fuzzy clustering algorithm meaning in Chinese
模糊簇聚算法
Examples
- An objective function was introduced to determine the structure of fuzzy models . at last , we present a specific fuzzy modeling method based on modified fuzzy clustering algorithm combined with least - square estimator and l - m optimize algorithm
根据模糊建模的实际需要，提出了一种改进的模糊聚类算法，并结合最小二乘和l - m优化算法，给出了模糊建模的具体实现方法。 - Use the hierachical fuzzy clustering algorithm to cluster the similar customers and solve the problems of validity of clustering results and how to get the best clusters . get the customer group requirement tendency model that belongs to the vision of customers . provide the necessary data preparation for the transformation of customer requirements to engineering parameters and indexes
研究了大规模定制的市场细分过程：应用matlab语言实现的层次模糊聚类分析算法将相似需求的客户聚成一类，极大的简化了算法的实现复杂度，解决了聚类结果的有效性评估和最佳分类的确定问题，获得属于客户视角的客户群体需求倾向模型，达到细分市场的目的，并为进一步将客户需求转化为工程意义的技术参数或指标提供了必要的数据准备。 - The following is what i have done in this paper : 1 . the paper systematically summed up the fundamental knowledge of fuzzy set theory , and introduced fuzzy clustering algorithms in detail , and analyzed the defects of low convergence speed and sensitivity to the initialization of fuzzy clustering algorithms , and proposed a modified fuzzy clustering algorithm based on ga
对模糊理论的基本内容进行了系统的总结和介绍，并详细介绍了模糊聚类算法，分析了模糊聚类算法收敛速度慢且对初始化很敏感的原因，引入了遗传算法，提出了一种改进的模糊聚类算法。 - 2 . according to distribution characteristic of recipes , a recipe fuzzy cluster algorithm based on kernel - function was presented . firstly one recipe kernel - function was defined to represent recipe class , through minimizing all the distance of recipe samples to recipe class kernel , recipe samples were classed . the class number was gave out and each recipe was gave membership degrees belong to each classes
2 、根据配方的模式分布特点，提出了一种基于类核函数的配方模糊聚类算法，定义一个配方类核函数来代表配方类，通过最小化所有配方样本到配方类核距离加权和来对配方进行聚类，得到聚类数目及模糊隶属度矩阵。 - How to apply the cluster analysis method to solve the cluster of samples is narrated in details : firstly , the ordinary cluster methods and the simply analysis of the intricacy of these methods is introduced , then our rapid fuzzy cluster algorithm is particularly narrated and the experiment data are provided , at last , how we realize the automatic extraction of information form the crops " texts is introduced
在文章的主体部分讲述了如何应用聚类分析的方法解决样本的归类问题：首先介绍了常用聚类方法，并对它们的复杂度进行了简要分析。然后详细介绍了我们提出快速模糊聚类算法，并给出了实验数据。文章最后介绍在农作< wp = 4 >物信息文本中实现信息自动提取的思路。