학술논문

Detection of Tongue-Based Myeloid Sarcoma Using Novel Cat Swarm Optimization and Comparison with Particle Swarm Optimization Algorithm
Document Type
Conference
Source
2024 7th International Conference on Circuit Power and Computing Technologies (ICCPCT) Circuit Power and Computing Technologies (ICCPCT), 2024 7th International Conference on. 1:347-352 Aug, 2024
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Measurement
Computers
Accuracy
Tongue
Statistical analysis
Particle swarm optimization
Optimization
Novel Cat Swarm Optimization
Leukemia
Image Processing
Artificial Intelligence
Particle Swarm Optimization (PSO)
Language
Abstract
the exact scope of this research work is to compare novel cat swarm optimisation to particle swarm optimisation for tongue-based Myeloid Sarcoma detection. To perform the detection of tumor and leukemia, ten sample tongue datasets were subjected to novel Cat Swarm Optimisation and Particle Swarm Optimisation (PSO) methods, and the fiducial interval remaining at 95%. According to the simulation's performance metrics, Novel Cat Swarm Optimisation outperforms PSO (79%) in terms of accuracy, with a significant level of p = 0.001 (p0.05) in SPSS statistical analysis. From this study, the accuracy of detection of tumor and leukemia using Novel Cat Swarm Optimization showed better results than the PSO algorithm for the considered sample images.