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排序方式: 共有104条查询结果,搜索用时 15 毫秒
1.
《Journal of Process Control》2014,24(7):1068-1075
This paper developed a new variable selection method for soft sensor applications using the nonnegative garrote (NNG) and artificial neural network (ANN). The proposed method employs the ANN to generate a well-trained network, and then uses the NNG to conduct the accurate shrinkage of input weights of the ANN. This paper took Bayesian information criterion as the model evaluation criterion, and the optimal garrote parameter s was determined by v-fold cross-validation. The performance of the proposed algorithm was compared to existing state-of-art variable selection methods. Two artificial dataset examples and a real industrial application for air separation process were applied to demonstrate the performance of the methods. The experimental results showed that the proposed method presented better model accuracy with fewer variables selected, compared to other state-of-art methods. 相似文献
2.
针对冷却水塔的节能操作给出了一种数据驱动的建模与优化方法。首先,基于冷却水塔实际运行数据,应用非负绞杀变量选择方法给出一个自适应模型用于描述冷却水塔过程,该模型对于冷却水塔出口水温具有良好的预测精度。根据变量选择结果,分析了外界空气温度与湿度对冷却能力的影响。然后,提出了基于模型的冷却水塔风机的优化操作策略,并进行实验将之应用于冷却水塔的操作。研究结果显示,基于模型的优化操作具有较大的节能空间。 相似文献
3.
非平稳噪声和低信噪比条件下提高增强语音质量一直以来都是语音增强研究的难题。近年来,卷积非负矩阵分解在语音增强算法中成功应用,本文进一步考虑语音信号在时频域的稀疏性,提出了稀疏卷积非负矩阵分解(Sparse Convolutive Nonnegative Matrix Factorization, SCNMF)的语音增强算法。该算法包括训练和增强两个阶段。训练阶段通过SCNMF算法分别对纯净语音和噪声的频谱进行训练,得到纯净语音和噪声字典,并将其作为增强阶段的先验信息。增强阶段首先通过SCNMF算法对带噪语音的频谱进行分解,然后利用纯净语音和噪声联合字典对语音编码矩阵进行估计,重构增强语音。本文通过实验仿真分析了稀疏因子对增强语音质量的影响。实验结果表明,在非平稳噪声和低信噪比条件下,本文算法增强效果均优于多带谱减、非负矩阵分解、卷积非负矩阵分解等传统的算法。 相似文献
4.
Inmaculada Higueras 《Journal of scientific computing》2009,39(1):115-128
Space discretization of some time dependent partial differential equations give rise to ordinary differential equations containing
additive terms with different stiffness properties. In these situations, additive Runge-Kutta (additive RK) methods are used.
For additive RK methods the curve of absolute monotonicity gives stepsize restrictions for monotonicity. Necessary conditions
for nontrivial curves of absolute monotonicity are the nonnegativity of the additive RK coefficients and some inequalities
on some incidence matrices. In this paper we characterize strong stability preserving additive Runge-Kutta methods giving
some order barriers and structural properties.
Research supported by the Ministerio de Educación y Ciencia, Project MTM2005-03894. 相似文献
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A manufacturing system with both quantitative and qualitative (QQ) quality responses (as a QQ system) is widely encountered in many cases. For example, in a lapping process of the semiconductor manufacturing, the quality of wafer’s geometrical characteristics is often measured by the total thickness variation as a quantitative response and the conformity of site total indicator reading as a binary qualitative response. The QQ responses are closely associated with each other in a QQ system, but current methodologies often model the two types of quality responses separately. This article presents a novel modeling approach, called “QQ models,” to jointly model the QQ responses through a constrained likelihood estimation. The QQ models can jointly select significant predictors by incorporating inherent features of QQ systems, leading to accurate variable selection and prediction. Both simulation studies and a case study in a lapping process are used to evaluate the performance of the proposed method. Supplementary materials to this article are available online. 相似文献
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In this paper, we propose a maximum contrast analysis (MCA) method for nonnegative blind source separation, where both the mixing matrix and the source signals are nonnegative. We first show that the contrast degree of the source signals is greater than that of the mixed signals. Motivated by this observation, we propose an MCA-based cost function. It is further shown that the separation matrix can be obtained by maximizing the proposed cost function. Then we derive an iterative determinant maximization algorithm for estimating the separation matrix. In the case of two sources, a closed-form solution exists and is derived. Unlike most existing blind source separation methods, the proposed MCA method needs neither the independence assumption, nor the sparseness requirement of the sources. The effectiveness of the new method is illustrated by experiments using X-ray images, remote sensing images, infrared spectral images, and real-world fluorescence microscopy images. 相似文献
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提出了一种用于人脸识别新的保持拓扑性非负矩阵分解方法。该方法通过将梯度距离最小化来发现人脸模式内在的流型结构。与PCA、LDA和最初的NMF方法相比较,保持拓扑性非负矩阵分解法发现一种嵌入来保留局部拓扑信息,比如边缘和质地。该文提出的保持拓扑性非负矩阵分解法对在有光照下的面部表情的变化有效。实验结果表明该方法提供了一种更好的脸部表示模式,同时也提高了人脸识别正确率。 相似文献