A5101427165- Advanced Multi-Objective Optimization Algorithms
- Infrared Target Detection Methodologies
- Advanced Image Fusion Techniques
- Metaheuristic Optimization Algorithms Research
- Advanced Image and Video Retrieval Techniques
- Topology Optimization in Engineering
- Remote-Sensing Image Classification
- Satellite Image Processing and Photogrammetry
- Retinal Imaging and Analysis
- Wireless Signal Modulation Classification
- Infrared Thermography in Medicine
- Radar Systems and Signal Processing
- Remote Sensing and Land Use
- Evolutionary Algorithms and Applications
- Blind Source Separation Techniques
PLA Army Engineering University
2018-2021
In this paper, we have proposed an image segmentation approach where combine the concept of fuzzy C-means (FCM) and four-chain quantum bee colony optimization (QA BC) named it as FQABC. FQABC algorithm, firstly, four chains encoding method is introduced to artificial (ABC) algorithm propose QABC then improved. Secondly, improved applied search for optimal initial clustering centers FCM. The overcomes drawbacks FCM which sensitive noisy data. It performs better in convergence, accuracy, time...
The simplicity and success of cuckoo search (CS) algorithm has inspired researchers to apply these techniques the multi-objective optimization field. paper studies application CS for solving problems (MOPs) based on decomposition methods. A new decomposition-based is proposed, called MOCS/D. proposed integrates unique Lévy flights technique improved polynomial mutation into evolutionary Decomposition (MOEA/D). Our approach compared with MOEA/D-SBX MOEA/D-DE test instances. experimental...