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	Data Driven Vibration Control: A Review 期刊论文 OAI收割 IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 9, 页码: 1898-1917 作者: Weiyi Yang; Shuai Li; Xin Luo \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2024/08/09 Data driven vibration control (DDVC) data science designing method feedforward control industrial robot input shaping optimizing method residual vibration
	Systemic model for software cost analyzing and optimizing (EI CONFERENCE) 会议论文 OAI收割 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011, May 27, 2011 - May 29, 2011, Xi'an, China 作者: Zhanglei; Zhanglei 收藏 \| 浏览/下载：60/0 \| 提交时间：2013/03/25 Constructing low cost software is the main method to save energy source in computer science. Traditional research about software cost is only in one level. They are partial in some degree. To settle the problem a systemic model for software cost analyzing and optimizing is proposed in this paper. In this systemic model software cost analyzing and optimizing are from low level to high level. It can provide all-sided analyzing and optimizing in instruction source code level and structure level. Some suggestions and methods are given in each level to enrich the model. The systemic model expresses a new point of view in software cost. 2011 IEEE.
	Structure optimization of strap-down inertial navigation system support (EI CONFERENCE) 会议论文 OAI收割 2011 2nd International Conference on Mechanic Automation and Control Engineering, MACE 2011, July 15, 2011 - July 17, 2011, Inner Mongolia, China 作者: Wang J.; Sun H.; Sun H. 收藏 \| 浏览/下载：31/0 \| 提交时间：2013/03/25 In order to meet the requirement of inertial navigation components and minimizing the system's weight and topological optimization was conducted. Then topological optimization and size optimization were conducted under conditions of random vibration and impact. Firstly according to the dynamic characteristics of missile and requirement of inertial navigation system the structure of inertial navigation support was designed according to types of missile connection and space arrangement of electronic components the method of transforming multi-loading cases to multi-loading constraints was used to optimizing the size of the support under conditions of random vibration and impact. Comparing to the original support structures RMS accelerations in installed points reduced by 25.2% under random vibration the weight of optimal structures reduced by 28.1% the structures also met the requirement of inertial navigation system under condition of impact. The support structure shows improvements in both dynamic characteristic and light weight comparing with the original one. 2011 IEEE.
	Using bidirectional binary particle swarm optimization for feature selection in feature-level fusion recognition system (EI CONFERENCE) 会议论文 OAI收割 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, May 25, 2009 - May 27, 2009, Xi'an, China 作者: Wang D.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：23/0 \| 提交时间：2013/03/25 In feature-level fusion recognition system the other is optimizing system sensor design to get outstanding cost performance. So feature selection become usually necessary to reduce dimensionality of the combination of multi-sensor features and improve system performance in system design. In general there are two main missions. One is improving the recognition correct rate as soon as possible the optimization is usually applied to feature selection because of its computational feasibility and validity. For further improving recognition accuracy and reducing selected feature dimensions this paper presents a more rational and accurate optimization Bidirectional Binary Particle Swarm Optimization (BBPSO) algorithm for feature selection in feature-level fusion target recognition system. In addition we introduce a new evaluating function as criterion function in BBPSO feature selection method. At the last we utilized Leave-One-Out method to validate the proposed method. The experiment results show that the proposed algorithm improves classification accuracy by two percentage points while the selected feature dimensions are less one dimension than original Particle Swarm Optimization approach with 16 original feature dimensions. 2009 IEEE.
	Novel method for optimizing polishing tool-path in CCOS based on weighted-iterative algorithm (EI CONFERENCE) 会议论文 OAI收割 4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, November 19, 2008 - November 21, 2008, Chengdu, China 作者: Zhang X.-J.; Wang X.; Wang X.; Wang X.; Wang X.-K. 收藏 \| 浏览/下载：40/0 \| 提交时间：2013/03/25 In Computer Controlled Optical Surfacing (CCOS) polishing tool-path is the base of solving other control parameters such as dwell time. In order to improve the fabrication results of polishing off-axis aspheric a novel method to optimize the tool-path is discussed in this paper. The optimizing method named weighted-iterative algorithm is according to the balance principle of the particle system. The power factor of each dwell point represents the requirement of dwell density. Considering the factors which influence the polishing result the power factors cosist of three elements include constant error distribution and dwell distance of workpiece edge. The tool-path is solved by numerical iterative method. In the end an error data is simulated with actual parameters using the matrix-based algorithm with two different tool-paths. The one is X-Y uniform spacing model and the other one is to optimize it based on the first. The comparison shows that the results of the optimized one are much better than traditional one especially the rms convergence rate. Theory of the algorithm is simple and exercisable and it satisfies practical requirement as well. 2009 SPIE.
	Optimizing control mode of optical payloads based on multi-population genetic algorithm (EI CONFERENCE) 会议论文 OAI收割 2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009, August 9, 2009 - August 12, 2009, Changchun, China Xu W.; Jin G. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 Optimizing the control mode of optical payload could improve the payload's work efficiency. When the mathematic model of payload's control mode was established optimization problems could be boiled down to seek the maximal value of the function with many variables. This paper put forward a calculational method to base the mathematic model the calculational method was multi-population genetic algorithm (MPGA). After the 0-1 variables and real multidimensional ones had been coded separately the algorithm established the populations independently made the multidimensional variables as the centrosome and combined 0-1 ones to work out the maximal value of the function which was established to describe the control mode of the optical payload. Moreover the emulational experiment had been done with the material arithmetic operators. The result indicates that the method using MPGA can hurdle the disadvantage of traditional ones which calculate slowly and get into local best value trap easily . It has the characters that not only fits large scale area scout but also gets the best value in full scale rapidly so this algorithm can better satisfy the technology demand for the intelligent control of optical payload. 2009 IEEE.
	Study on color model conversion for camera with neural network based on the combination between second general revolving combination design and genetic algorithm (EI CONFERENCE) 会议论文 OAI收割 ICO20: Illumination, Radiation, and Color Technologies, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li Z.; Zhou F.; Wang C.; Li Z. 收藏 \| 浏览/下载：36/0 \| 提交时间：2013/03/25 Munsell color system is selected to establish the mutual conversion between RGB and Lab* color model for camera. The color luminance meter and CCD camera synchronously measure the same color card XYZ value is gotten from the color luminance meter the training error is 0.000748566 it can show that the method combining second general revolving combination design with genetic algorithm can optimize the hidden-layer structure of neural network. Using the data of testing set to test this network and calculating the color difference between forecast value and true value the color picture captured from CCD camera is expressed for RGB value as the input of neural network and the Lab* value converted from XYZ value is regarded as the real color value of target card which the difference is not obvious comparing with forecast result the maximum is 5.6357 NBS namely the output of neural network. The neural network of two hidden-layers is considered the minimum is 0.5311 NBS so the second general revolving combination design is introduced into optimizing the structure of neural network and the average of color difference is 3.1744 NBS. which can carry optimization through unifying project design data processing and the precision of regression equation. Their mathematics model of encoding space is gained and the significance inspection shows the confidence degree of regression equation is 99%. The mathematics model is optimized by genetic algorithm optimization solution is gotten and function value of the goal is 0.0007168. The neural network of the optimization solution is trained
	A Post Processing Method for Optimizing Synthesis Strategy for Oligonucleotide Microarrays 期刊论文 OAI收割 Nucleic Acids Research, 2005, 期号: 11 Kang Ning; Kwok Pui Choi; Hon Wai Leong; Louxin Zhang 收藏 \| 浏览/下载：17/0 \| 提交时间：2012/06/01 A Post Processing Method for Optimizing Synthesis Strategy for Oligonucleotide Microarrays