Abstract:
This paper presents a novel multi-level quantization scheme which best approximates the sigmoid function for multi-value discrete variable transformation in PSO. We defin...Show MoreMetadata
Abstract:
This paper presents a novel multi-level quantization scheme which best approximates the sigmoid function for multi-value discrete variable transformation in PSO. We define the set of multi-level quantization as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming particle's position into multilevel discrete values. In this paper, the feasibility of the proposed technique was tested in photovoltaic (PV) system allocation problem, and a comparison study with genetic algorithm (GA) is performed to show the quality of the solutions obtained.
Published in: 2009 IEEE International Conference on Fuzzy Systems
Date of Conference: 20-24 August 2009
Date Added to IEEE Xplore: 02 October 2009
ISBN Information:
Print ISSN: 1098-7584
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Particle Swarm ,
- Particle Swarm Optimization ,
- Discrete Particle Swarm Optimization ,
- Multilevel Quantization ,
- Sigmoid Function ,
- Discrete Variables ,
- Solution Quality ,
- Particle Position ,
- Photovoltaic System ,
- Discrete Transformation ,
- Discretion ,
- Optimization Problem ,
- Standard Deviation Values ,
- Power Loss ,
- Cognitive Components ,
- Nonlinear Programming ,
- Particle Velocity ,
- Dimensional Problems ,
- Random Search ,
- Linear Representation ,
- Continuous Version ,
- Discrete Problem ,
- Position Update ,
- Candidate Solutions ,
- Nonlinear Optimization Problem ,
- Velocity Term ,
- Worst Value ,
- Graph Partitioning ,
- Quantization Levels ,
- Load Buses
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Particle Swarm ,
- Particle Swarm Optimization ,
- Discrete Particle Swarm Optimization ,
- Multilevel Quantization ,
- Sigmoid Function ,
- Discrete Variables ,
- Solution Quality ,
- Particle Position ,
- Photovoltaic System ,
- Discrete Transformation ,
- Discretion ,
- Optimization Problem ,
- Standard Deviation Values ,
- Power Loss ,
- Cognitive Components ,
- Nonlinear Programming ,
- Particle Velocity ,
- Dimensional Problems ,
- Random Search ,
- Linear Representation ,
- Continuous Version ,
- Discrete Problem ,
- Position Update ,
- Candidate Solutions ,
- Nonlinear Optimization Problem ,
- Velocity Term ,
- Worst Value ,
- Graph Partitioning ,
- Quantization Levels ,
- Load Buses