2010 Second International Conference on Computational Intelligence and Natural Computing最新文献_第8页

Prediction of the crystal's growth rate based on BPNN and rough sets 基于bp神经网络和粗糙集的晶体生长速率预测

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI: 10.1109/CINC.2010.5643759

Xingbo Sun, Xiuhua Tang

{"title":"Prediction of the crystal's growth rate based on BPNN and rough sets","authors":"Xingbo Sun, Xiuhua Tang","doi":"10.1109/CINC.2010.5643759","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643759","url":null,"abstract":"Ammonium dihydrogen phosphate(DAP) is widely used in the industry. Usually this product contains impurities and substances and may not satisfy the need of modern agricultural and industrial demand, so we must dip and recrystalize for high quality product. In the process of crystallization, the nucleation rate and the growth rate are the most important parameter, then we study these parameter in order to instruct the technology of crystallization. A liquid fluidized bed crystallizer was used to determine the nucleation rate and the growth rate of ammonium dihydrogen phosphate (ADP) at crystallization temperature 15 and 25 for different saturation temperature solution. The growth rate in a Liquid fluidized bed is decided manly by the supersaturation, cooling temperature, saturation temperature and suspension density. In the paper we build a model predicting the growth rate through these conditions based on Back Propagation (BP) neural network with experimental data as training data. The experimental data, which collected from a Liquid fluidized bed, is preprocessed using the level of consistency in rough sets theory before be using as training sets in modeling process. The simulation results show that the neural network model given in this paper is capable of forecasting the behavior of growth rate exactly and rapidly, and the maximum relative error does not exceed 4.8% as compared with measured values. It also indicates the BP network has prodigious practicability.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122830702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Calculation of the electrical parameters for asynchronous motors under the periodically variable running condition 周期性变工况下异步电动机电气参数的计算

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI: 10.1109/CINC.2010.5643742

Yan Ying, Luo Yingli, Lu Wenbin, Hu Bin

{"title":"Calculation of the electrical parameters for asynchronous motors under the periodically variable running condition","authors":"Yan Ying, Luo Yingli, Lu Wenbin, Hu Bin","doi":"10.1109/CINC.2010.5643742","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643742","url":null,"abstract":"The detection and diagnosis for the asynchronous motors' working states under the periodically variable running condition can be achieved by using theirs electrical parameters in the continuous short intervals, and the accuracy of these parameters can directly influence the results of the diagnosis. Fourier Transform has good properties and is a traditional method to exact the electrical parameters from the input signals. Unfortunately, it is easily corrupted by the presences of the frequency fluctuation and the noninteger harmonics in the signals. To overcome this defect of Fourier Transform, this paper presents a computational algorithm based on Complex Morlet Wavelet (CMW) to calculate the motors' electrical parameters, which has better time and frequency characteristics and increases the reliability and accuracy of the detection process. Simulations are conducted to verify the superiority of the proposed algorithm and the simulation results have shown that CMW algorithm is much more reliable and has much higher calculating accuracy than Fourier algorithm.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123389621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A design of CAN-bus based collector for Automatic Meter Reading system 基于can总线的自动抄表系统采集器设计

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI: 10.1109/CINC.2010.5643730

J. Jun, Fan Liang-zhong, Zhang Fu-an

引用次数: 2

Existence and local behavior of general cubic Hermite-Padé Approximation 一般三次hermite - pad<s:1>近似的存在性及局部性质

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI: 10.1109/CINC.2010.5643818

Li Jin

引用次数: 0

Path planning for reconnaissance UAV based on Particle Swarm Optimization 基于粒子群优化的侦察无人机路径规划

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI: 10.1109/CINC.2010.5643794

Yong Bao, Xiaowei Fu, Xiao-guang Gao

引用次数: 40

Using revised string edit distance to sign language video retrieval 使用修改后的字符串编辑距离进行手语视频检索

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI: 10.1109/CINC.2010.5643895

Shilin Zhang, Bo Zhang

{"title":"Using revised string edit distance to sign language video retrieval","authors":"Shilin Zhang, Bo Zhang","doi":"10.1109/CINC.2010.5643895","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643895","url":null,"abstract":"In this paper, we present a revised method to compute the similarity of traditional string edit distance. Given two strings X and Y over a finite alphabet, an edit distance between X and Y can be defined as the minimum weight of transforming X into Y through a sequence of weighted edit operations. Because this method lacks some types of normalization, it would bring some computation errors when the sizes of the strings that are compared are variable. In order to compute the edit distance, a new algorithm is introduced. This algorithm is shown to work in O (m*n*log(n)) time and O(n*m) memory space for strings of lengths m and n. Content-based video retrieval is a challenging field, and most research focus on the low level features such as color histogram, texture and etc. In this paper, we solve the retrieval problem by high level features used by hand language trajectory and compare the similarity by our revised string edit distance algorithms. Trajectory based video retrieval is widely explored in recent years by many excellent researchers. Experiments in trajectory-based sign language video retrieval are presented in our paper at last, revealing that our revised edit distance algorithm consistently provide better results than classical edit distances.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130303490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A new particle swarm optimization algorithm for solving constraint and mixed variables optimization problem 一种求解约束和混合变量优化问题的粒子群算法

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI: 10.1109/CINC.2010.5643867

Wei-gang Wang, H. Ni

引用次数: 0

A trust model based on fuzzy set in peer-to-peer network 基于模糊集的点对点网络信任模型

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI: 10.1109/CINC.2010.5643720

Chang-sheng Zhu, Ying-ying Gso, Lei Qian, Qing-rong Wang

引用次数: 0

Research on the intelligently early warning of the mine safety based on the multi-sensor data fusion technology 基于多传感器数据融合技术的矿山安全智能预警研究

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI: 10.1109/CINC.2010.5643843

Kainan Liu

引用次数: 0

A burst change detection algorithm for data streams 数据流的突发变化检测算法

2010 Second International Conference on Computational Intelligence and Natural Computing Pub Date : 2010-11-22 DOI: 10.1109/CINC.2010.5643822

Xian-fei Yang, Jian-pei Zhang, Yang Jing, Li Xiang

引用次数: 2