FDP聚类算法

利用一维卷积神经网络将叶子进行分类，里面包含的有数据(Classification of leaves using one dimensional convolution neural network)

利用python进行数据分析，英文书籍，从pandas库的数据分析工具开始利用高性能工具对数据进行加载、清理、转换、合并以及重塑；利用matpIotlib创建散点图以及静态或交互式的可视化结果；利用pandas的groupby功能对数据集进行切片、切块和汇总操作；处理各种各样的时间序列数据。(Starting from the data analysis tools of pandas database, high performance tools are used to load, clean, transform, merge and remodel data; scatter plots and static or interactive visualization results are created by matpIotlib; data sets are sliced, sliced and aggregated by pandas group by function; and various operations are processed. Time series data.)

bp网络实现认知无线电的检测和预测,从而达到了对频谱的分配(Bp network realizes the detection and prediction of cognitive radio, thus achieving the spectrum allocation.)

强大的计算电磁场本征函数与本征模的程序,matlab版本(A powerful Program for calculating the Eigenfunction and Eigenmode of electromagnetic Field)

说明：  实现了无监督AP聚类 其优势在于不用知道聚类个数(The advantage of unsupervised AP clustering is that the number of clusters is not known)

说明：  用matlab 实现了kmeans算法还附有评价指标计算(Matlab to achieve kmeans algorithm also attached to the evaluation index calculation)

三次样条插值的C语言算法,但是总是数据溢出()

用matlab 实现了kmeans算法还附有评价指标计算(Matlab to achieve kmeans algorithm also attached to the evaluation index calculation)

从数据库获取车辆在一段时间内的所有行驶记录的相关数据，确定所需数据为GPS经纬度坐标和驾驶时长等，QB模型采用MDF的思想,其基本思想为:通过平均直接翻转距离函数定义两条轨迹之间的距离，两条轨迹需要具有相同的经纬度点数，具有相同点数的轨迹最大的优点是对轨迹距离成对计算，且相同轨迹之间具有更高的分辨率，对于轨迹聚类的结果有一定的优化。(Retrieved from the database cars all over a period of time, record the related data, determine the required data for the GPS latitude and longitude coordinates, and the driving time, QB model by adopting the idea of MDF, its basic idea is: flip directly by the average distance function definition of the distance between two trajectories, two tracks will have the same latitude and longitude points, and has the biggest advantages of the same points of trajectory track distance calculation in pairs, and has higher resolution, between the same trajectory for trajectory clustering results have certain optimization.)

包含很多知名算法实现，支持向量机，决策树，粗糙集，贝叶斯分类器等，适合学术研究，短评论意见挖掘，文本分类等。