An image reconstruction algorithm based on artificial fish-swarm for electrical capacitance tomography system

Abstract

According to the fundamental principles of electrical capacitance tomography (ECT), 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.