Identification of vulnerable plaque plays an important role in coronary heart disease diagnosis for clinicians. In this paper we propose a novel method based on flexible neural tree (FNT) to identify vulnerable plaque...
详细信息
ISBN:
(纸本)9781728105529
Identification of vulnerable plaque plays an important role in coronary heart disease diagnosis for clinicians. In this paper we propose a novel method based on flexible neural tree (FNT) to identify vulnerable plaques in intravascular optical coherence tomography (IVOCT) images. First, a flexible neural tree classifier is constructed by selecting features of the image. Then, the probabilisticincrementalprogramevolution (PIPE) algorithm optimizes the flexible neural tree structure and uses particle swarm optimization (PSO) to optimize the parameters. Experimental results show that this method can effectively identify vulnerable plaques in IVOCT images.
This paper presents an automatic way of evolving hierarchical Takagi-Sugeno fuzzy systems (TS-FS). The hierarchical structure is evolved using probabilisticincrementalprogramevolution (PIPE) with specific instructi...
详细信息
This paper presents an automatic way of evolving hierarchical Takagi-Sugeno fuzzy systems (TS-FS). The hierarchical structure is evolved using probabilisticincrementalprogramevolution (PIPE) with specific instructions. The fine tuning of the IF-THEN rule's parameters encoded in the structure is accomplished using evolutionary programming (EP). The proposed method interleaves both PIPE and EP optimizations. Starting with random structures and rules' parameters, it first tries to improve the hierarchical structure and then as soon as an improved structure is found, it further fine tunes the rules' parameters. It then goes back to improve the structure and the rules' parameters. This loop continues until a satisfactory solution (hierarchical TS-FS model) is found or a time limit is reached. The proposed hierarchical TS-FS is evaluated using some well known benchmark applications namely identification of nonlinear systems, prediction of the Mackey-Glass chaotic time-series and some classification problems. When compared to other neural networks and fuzzy systems, the developed hierarchical TS-FS exhibits competing results with high accuracy and smaller size of hierarchical architecture.
暂无评论