高氧化态（Ⅱ─Ⅳ）三核金属簇合物构型的人工神经网络判别方法

本文运用一典型的人工神经网络模型─“反向传播”模型，对高氧化态（Ⅱ─Ⅳ）三核金属簇合物的构型分布进行了分析，得到了较好的分类、预报结果为化合物结构分析提供了新的工具。     

Design and analysis of a plug-in robust compensator: an application to indirect-field-oriented-control induction machine drives

It is well known that the system performance for an indirect-field-oriented-control induction motor drive degrades under the variation of rotor resistance and in the presence of external load torque. In this paper, a plug-in robust compensator for speed and position control enhancement of an indirect-field-oriented-control induction machine drive is developed. In the case where a controller for the induction machine already exists or is in operation with satisfactory nominal tracking performance, this plug-in compensator, designed using the H/sub /spl infin// loop-shaping techniques, can be plugged into the existing controller without affecting the already satisfactory nominal tracking performance of the existing closed-loop system but with the capability to improve the system performance under plant parameter variations and in the presence of external disturbances. Simulation and experimental results are given to validate the proposed plug-in robust compensator.     

Al2O3—TiB2陶瓷刀具材料的高温氧化及其对刀具耐磨性能的影响

研究了Ａｌ２Ｏ３－ＴｉＢ２陶瓷刀具材料在１０００℃下的氧化行为，用ＸＲＤ、ＳＥＭ分析了氧化后的相组成及显微结构。结果表明：Ａｌ２Ｏ３－ＴｉＢ２陶瓷材料在１０００℃空气中氧化增重符合抛物线规律；随ＴｉＢ２含量的增加，该材料的抗氧化能力下降。     

试谈我国紫菜资源的工业利用

介绍了我国紫菜工业在工艺改进、资源开发、综合利用和深度加工等方面的情况,提出了提高产率、降低物耗、增进效益和增加品种的途径。     

RETRACTED ARTICLE: Research on image classification method based on convolutional neural network

Neural Computing and Applications - Image classification method is currently the more popular image technology, but it still has certain problems in practice. In order to improve the image...     

基于广东区域性高职院校创业教育的思考——记广州城建职业学院学生创业教育的探索

职业素质是劳动者对社会职业了解与适应能力的一种综合体现,主要包括职业修养和职业技能。在高职院校中开展创业教育是我国经济形势发展的需要,对于培养学生的实践能力、创新精神和解决学生的就业压力有着十分重要的意义。广州城建职业学院的创业教育可以从以下三方面着手：一是转变观念,营造氛围;二是传授本领,打好基础;三是开展活动,提高能力,逐步探索出一条适合广州城建职业学院特色高职学生创业教育的新路子。     

热处理对Ag—15Al固溶体短程有序度的影响

研究了热处理对Ag-15Al(at％)固溶体合金电阻率和有序参数的影响,由X射线衍射分析表明,合金的短程序转变不是Ag_3Al化合物型的δ第二相的形成,而是α-Ag-Al固溶体原子的有序排列。     

Extracting Takagi-Sugeno Fuzzy Rules with Interpretable Submodels via Regularization of Linguistic Modifiers

In this paper, a method for constructing Takagi-Sugeno (TS) fuzzy system from data is proposed with the objective of preserving TS submodel comprehensibility, in which linguistic modifiers are suggested to characterize the fuzzy sets. A good property held by the proposed linguistic modifiers is that they can broaden the cores of fuzzy sets while contracting the overlaps of adjoining membership functions (MFs) during identification of fuzzy systems from data. As a result, the TS submodels identified tend to dominate the system behaviors by automatically matching the global model (GM) in corresponding subareas, which leads to good TS model interpretability while producing distinguishable input space partitioning. However, the GM accuracy and model interpretability are two conflicting modeling objectives, improving interpretability of fuzzy models generally degrades the GM performance of fuzzy models, and vice versa. Hence, one challenging problem is how to construct a TS fuzzy model with not only good global performance but also good submodel interpretability. In order to achieve a good tradeoff between GM performance and submodel interpretability, a regularization learning algorithm is presented in which the GM objective function is combined with a local model objective function defined in terms of an extended index of fuzziness of identified MFs. Moreover, a parsimonious rule base is obtained by adopting a QR decomposition method to select the important fuzzy rules and reduce the redundant ones. Experimental studies have shown that the TS models identified by the suggested method possess good submodel interpretability and satisfactory GM performance with parsimonious rule bases.