An Image Reconstruction Algorithm Based on Artificial Fish-Swarm for Electrical Capacitance Tomography System

摘要：

According to the fundamental principles of electrical capacitance tomography (F.CT), a new ECT algorithm optimized Radial Basis Function (RBF) neural network algorithm, which is based on Artificial Fish Swarm Algorithm (AFSA) is proposed against the soft field effects and ill-conditioning problems in ECT technology. After giving the mathematic model of the algorithm, this paper also applies the AFSA to the training process of neural networks to compare with the traditional neural network algorithm. At last, a conclusion that with little error, high quality and fast convergence rate, etc. The ECT image reconstruction algorithm which is based on AFSA and the optimized RBF neural networks providing a new way for the ECT image reconstruction algorithm is reached.

关键词： electrical capacitance tomography image reconstruction artificial fish-swarm RBF neural network

作者: Chen Deyun Shao Lei Zhang Zhen Yu Xiaoyang

作者单位: School of Computer Science and Technology Harbin University of Science and Technology Harbin,China

会议类型: 国际会议

会议名称: The 6th International Forum on Strategic Technology(IFOST 2011)(第六届国际战略技术论坛)

会议地点: 哈尔滨

会议语种:英文

页码: 1190-1194

在线出版日期: 2011-08-22（万方平台首次上网日期，不代表论文的发表时间）