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Stochastic diffusion search

Stochastic diffusion search (SDS) was first described in 1989 as a population-based, pattern-matching algorithm [Bishop, 1989]. It belongs to a… 
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Papers overview

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2017
2017
The method introduced in this paper uses stochastic diffusion search (SDS) to select the most relevant feature subset for the… 
2015
2015
The use of clustering in various applications is key to its popularity in data analysis and data mining. Algorithms used for… 
2012
2012
Stochastic Diffusion Search (SDS) is a population-based, naturally inspired search and optimization algorithm. It belongs to a… 
2011
2011
Stochastic Diffusion Search (SDS) is a multi-agent, naturally inspired search and optimization algorithm that is based on direct… 
2011
2011
To solve the quadratic knapsack problem,we propose a stochastic diffusion search algorithm which is a novel algorithm based on… 
2010
2010
In recent years studies of social agents have suggested several new metaheuristics for use in search and optimisation; Stochastic… 
2009
2009
Nature has often provided the inspiration needed for new computational paradigms and metaphors [1,16]. However natural systems do… 
2008
2008
This paper describes the development of an extension of a best-fit string-matching algorithm, Stochastic Diffusion Search. The… 
2007
2007
Stochastic Diffusion Search is a well characterised robust swarm intelligence global metaheuristic, that can efficiently solve… 
2004
2004
Stochastic Diffusion Search (sds) was introduced by Bishop (1989a) as an algorithm to solve pattern matching problems. It relies…