A new heuristic density-based ant colony clustering algorithm (HDACC) is presented.
提出一种基于密度的启发性群体智能聚类算法。
The paper presents an ant colony clustering algorithm based on directional similarity: ACCADS.
提出了一种基于方向相似性度量的蚁群聚类算法。
The prediction results show that the method based on ant colony clustering algorithm for estimating fetal weight has certain feasibility.
此预测结果表明，蚁群聚类算法预测胎儿体重的方法具有一定的可行性。
Aiming to the complexity and uncertainty of oil-bearing of reservoir recognition, this paper proposes an improved ant colony clustering algorithm.
针对储层含油性识别过程的复杂性和不确定性，提出一种改进的蚁群聚类算法。
This system used an improved ant colony clustering algorithm to get hand center quickly, established relevant rendering system, and registered the virtual object.
利用一种改进的快速蚁群聚类算法来获取掌形的中心，建立相关的渲染坐标系，从而精确注册虚拟物体。
According to analysis of the data of rock burst samples and from the engineering analogy thinking by the ant colony clustering algorithm, the rock burst can be predicted.
该方法在分析岩爆实例资料的基础上，采用蚁群聚类算法，以工程类比的思想判断岩爆的发生状态。
Experimental results show that the new algorithm for image segmentation accuracy than a single K means clustering algorithm and the ant colony clustering algorithm has greatly improved.
实验结果证明，新算法在图像分割处理的精确度上较单一的K均值和蚁群聚类算法有很大提高。
The basic ant colony clustering algorithm in the calculation of similarity, due to not take direction between adjacent objects, often caused by clustering algorithms do not even slow convergence.
基本蚁群聚类算法在计算相似度时，由于没有考虑相邻对象之间方向的影响，往往造成聚类速度缓慢甚至算法不收敛。
This paper provides a model of the clustering and an optimized ant colony-clustering algorithm which is based on the swarm intelligence and that mathematic model is provided at the same time.
该文通过对现有群体智能理论和聚类算法的研究，提出了一种基于群体智能理论的聚类模型，并在此基础上给出了一种优化蚁群聚类算法。
A new coin identification method based on ant colony algorithm with clustering characteristics is proposed in this paper.
利用蚁群算法的聚类能力，提出一种硬币识别新方法。
An optimization algorithm of RBF Neural Networks based on ant colony clustering and a pruning method is proposed.
提出了一种基于蚁群聚类算法和裁剪方法的RBF神经网络优化算法。
Then, the thesis USES ant colony algorithm which is based on the elicitation of ant's feeding to solve the clustering problem.
然后成功地将聚类问题转换成蚁群求解问题，并使用基于蚂蚁觅食启发的蚁群算法进行聚类分析。
Then, the thesis USES ant colony algorithm which is based on the elicitation of ant's feeding to solve the clustering problem.
然后成功地将聚类问题转换成蚁群求解问题，并使用基于蚂蚁觅食启发的蚁群算法进行聚类分析。
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