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浏览/检索结果: 共3条，第1-3条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 An approach to mutation-based test data generation 会议论文 2013 International Conference on Precision Mechanical Instruments and Measurement Technology, ICPMIMT 2013, Shenyang, Liaoning, China, May 25, 2013 - May 26, 2013 作者:  Wang, Fang;  Rina, Wu;  Lee, Shu Fang;  Zheng, Tian Hua 收藏  |  浏览/下载：4/0  |  提交时间：2017/01/18 Software testing  Data communication systems  Design  Testing  Design approaches  Fault simulation  Mutation operators  Mutation testing  Quality of softwares  Software defects  Test data  Test data generation   基于受控马尔科夫链的软件缺陷优化测试策略 期刊论文 Computer Science, 2012, 卷号: 39, 期号: 5, 页码: 117-119,136 包晓安; 姚澜; 张晓文; 曹建文 收藏  |  浏览/下载：22/0  |  提交时间：2012/11/12 Software cybernetics  Software defects test  Optimal testing strategy  Controlled Markov chain   Double inverted pendulum control based on three-loop PID and improved BP neural network (EI CONFERENCE) 会议论文 2011 2nd International Conference on Digital Manufacturing and Automation, ICDMA 2011, August 5, 2011 - August 7, 2011, Zhangjiajie, Hunan, China Sang Y.; Fan Y.; Liu B. 收藏  |  浏览/下载：28/0  |  提交时间：2013/03/25 To deal with the defects of BP neural networks used in balance control of inverted pendulum  such as longer train time and converging in partial minimum  this article reaLizes the control of double inverted pendulum with improved BP algorithm of artificial neural networks(ANN)  builds up a training model of test simulation and the BP network is 6-10-1 structure. Tansig function is used in hidden layer and PureLin function is used in output layer  LM is used in training algorithm. The training data is acquried by three-loop PID algorithm. The model is learned and trained with Matlab calculating software  and the simuLink simulation experiment results prove that improved BP algorithm for inverted pendulum control has higher precision  better astringency and lower calculation. This algorithm has wide appLication on nonLinear control and robust control field in particular. 2011 IEEE.