Clustering-Based Particle Swarm Optimization for Electrical Impedance Imaging
نویسندگان
چکیده
An attempt has been made in this paper to solve the non-linear and ill-posed Electrical Impedance Tomography (EIT) inverse problem using clustering-based particle swam optimization (PSO). To enhance optimal search capability in such an ultra high dimension space and improve the quality of the reconstructed image, an adaptive PSO algorithm combined with a modified Newton–Raphson algorithm and a conductivity-based clustering algorithm was proposed. The modifications are performed on the reduction of dimension by dividing all mesh into clusters and initializing particles using the result of the modified Newton–Raphson type algorithm. Numerical simulation results indicated that the proposed method has a faster convergence to optimal solution and higher spatial resolution on a reconstructed image.
منابع مشابه
Clustering of Fuzzy Data Sets Based on Particle Swarm Optimization With Fuzzy Cluster Centers
In current study, a particle swarm clustering method is suggested for clustering triangular fuzzy data. This clustering method can find fuzzy cluster centers in the proposed method, where fuzzy cluster centers contain more points from the corresponding cluster, the higher clustering accuracy. Also, triangular fuzzy numbers are utilized to demonstrate uncertain data. To compare triangular fuzzy ...
متن کاملImage Reconstruction Using Particle Swarm Optimization (PSO) in Electrical Impedance Tomography
Electrical impedance tomography (EIT) aims in reconstructing resistivity distribution of inhomogeneous objects, by using the voltage measurements from the boundary electrodes and facilitates in solving non linear inverse problems. For the medical imaging research community, developing a suitable reconstruction algorithm is a challenging task as the inverse problem in EIT is severely ill-posed. ...
متن کاملStock Price Prediction using Machine Learning and Swarm Intelligence
Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...
متن کاملFuzzy Particle Swarm Optimization Algorithm for a Supplier Clustering Problem
This paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. During recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions is usually complex and unstructured. In general, many quantitative and qualitative factors, such as quality, price, and fl...
متن کاملSolution of Multi-Objective optimal reactive power dispatch using pareto optimality particle swarm optimization method
For multi-objective optimal reactive power dispatch (MORPD), a new approach is proposed where simultaneous minimization of the active power transmission loss, the bus voltage deviation and the voltage stability index of a power system are achieved. Optimal settings of continuous and discrete control variables (e.g. generator voltages, tap positions of tap changing transformers and the number of...
متن کامل