This paper describes a genetic algorithm (GA) that evolves optimized sets of coefficients for one-dimensional signal reconstruction under lossy conditions due to quantization. Beg...
In this work we provide empirical evidence that shows how a variable-length genetic algorithm (GA) can naturally evolve shorter average size populations. This reduction in chromos...
GA-based clustering algorithms often employ either simple GA, steady state GA or their variants and fail to consistently and efficiently identify high quality solutions (best known...
— This paper presents an approach to the multiple sequence alignment (MSA) problem by applying genetic algorithms with a reserve selection mechanism. MSA is one of the most funda...
Yang Chen, Jinglu Hu, Kotaro Hirasawa, Songnian Yu
— We propose a reduced-complexity genetic algorithm for secure and dynamic deployment of resource constrained multi-hop mobile sensor networks. Mobility and security are relative...