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Adaptive clustering method based on improved ABC (Artificial Bee Colony) algorithm and DE variation strategy

An adaptive clustering and clustering technology, applied in computing, computer components, instruments, etc., can solve problems such as easy to fall into local optimum, and achieve the effect of improving local search ability, search efficiency and post-search speed

Active Publication Date: 2016-03-23
易有乐网络科技(北京)有限公司
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide an adaptive clustering method based on the improved ABC algorithm and the DE mutation strategy. Optimal Disadvantages

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  • Adaptive clustering method based on improved ABC (Artificial Bee Colony) algorithm and DE variation strategy
  • Adaptive clustering method based on improved ABC (Artificial Bee Colony) algorithm and DE variation strategy
  • Adaptive clustering method based on improved ABC (Artificial Bee Colony) algorithm and DE variation strategy

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Embodiment Construction

[0028] Embodiments of the invention are described in detail below, examples of which are illustrated in the accompanying drawings. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0029] The artificial bee colony algorithm is inspired by the foraging behavior of bees, and this algorithm is mainly based on the foraging behavior model of bee colonies. This model contains three core elements: hired bees, non-employed bees and food sources. The former two are responsible for searching for rich sources near the hive. This model also defines two guidance modes: a rich source will feed back a positive signal, thereby guiding more bees to collect honey; a poor source will feed back a negative signal, which will lead to abandoning this food source. These two behaviors are self-organizing and swarm-intelligent.

[0030] Such as figure 1 As shown, the wor...

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Abstract

The invention discloses an adaptive clustering method based on an improved ABC (Artificial Bee Colony) algorithm and a DE variation strategy. The method adopts a variation operation and a crossing operation to replace a single search operation in the original ABC algorithm, and adopts an adaptive DE variation strategy and a new probability selection value method to replace the original method. The method overcomes the defect that the traditional clustering algorithm easily results in local optimum in the late period to a certain degree and the defect of relatively low search speed; the improved ABC algorithm is combined with DE to redefine an artificial bee position update position, so that the algorithm jumps out local optimum as much as possible and then a global optimal solution is found. The clustering result of the method is diverse and accurate, and the algorithm has certain advantages on speed and efficiency.

Description

technical field [0001] The invention relates to a clustering method, in particular to an adaptive clustering method based on an improved ABC algorithm and a DE mutation strategy, and belongs to the technical field of data mining. Background technique [0002] Since the development of swarm intelligence evolutionary algorithm in the 1990s, it has quickly become an important branch of evolutionary algorithm and a new academic research hotspot due to its low requirements on functions, the evolution process has nothing to do with the initial value, and fast search speed. Among the more mature algorithms are Ant Colony Optimization (Ant Colony Optimization) proposed by Dorgo et al. and Particle Swarm Optimization (Particle Swarm Optimization) proposed by Kennedy et al. In recent years, the artificial bee colony (ArtificialBeeColony, ABC) algorithm has also received more and more people's attention. Karaboga proposed artificial bee colony algorithm in 2005, which is an optimizati...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/214
Inventor 蒋炯明薛羽
Owner 易有乐网络科技(北京)有限公司
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