重组的优点，由压电式加速度传感器、光电传感器、电荷放大器、 PCI一6133同步数据采集卡、PC机以及采用LabVIEW开发的测试软件构成，测试软 件包括数据采集模块、故障特征值定义模块以及故障类型识别模块三大部分 -Based on the EMD, and the correlation dimension and ne
d4ef13.ZIP
- 基于黄金分割和BP网络的气体体积分数预测模型Based on the golden section and BP neural network prediction model of gas volume fraction-Based on the golden section and BP neural network prediction model of gas volume fraction
meiqilu
- RBF神经网络仿真BJ煤气炉数据，运用matlab软件自带的函数进行仿真。-RBF neural network simulation BJ gas furnace data, use the Matlab software comes with a function to be simulated.
BJM
- 采用梯度下降法确定RBF神经网络基函数的中心，煤气炉数据辨识的仿真研究-Using gradient descent method to determine the center of the RBF neural network basis function, the identification of the gas furnace data simulation study
VISITAbp
- 电力变压器是电力系统中的主要设备之一，利用它可以把不同电压的电网联结在一起，组成复杂的电网或庞大的电力系统，并在其中发挥着重要的作用。电力变压器的可靠运行关系到整个电网的安全，如何对电力变压器的运行中的故障进行诊断，已成为电力部门急需解决的问题。目前，以油中溶解气体为特征量对变压器的故障进行分析，得到了广泛应用。 本次设计要求对电力变压器的内部故障进行广泛了解，并应用BP神经网络对变压器进行智能故障诊断软件设计，实现变压器内部故障论断。主要包括以下内容： 1、掌握用以变压器油中气体为特征
Neural-Gas
- 本算例是一个简单有效，可以直接进行的Neural-Gas 竞争学习聚类算法-his implementation aims to be simple and direct. More powerful implementations of the Neural-Gas Competitive Learning Algorithms
gas-furnace
- mtlab cod fuzzy wavelet neural network
GNG---Original
- MATLAB code for Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes
Graph-based clustering and data visualization algorithms
- This Matlab package is written specifically for the book Ágnes Vathy–Fogarassy and János Abonyi: Graph-based clustering and data visualization algorithms. The purpose of the package is to demonstrate a wide range of graph-based clustering and visuali
GNG
- Neural Gas Network matlab code