机器学习在滑坡的易发性评价中面临两个难点, 一是评价指标的客观量化, 二是训练样本的选择.
鉴于此, 采用频率比法实现了评价指标的客观量化, 利用k 均值聚类算法实现了非滑坡样本数据 …

Recommender systems suggest items to users based on their potential interests, and they
are important to alleviate the search and selection pressures induced by the increasing item …

The classification favors seriously to the most kinds when we use the traditional sorter to
classify the imbalanced data set. In order to effectively enhance classified performance of …

Among the typical clustering methods, the K-means algorithm plays the most important role
in clustering because of its simplicity and efficiency. However, it is sensitive to the initial …

Because the K-Means algorithm is easy to fall into the local optimum and the Cuckoo search
(CS) algorithm is affected by the step size, this paper proposes a K-Means clustering …

A new clustering method, RVPSO-K was proposed in this paper based on the random
research combining K-means and PSO according to the character of the clustering of Web …

摘要针对背景差法易受外界环境因素影响的缺点, 提出了一种基于改进K-均值聚类的背景建模
方法. 通过比较任意样本与该像素位置处的子类中心之间的距离, 对各个像素的观察值进行聚类 …

将农村温室气体排放途径划分为农业生产, 畜牧养殖, 垃圾污水处理和能源消耗4 类, 基于《
省级温室气体排放清单指南》 和IPCC 碳排放清单编制方法提出各途径温室气体排放量计算方法 …

根据2002, 2004, 2008, 2010, 2012 和2016 年白令海陆坡海域底层拖网的资源调查数据,
探讨了白令海大陆坡头足类优势种及其空间分布与环境因子的关系, 分析了白令海陆坡头足类的 …

Medical data analysis is an important part of intelligent medicine, and clustering analysis is a
commonly used method for data analysis of Traditional Chinese Medicine (TCM); however …