检索结果-南通市图书馆

Empirical Study of classification Process for Two-stage Turbo Air Classifier in Series

Chinese Journal of Mechanical Engineering 2013年第3期26卷 526-531页

作者： YU Yuan LIU Jiaxiang LI Gang College of Mechanical and Electrical Engineering Beijing University of Chemical Technology College of Materials Science and Engineering Beijing University of Chemical Technology

The suitable process parameters for a two-stage turbo air classifier are important for obtaining the ultrafine powder that has a narrow particle-size distribution, however little has been published internationally on the classification process for the two-stage turbo air classifier in series. The influence of the process parameters of a two-stage turbo air classifier in series on classification performance is empirically studied by using aluminum oxide powders as the experimental material. The experimental results show the following: 1) When the rotor cage rotary speed of the first-stage classifier is increased from 2 300 r/min to 2 500 r/min with a constant rotor cage rotary speed of the second-stage classifier, classification precision is increased from 0.64 to 0.67. However, in this case, the final ultrafine powder yield is decreased from 79% to 74%, which means the classification precision and the final ultrafine powder yield can be regulated through adjusting the rotor cage rotary speed of the first-stage classifier. 2) When the rotor cage rotary speed of the second-stage classifier is increased from 2 500 r/min to 3 100 r/min with a constant rotor cage rotary speed of the first-stage classifier, the cut size is decreased from 13.16 μm to 8.76 μm, which means the cut size of the ultrafine powder can be regulated through adjusting the rotor cage rotary speed of the second-stage classifier. 3) When the feeding speed is increased from 35 kg/h to 50 kg/h, the 'fish-hook' effect is strengthened, which makes the ultrafine powder yield decrease. 4) To weaken the 'fish-hook' effect, the equalization of the two-stage wind speeds or the combination of a high first-stage wind speed with a low second-stage wind speed should be selected. This empirical study provides a criterion of process parameter configurations for a two-stage or multi-stage classifier in series, which offers a theoretical basis for practical production.

关键词： two-stage turbo air classifier in series aluminum oxide powders process parameters classification performance

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Neural Network Compact Ensemble and Its Applications

引用

Chinese Journal of Mechanical Engineering 2010年第2期23卷 209-216页

作者： WANG Qinghua ZHANG Youyun ZHU Yongsheng Key Laboratory for Modern Design and Rotor-Bearing System of Ministry of Education Xi ＇an Jiaotong University Xi＇an 710049 China School of Mechatronic Engineering Xi＇an Technological University Xi＇an 710032 China

There has been many methods in constructing neural network （NN） ensembles, where the method of simultaneous training has succeed in generalization performance and efficiency. But just like regular methods of constructing NN ensembles, it follows the two steps, first training component networks, and then combining them. As the two steps being independent, an assumption is used to facilitate interactions among NNs during the training stage. This paper presents a compact ensemble method which integrates the two steps of ensemble construction into one step by attempting to train individual NNs in an ensemble and weigh the individual members adaptively according to their individual performance in the same learning process. This provides an opportunity for the individual NNs to interact with each other based on their real contributions to the ensemble. The classification performance of NN compact ensemble （NNCE） was validated through some benchmark problems in machine learning, including Australian credit card assessment, pima Indians diabetes, heart disease, breast cancer and glass. Compared with other ensembles, the classification error rate of NNCE can be decreased by 0.45% to 68%. In addition, the NNCE was applied to fault diagnosis for rolling element bearing. The 11 time-domain statistical features are extracted as the properties of data, and the NNCE is employed to classify the data. With the results of several experiments, the compact ensemble method is shown to give good generalization performance. The compact ensemble method can recognize the different fault types and various fault degrees of the same fault type.

关键词： neural network compact ensemble(NNCE) combination weights classification performance fault diagnosis

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Influence of Pixel Quality, Land Cover, and Hydroclimatic Cycle on Moderate Resolution Imaging Spectroradiometer Inundation Monitoring performance in the Pantanal, Brazil

引用

Journal of Geoscience and Environment Protection 2023年第2期11卷 90-120页

作者： Sérgio Wagner Gripp da Silveira Ibraim Fantin-Cruz Peter Zeilhofer Midwest Regional Unit National Institute for Space Research Cuiabá Brazil Department of Sanitary and Environmental Engineering Federal University of Mato Grosso Cuiabá Brazil Department of Geography Federal University of Mato Grosso Cuiabá Brazil

Moderate resolution imaging spectroradiometer (MODIS) time series (TS) have been widely applied for flood monitoring in large tropical wetlands. However, little systematic work is available on the influence of pixel quality, vegetation cover, and the annual hydroclimatic cycle on classification performance. In this study, this issue is examined based on a six-year, 250 m resolution MOD13Q1 TS underpinned by extensive in situ measurements. The most parsimonious logistic regression model was obtained for land surface water index (LSWI) and enhanced vegetation index (EVI). The inclusion of the 500 m MCD12Q1 land cover Type 2 product improves accuracy. performance markedly decreases for subsets that include pixels with a VI quality assurance (QA) level poorer than 0110 and/or a pixel reliability (PR) of three. When a Savitzky-Golay filter was used for TS reconstitution, performance is slightly lower than those obtained in a classification of a VI QA 0001 or PR = 0 level strata;moreover, these have the advantage of gap-free flood monitoring. The overall accuracy (OA) of the PR = 0 subset is better for grasslands, and slightly lower for Savannah, and for woodland and forests. The average OA is highest for the dry season, intermediate for the rainy/flooded season, and lowest for the transitional seasons, when the wetland becomes flooded or dries. Comparisons of internal, k-fold, and external validations indicate that only external validation enables a realistic assessment of flood-mapping performance. The complete substitution of PR = 3 pixels by filled-in values is recommended for operational flood monitoring, and it is concluded that the use of the simplified PR metrics as filtering criteria for gap filling and smoothing is sufficient for flood monitoring in the Pantanal. classification metrics vary more strongly as a function of the hydrological period than by vegetation cover. MOD13Q1 users should be aware that OA in forest stands during the transition seasons are, on

关键词： MODIS classification performance Flooding LSWI EVI Large Tropical Wetlands

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Novel Approach of Hybrid Genetic Optimization with Elite Ant Colony:Application in the Modulation Recognition

引用

Wuhan University Journal of Natural Sciences 2011年第1期16卷 43-48页

作者： LIU Shu WANG Hongyuan LANG Liang Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan 430074Hubei China

A novel approach （HGO-EAC） for hybrid genetic op-timization （GO） with elite ant colony （EAC） is proposed for the automatic modulation recognition of communication signals,through which we improve the basic ant colony algorithms by referencing elite strategy and present a new fusion strategy for genetic optimization and elite ant colony. This approach is used to train the neural networks as the classifier for modulation. Simula-tion results indicate good performance on an additive white Gaus-sian noise （AWGN） channel,with recognition rate reaching to 70% especially for CW even at signal-to-noise ratios as low as 5 dB. This approach can achieve a high recognition rate for the typical modulations such as CW,4ASK,4FSK,BPSK,and QAM16. Test result shows that it has better performance than BP algorithm and basic ant colony algorithms by achieving faster training and stronger robustness.

关键词： elite ant colony fusion strategy genetic optimization neural networks classification performance modulation recognition

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Improved classification Approach via GEPSVM

引用

Journal of Southwest Jiaotong University(English Edition) 2009年第4期17卷 292-296页

作者：徐晓明姜楠丁秋林 College of Information Science and Technology Nanjing University of Aeronautics and Astronautics

A modified multisurface ＂proximal support vector machine classifier via generalized eigenvalues （GEPSVM for short）＂ was proposed. By defining a new principle, we designed a new classification approach via GEPSVM, namely, maximum or minimum plane distance GEPSVM （MPDGEPSVM）. Unlike GEPSVM, our approach obtains two planes by solving two simple eigenvalue problems, such that it can avoid occurrence of singular problems. Our approach, compared with GEPSVM, has better classification performalce. Moreover, MPDGEPSVM is over one order of magnitude faster than GEPSVM, and almost two orders of magnitude faster than SVM. Computational results on public datasets from UCI database illustrated the efficiency of MPDGEPSVM.

关键词： Generalized eigenvalues Simple eigenvalue Singular problems classification performance

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Power Quality Event Detection and Analysis in Power System Using Neural Network

Power Quality Event Detection and Analysis in Power System U...

引用

第二届国际测量仪器与测试自动化学术会议

作者： Liao Wei~1 Wang Hua~1 Han Pu~2 1 Hebei University of Engineering Handan 050038 China 2 Noah China Electric Power University Baoding 071003 China

＜正＞A novel approach for the power quality（PQ） disturbances classification based on the wavelet transform（WT） and neural network is *** transform is utilized to extract feature vectors for various PQ disturbances and the WT can accurately localizes the characteristics of a signal both in the time and frequency *** feature vectors then are applied to a neural network for training and disturbance pattern *** comparing with a classic neural network,it is concluded that the proposed neural network has better data driven learning and local interconnections *** research results between the proposed method and the other existing method are discussed and the proposed method can provide accurate classification *** the basis of hypothesis test of the averages,it is shown that corresponding to different wavelets selection,there is no statistically significant difference in performance of PQ disturbances classification and the relationship between the wavelet decomposition level and classification performance is *** simulation results demonstrate the proposed method gives a new way for identification and classification of dynamic power quality disturbances.

关键词： Power quality disturbance self-organizing learning array wavelet transform classification performance

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Power Quality Detection and Discrimination in Distributed Power System Based on Wavelet Transform

Power Quality Detection and Discrimination in Distributed Po...

引用

第二十七届中国控制会议

作者： Pang Peilin,Ding Guangbin Hebei University of Engineering,Handan 056038,P.R.China

A novel approach for the power quality（PQ） disturbances classification based on the wavelet transform and self-organizing learning array system is *** network is utilized to extract feature vectors for various PQ disturbances and the wavelet transform can accurately localizes the characteristics of a signal both in the time and frequency *** feature vectors then are applied to the system for training and disturbance pattern *** comparing with a classic neural network,it is concluded that the proposed system has better data driven learning and local interconnections *** research results between the proposed method and the other existing method are discussed and the proposed method can provide accurate classification *** the basis of hypothesis test of the averages,it is shown that corresponding to different wavelets selection,there is no statistically significant difference in performance of PQ disturbances classification and the relationship between the wavelet decomposition level and classification performance is *** simulation results demonstrate the proposed method gives a new way for identification and classification of dynamic power quality disturbances.

关键词： Power quality disturbance Self-organizing learning system Wavelet transform classification performance

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：