2024年第五届“华数杯”全国大学生数学建模竞赛 A题详细思路+详细matlab代码+优秀论文范例_2024华数杯a题

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2024年第五届“华数杯”专栏地址：https://blog.csdn.net/m0_52343631/chttps://blog.csdn.net/m0_52343631/c

目录

2024年第五届“华数杯”专栏地址：https://blog.csdn.net/m0_52343631/category_12482955.html?spm=1001.2014.3001.5482

摘要

1 问题重述

2 问题分析

3 模型假设

4 主要符号说明

5.模型建立与求解

六、总结

参考文献

附录

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2021年优秀论文

摘要

1 问题重述

2 问题分析

3 模型假设

4 主要符号说明

5.模型建立与求解

六、总结

参考文献

附录

from numpy import *
import pandas as pd
import xlrd
import matplotlib.pyplot as plt
def loadDataSet(fileName):
 dataMat = [ ]
 fr = xlrd.open_workbook(fileName)
 sheet = fr.sheets()[0]
 cols = sheet.ncols
 for i in range(cols):
 #curLine = line.strip().split('\t')
 fltcol = list(sheet.col_values(i))
 '''
 if i <= 3:
 print(fltcol)
 '''
 
 dataMat.append(fltcol)
 return dataMat
def distEclud(vecA, vecB):
 return sqrt(sum(power(vecA-vecB, 2)))
def randCent(dataSet,k):
 n = shape(dataSet)[1]
 centroids = mat(zeros((k,n)))
 for j in range (n):
 minJ = min(dataSet[:,j])
 rangeJ = float(max(dataSet[:,j]) - minJ)
 centroids[:,j] = minJ + rangeJ * random.rand(k, 1)
 return centroids
def kMeans(dataSet, k, distMeas=distEclud, createCent=randCent):
 m = shape(dataSet)[0]
 clusterAssment = mat(zeros((m,2)))
 centroids = createCent(dataSet, k)
 clusterChanged = True
 while clusterChanged:
 clusterChanged = False
for i in range(m):
 minDist = inf; minIndex = -1
 for j in range(k):
 distJI = distMeas(centroids[j,:],dataSet[i,:])
 if distJI < minDist:
 minDist = distJI; minIndex = j
 if clusterAssment[i,0] != minIndex: clusterChanged = True
 clusterAssment[i,:] = minIndex,minDist**2
 #print(centroids)
 for cent in range(k):
 ptsInClust = dataSet[nonzero(clusterAssment[:,0].A==cent)[0]]
 if len(ptsInClust)!= 0:
 centroids[cent,:] = mean(ptsInClust, axis=0)
 
 #centroids[cent,:] = mean(ptsInClust, axis=0)
 return centroids, clusterAssment
'''
def kMeans(dataset, tezhengshu, jisuan_distance = distEclud, readdata = randCent):
 dataset_lie_shu=shape(dataset)[1]
 dataset_hang_shu=shape(dataset)[0]
 
 tongji_juzhen=array(ones([dataset_hang_shu,2]))
 #ll=numpy.ones([dataset_hang_shu, 1])
 #print(type(ll))
 #print_date(dataset,numpy.array(numpy.ones([dataset_hang_shu,1])).flatten())
 creat_random_juzhen= creat_cluter (dataset,dataset_lie_shu,4)
 clu_change=True
 lun_index=1
 while clu_change:
 clu_change=False
 for i in range(dataset_hang_shu):
 juli_juzhen=[(jisuan_distance(creat_random_juzhen[j,:],dataset[i,:])) for j in range(4)]
 zhi_min_juli_juzhen=min(juli_juzhen)
 index_min_juli_juzhen=juli_juzhen.index(zhi_min_juli_juzhen)
 if tongji_juzhen[i,0] != index_min_juli_juzhen:
 clu_change=True
 tongji_juzhen[i,:]=index_min_juli_juzhen,zhi_min_juli_juzhen
 for i in range(4):
 belong_juzhen=nonzero(tongji_juzhen[:,0] == i)[0]
#print(belong_juzhen)
 belong_dataset=dataset[belong_juzhen]
 if len(belong_juzhen) != 0:
 creat_random_juzhen[i,]=mean(belong_dataset,axis=0)
 print("第%d 轮第%d 个簇点改变："%(lun_index,i))
 print(creat_random_juzhen)
 lun_index+=1
 return creat_random_juzhen,tongji_juzhen
def creat_cluter(dataset,dataset_lie_shu,tezhengshu):
 temp_cluter=array(zeros([tezhengshu,dataset_lie_shu]))
 for i in range(dataset_lie_shu):
 min_lie=min(dataset[:,i])
 max_lie=max(dataset[:,i])
 kuadu_lie=max_lie-min_lie
 ran_lie=kuadu_lie*(random.rand())+min_lie
 temp_cluter[:,i]=ran_lie
 return array(temp_cluter)
'''
#########################################################
def dist(vec1, vec2):
 return sqrt(sum(square(vec1 - vec2)))
def main():
 datMat = mat(loadDataSet('shuju_nom.xlsx'))
 myCentriods, clustAssing = kMeans(datMat, 30)
 print(myCentriods)
 #print(clustAssing)
 index = 0
 dis = []
 for i in clustAssing[:,0]:
 dis.append(dist(array(datMat[index]), myCentriods[int(i)].view()))
 print(dist(array(datMat[index]), myCentriods[int(i)].view()))
 data1 = pd.DataFrame(myCentriods.T)
 data2 = pd.DataFrame(clustAssing[:,0].T)
 data3 = pd.DataFrame(array(dis).T)
 
 writer = pd.ExcelWriter('output.xlsx')
 data1.to_excel(writer, 'page_1', float_format='%.5f')
data2.to_excel(writer, 'page_2', float_format='%d')
 data3.to_excel(writer, 'page_3', float_format='%.5f')
 writer.save()
 writer.close()
if __name__ == '__main__':
 main()