Multi-layer self-organizing polynomial neural networks and their development with the use of genetic algorithms   总被引：1，自引：0，他引：1  

Sung-Kwun Oh 《Journal of The Franklin Institute》2006,343(2):125-136

In this paper, we introduce a new architecture of genetic algorithms (GA)-based self-organizing polynomial neural networks (SOPNN) and discuss a comprehensive design methodology. Let us recall that the design of the “conventional” PNNs uses an extended group method of data handling (GMDH) and exploits polynomials (such as linear, quadratic, and modified quadratic functions) as well as considers a fixed number of input nodes (as being selected in advance by a network designer) at polynomial neurons (or nodes) located in each layer. The proposed GA-based SOPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional PNNs. The design procedure applied in the construction of each layer of a PNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomial, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the network. To evaluate the performance of the GA-based SOPNN, the model is experimented with using chaotic time series data. A comparative analysis reveals that the proposed GA-based SOPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.  相似文献   

基于组合神经网络的聚合物质量预测   总被引：2，自引：0，他引：2  

潘海天  夏陆岳  蔡亦军  李伯耿 《科技通报》2004,20(4):298-302

介绍了一种将组合神经网络用于聚合物质量预测的方法．由定量数据建立的单一神经网络模型往往缺乏泛化能力，而使用组合神经网络模型则可以显著改善模型的泛化能力．由于在建立组合神经网络模型过程中，合适的组合权重对模型是否具有良好预测性能是非常重要的，因此采用了岭回归方法来选择合适的组合权重．所提出的方法已成功应用于PVC颗粒特性的预测研究中。研究结果表明，与单一神经网络模型相比，组合神经网络模型具有更佳的模型预测精度和鲁棒性．  相似文献   

多源单汇无线传感器网络的局部路由算法     

孙波  高随祥  迟锐  黄菲 《中国科学院研究生院学报》2007,24(4):401-407

无线传感器网络节点有着严格的能量限制，目前已有的许多路由协议假定了节点知道网络的全局信息或者让节点根据路由表进行路由。这些方式均会使网络产生较多的通信负荷，增大能量开销。结合多源单汇路由的特点，本文提出了几种局部路由算法。该算法中，节点仅根据目标节点与邻居节点的地理位置、剩余能量等信息，决定下一跳节点，最终建立到达目的节点的路径。本文首次引入了带约束后跳发射的思想，并将这种后跳发射与已有的算法相结合得到新的后跳路由算法。计算机仿真实验表明，在有数据融合的网络中，带约束的后跳－为难度路由算法使得网络的生存时间最长，较其余算法增加了网络11%和14%的工作周期数。最后又将局部路由算法进行合理改进，得到最小化平均为难度的算法，应用于无数据融合的网络中，效果很好。  相似文献   

基于神经网络的知识选择     

黄立军 《情报科学》2002,20(5):497-499,505

知识选择（KS）是一种全新的方法，其过程由三个滤波器实现：（1）辨识过程，即根据查询的组合属性选择知识项。（2）自适应过程，即为滤波而使用相关的背景适应知识。（3）预测过程，即提前几步预测未来的查询。本文提出了用神经网络求解KS问题的方法以及KS在计算机安全领域的应用方法。  相似文献   

英汉网络语言的构词共性研究     

刘智慧 《湖南师范大学社会科学学报》2011,40(5):119-122

词汇是构成语言的三大要素之一,它在承载着语音的内容同时又体现着语法的功能。词汇作为一个开放的体系,是语言中最敏感、最富于变化的部分。网络的出现催生了大量的网络词语。我们的研究表明,英汉网络词语主要通过合成、缩略、转义和生造法构成,体现了两种语言的共性,反映了网络语言的简洁、新颖和不稳定性。  相似文献   

一类神经网络的指数稳定性分析     

孙春香  李冠军 《绵阳师范学院学报》2011,30(8)

避免构造Lyapunov函数的困难,运用广义Dahlquist数方法研究了一类神经网络模型平衡点的存在唯一性和指数稳定性,在没有假设激活函数具有可微性、有界性的条件下,得出新的判据。  相似文献   

Predicting citation counts based on deep neural network learning techniques     

《Journal of Informetrics》2019,13(2):485-499

With the growing number of published scientific papers world-wide, the need to evaluation and quality assessment methods for research papers is increasing. Scientific fields such as scientometrics, informetrics, and bibliometrics establish quantified analysis methods and measurements for evaluating scientific papers. In this area, an important problem is to predict the future influence of a published paper. Particularly, early discrimination between influential papers and insignificant papers may find important applications. In this regard, one of the most important metrics is the number of citations to the paper, since this metric is widely utilized in the evaluation of scientific publications and moreover, it serves as the basis for many other metrics such as h-index. In this paper, we propose a novel method for predicting long-term citations of a paper based on the number of its citations in the first few years after publication. In order to train a citation count prediction model, we employed artificial neural network which is a powerful machine learning tool with recently growing applications in many domains including image and text processing. The empirical experiments show that our proposed method outperforms state-of-the-art methods with respect to the prediction accuracy in both yearly and total prediction of the number of citations.  相似文献   

复杂网络上传染病防控的研究     

王剑凌 《福建教育学院学报》2011,(2):125-128

在分析小世界网络和无标度网络的概念和特征的基础上,回顾经典的传染病模型,从隔离和接种疫苗两个方面,对复杂网络上传染病防控的研究成果进行系统总结,并展望未来的发展趋势。  相似文献   

论地方电大在线平台如何应对网络文化的挑战     

杜俊 《广州广播电视大学学报》2011,11(2):42-45,109

网络文化的发展对地方电大在线平台有巨大的影响,从规范化、信息化、个性化到＂自由＂化。在线平台不仅要在平台页面和栏目上精心设计,内容丰富,及时更新,而且要搭建学员与教学人员及时互动的交流平台,同时大力强化网站管理,与相关学习之间门户联合,资源互补,以应对挑战。  相似文献   

基于混合图的在线社交网络朋友推荐算法     

俞琰  邱广华  陈爱萍 《现代图书情报技术》2011,(11):54-59

针对在线社交网络朋友推荐问题,尝试融合多个社会网络为一个混合图模型,采用基于混合图模型的重启动随机游走算法,为用户提供个性化的朋友推荐,并通过参数调节多个网络的权重。实验表明,该算法提高了在线社交网络朋友推荐的准确性。  相似文献