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	Neural Network Predictive R2R Control to CMP Process 会议论文 OAI收割 2011 4th IEEE International Conference on Computer Science and Information Technology, Chengdu, China, June 10-12, 2011 作者: Wang L(王亮); Hu JT(胡静涛) 收藏 \| 浏览/下载：51/0 \| 提交时间：2012/06/06 chemical mechanical polishing RBF neural network predictive control run-to-run control PSO rolling optimization
	Energy-saving scheduling strategy for elevator group control system based on ant colony optimization (EI CONFERENCE) 会议论文 OAI收割 2010 IEEE Youth Conference on Information, Computing and Telecommunications, YC-ICT 2010, November 28, 2010 - November 30, 2010, Beijing, China 作者: Zhang J.-L.; Li J.-F. 收藏 \| 浏览/下载：30/0 \| 提交时间：2013/03/25 Elevator group control scheduling is to dispatch every elevator to serve call requests from different floors based on some certain goal. It's a kind of typical combinatorial optimization problems. Ant colony algorithm is good at solving the discrete combinatorial optimization its well global optimization ability and quick convergence velocity are both necessary to a scheduling algorithm. Moreover reducing passengers' waiting and traveling time is the main focus of current dispatching algorithms neglecting the energy consumed by the elevator system. So it's necessary to research on energy-saving algorithms. For the purpose of elevator group's energy-conservation run the objective function of energy is built ant colony model for elevator group control system is created its optimization mechanism is figured out and convergence of the algorithm is studied in this paper. Simulation results show the effectiveness of the strategy. 2010 IEEE.
	An intelligent video surveillance system (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on E-Product E-Service and E-Entertainment, ICEEE2010, November 7, 2010 - November 9, 2010, Henan, China Gao S. 收藏 \| 浏览/下载：19/0 \| 提交时间：2013/03/25 This paper presents an intelligent video surveillance system. The system is composed of one or more nodes flexibly according to the application scenarios such as private properties banks and museums. Each node is an autonomous vision-based device capable to perform intelligent tasks. It is able to digitize and compress the acquired analog video signals in MPEG-4 standard and then transmit the compressed video stream to the control center. At the same time the node makes use of a statistical approach for real-time detecting moving object and online alarm generation to enable a single human operator to monitor activities over a complex area using a distributed network of active video sensors. The node is implemented on a platform with high performance to ensure that the algorithm is able to run in real-time. Applications demonstrate that the intelligent system has an excellent performance in many scenarios to help people make decisions more accurately and rapidly. 2010 IEEE.
	The study on the near infrared spectrum technology of sauce component analysis (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li S.; Wang C.; Chen X.; Chen X.; Chen X. 收藏 \| 浏览/下载：40/0 \| 提交时间：2013/03/25 The author Shangyu Li engages in supervising and inspecting the quality of products. In soy sauce manufacturing quality control of intermediate and final products by many components such as total nitrogen saltless soluble solids nitrogen of amino acids and total acid is demanded. Wet chemistry analytical methods need much labor and time for these analyses. In order to compensate for this problem we used near infrared spectroscopy technology to measure the chemical-composition of soy sauce. In the course of the work a certain amount of soy sauce was collected and was analyzed by wet chemistry analytical methods. The soy sauce was scanned by two kinds of the spectrometer the Fourier Transform near infrared spectrometer (FT-NIR spectrometer) and the filter near infrared spectroscopy analyzer. The near infrared spectroscopy of soy sauce was calibrated with the components of wet chemistry methods by partial least squares regression and stepwise multiple linear regression. The contents of saltless soluble solids total nitrogen total acid and nitrogen of amino acids were predicted by cross validation. The results are compared with the wet chemistry analytical methods. The correlation coefficient and root-mean-square error of prediction (RMSEP) in the better prediction run were found to be 0.961 and 0.206 for total nitrogen 0.913 and 1.215 for saltless soluble solids 0.855 and 0.199 nitrogen of amino acids 0.966 and 0.231 for total acid respectively. The results presented here demonstrate that the NIR spectroscopy technology is promising for fast and reliable determination of major components of soy sauce.