Intelligent non-linear modelling of an industrial winding process using recurrent local linear neuro-fuzzy networks

This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system. A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT), which is an incremental tree-based learning algorithm. The proposed NF models are compared with other known intelligent identifiers, namely multilayer perceptron (MLP) and radial basis function (RBF). Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system. Experimental results show the effectiveness of our proposed NF modelling approach.     

Access数据库的三个教学案例设计

针对初学者在学习Access数据库中遇到的困难,设计了三个教学案例,介绍报表中计算控件的使用、if语句的语法格式和通配符“？”和“’,的使用．对于提高Access数据库的教学效果有一定的参考价值。     

Assessing terrestrial wildlife populations in the Toronto and Region Area of Concern

Beneficial use impairments (BUIs) under the Great Lakes Water Quality Agreement identify environmental issues requiring remedial action within the Great Lakes Areas of Concern (AOCs). We conducted this study to support the assessment of the wildlife component of BUI 3: degradation of fish and wildlife populations. We compared bird and amphibian (frogs and toads) data from the Toronto and Region Conservation Authority’s Terrestrial Long-term Monitoring Program in the Toronto and Region AOC to an adjacent, but otherwise similar, reference watershed, Duffins Creek. Twelve of 13 targets were met within the AOC for forest bird, wetland bird, meadow bird and amphibian populations based on averages of mean annual values at sites within the AOC that were within two standard deviations of averages at sites in the Duffins Creek reference watershed between 2008 and 2017. Even though wildlife populations within the AOC were within the normal range of variability expected from a reference watershed, they were often at lower levels than within the Duffins Creek reference watershed. In addition, forest bird and amphibian populations were negatively affected by urbanization within the AOC and meadow bird indices declined. We conclude that while wildlife populations within the AOC currently meet targets for BUI 3, they continue to be negatively impacted by numerous stressors that are primarily related to past and ongoing urbanization. Thus, continued restoration of wildlife habitat and protection of existing habitat within the AOC is highly recommended.     

白浮泉形成及断流原因分析

本研究在分析已有资料的基础上,通过资料分析和水化学测试,查明白浮泉主要接受东北部兴寿地区同一含水层顺层流动补给和北部十三陵地区地表水沿大宫门古河道补给,在化庄地区水流受相对隔水层阻挡,沿山前基岩破碎带排泄形成的.随着区域大气降水的减少和十三陵水库采取的防渗措施,以及地下水开采量增加,白浮泉接受的补给量大幅减少,导致其断流.本研究通过资料搜集、水化学分析等手段查明了白浮泉形成和断流原因,为白浮泉复涌提供了基础资料支撑.     

Data stream classification with novel class detection: a review,comparison and challenges

Knowledge and Information Systems - Developing effective and efficient data stream classifiers is challenging for the machine learning community because of the dynamic nature of data streams. As a...     

Influential facilities placement over moving objects

Distributed and Parallel Databases - In this paper we propose and study the problem of k-Collective influential facility placement over moving object. Specifically, given a set of candidate...     

Spatial division networks for weakly supervised detection

Neural Computing and Applications - With only global image-level annotations, weakly supervised learning of deep convolutional neural networks has shown enough capacity in classification and...     

A hybrid model for spelling error detection and correction for Urdu language

Neural Computing and Applications - Detecting and correcting misspelled words in a written text are of great importance in many natural language processing applications. Errors can be broadly...     

Texture compensation with multi-scale dilated residual blocks for image denoising

Neural Computing and Applications - Deep convolutional neural networks have achieved great success for image denoising recently. However, increasing the depth of the neural network cannot...     

具有时变状态滞后2-D离散系统的稳定与镇定(英文)

针对一类由局部状态空间(LSS)Fornasini-Marchesini(FM)第二模型描述的,具有时变状态滞后的2-D离散系统,其中时变滞后项的上、下界均为正实数,研究了其稳定性和控制综合问题。首先,利用Lyapunov-Krasovski泛函方法,提出了系统的稳定性准则。再根据这一准则,分别设计状态反馈和动态输出反馈控制器保证系统的稳定性。状态反馈控制律和输出反馈矩阵可由线性矩阵不等式(LMI)求得。最后,通过数值算例说明所得结果的有效性。