1,359 research outputs found
GA Based Robust Blind Digital Watermarking
A genetic algorithm based robust blind digital watermarking scheme is presented.
The experimental results show that our scheme keeps invisibility, security and robustness
more likely than other proposals in the literature, thanks to the GA pretreatment.Junta de AndalucĂa FQM-01
FREE SEARCH AND DIFFERENTIAL EVOLUTION TOWARDS DIMENSIONS NUMBER CHANGE
This paper presents an exploration of Free Search (FS) and modified Differential Evolution (DE) with enhanced adaptivity. The aim of the study is to identify how these methods can cope with changes of the number of variables of a hard design test, unaided. The results suggest that both methods can adapt successfully to the variation of the number of variables and constraint conditions. The results are presented. Contributions to the engineering design are replacement in high extent of human based search with machine based and movement of optimisation process from human guided to machine self guided search
Adaptive intelligence: essential aspects
The article discusses essential aspects of Adaptive Intelligence. Experimental results on optimisation of global test functions by Free Search, Differential Evolution, and Particle Swarm Optimisation clarify how these methods can adapt to multi-modal landscape
and space dominated by sub-optimal regions, without supervisorsâ control. The achieved results are compared and analysed
Free Search Towards Multidimensional Optimisation Problems
The article presents experimental results achieved from a novel heuristic algorithm for real-value search and optimisation called Free Search (FS). The aim is to clarify the abilities of this method to return optimal solutions from multidimensional search spaces currently resistant to other search techniques
Optimising the topology of complex neural networks
In this paper, we study instances of complex neural networks, i.e. neural
netwo rks with complex topologies. We use Self-Organizing Map neural networks
whose n eighbourhood relationships are defined by a complex network, to
classify handwr itten digits. We show that topology has a small impact on
performance and robus tness to neuron failures, at least at long learning
times. Performance may howe ver be increased (by almost 10%) by artificial
evolution of the network topo logy. In our experimental conditions, the evolved
networks are more random than their parents, but display a more heterogeneous
degree distribution
HEURISTICS OPTIMISATION OF NUMERICAL FUNCTIONS
The article presents an investigation of heuristic behaviour of search algorithms applied to numerical problems. The aim is to compare the abilities of Particle Swarm Optimisation, Differential Evolution and Free Search to adapt to variety of search spaces without the need for constant re-tuning of algorithms parameters. The article focuses on several advanced characteristics of Free Search and attempts to clarify specifics of its behaviour. The achieved experimental results are presented and discussed
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