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Everything about Dispersive flies optimisation
Dispersive flies optimisation (DFO) is a bare-bones swarm intelligence algorithm which is inspired by the swarming behaviour of flies hovering over food sources. DFO is a simple optimiser which works by iteratively trying to improve a candidate solution with regard to a numerical measure that is calculated by a fitness function. Each member of the population, a fly or an agent, holds a candidate solution whose suitability can be evaluated by their fitness value. Optimisation problems are often formulated as either minimisation or maximisation problems. Wikipedia →
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- Read the overview: Dispersive flies optimisationA 5-minute orientation
- Read the landmark paper: Neighbour adjusted dispersive flies optimization based deep hybrid sentiment analysis frameworkCited 32 times
- Go sideways: Particle swarm optimizationA closely related topic
- Go sideways: Swarm intelligenceA closely related topic
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🏆 Landmark papers (most cited)
Neighbour adjusted dispersive flies optimization based deep hybrid sentiment analysis framework
Swarmgan: enhancing GAN image generation through latent space optimization using dispersive flies optimization
A new dispersive flies optimisation algorithm for the sum of three cubes
A new dispersive flies optimisation algorithm for the sum of three cubes
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đź”— Related topics
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