2021研究生数学建模B题空气质量预报二次建模求解过程：基于Stacking机器学习混合模型的空气质量预测｛含码源+pdf文章｝

import numpy as np import math import pandas as pd import matplotlib.pyplot as plt import openpyxl as op import seaborn as sns pd.set_option('display.width', 1000)#加了这一行那表格的一行就不会分段出现了 #显示所有列 pd.set_option('display.max_columns', None) #显示所有行 pd.set_option('display.max_rows', None) path = 'D:/shumo/jianmo/A2_new.xlsx' data = pd.read_excel(path,sheet_name = 0) print(type(data)) data_new = data.values print(data_new) print(type(data_new)) # print(data_new) print(data_new.shape) # print("######################") # data = np.delete(data_new,0,axis=1) # data = np.delete(data,0,axis=1) # # print(data) # print(data.shape) # print(type(data)) # print('####################') data = data_new.tolist() # print(data) print(type(data)) print(np.array(data).shape) print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") # 用于储存每行的最大AQI AQI_max_plot = [] AQI_max = ["AQI"] IQAI_so2 = ["so2"] IQAI_no2 = ["no2"] IQAI_pm10 = ["pm10"] IQAI_pm2_5 = ["pm2_5"] IQAI_o3 = ["o3"] IQAI_co = ["co"] # for row in range(0,len(data)-3): for row in range(0,len(data)): # 用于储存 每行的IAQI IAQI = [] for i in range(0,6): # 二氧化硫的IAQI计算 if i == 0: if data[row][i]<=50: IAQI_h = 50 IAQI_l = 0 BP_h = 50 BP_l = 0 IAQI_0 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l else: print("erro 0") IQAI_so2.append(IAQI_0) IAQI.append(IAQI_0) # 二氧化氮的IAQI计算 elif i == 1: if data[row][i]<=40: IAQI_h = 50 IAQI_l = 0 BP_h = 40 BP_l = 0 IAQI_1 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i]<=80: IAQI_h = 100 IAQI_l = 50 BP_h = 80 BP_l = 40 IAQI_1 = ((IAQI_h - IAQI_l) / (BP_h - BP_l)) * (data[row][i] - BP_l) + IAQI_l elif data[row][i]<=180: IAQI_h = 150 IAQI_l = 100 BP_h = 180 BP_l = 80 IAQI_1 = ((IAQI_h - IAQI_l) / (BP_h - BP_l)) * (data[row][i] - BP_l) + IAQI_l elif data[row][i] <= 280: IAQI_h = 200 IAQI_l = 150 BP_h = 280 BP_l = 180 IAQI_1 = ((IAQI_h - IAQI_l) / (BP_h - BP_l)) * (data[row][i] - BP_l) + IAQI_l else: print("erro 1") IQAI_no2.append(IAQI_1) IAQI.append(IAQI_1) #PM10 IAQI 的计算 elif i == 2: if data[row][i]<=50: IAQI_h = 50 IAQI_l = 0 BP_h = 50 BP_l = 0 IAQI_2 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i]<=150: IAQI_h = 100 IAQI_l = 50 BP_h = 150 BP_l = 50 IAQI_2 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i] <= 250: IAQI_h = 150 IAQI_l = 100 BP_h = 250 BP_l = 150 IAQI_2 = ((IAQI_h - IAQI_l) / (BP_h - BP_l)) * (data[row][i] - BP_l) + IAQI_l else: print("erro 2") IQAI_pm10.append(IAQI_2) IAQI.append(IAQI_2) # PM2.5 IAQI 的计算 elif i == 3: if data[row][i] <= 35: IAQI_h = 50 IAQI_l = 0 BP_h = 35 BP_l = 0 IAQI_3 = ((IAQI_h - IAQI_l) / (BP_h - BP_l)) * (data[row][i] - BP_l) + IAQI_l elif data[row][i] <= 75: IAQI_h = 100 IAQI_l = 50 BP_h = 75 BP_l = 35 IAQI_3 = ((IAQI_h - IAQI_l) / (BP_h - BP_l)) * (data[row][i] - BP_l) + IAQI_l elif data[row][i] <= 115: IAQI_h = 150 IAQI_l = 100 BP_h = 115 BP_l = 75 IAQI_3 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i] <= 150: IAQI_h = 200 IAQI_l = 150 BP_h = 150 BP_l = 115 IAQI_3 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i] <= 250: IAQI_h = 300 IAQI_l = 200 BP_h = 250 BP_l =150 IAQI_3 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i] <= 350: IAQI_h = 400 IAQI_l = 300 BP_h = 350 BP_l =250 IAQI_3 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i] <= 500: IAQI_h = 500 IAQI_l = 400 BP_h = 500 BP_l =350 IAQI_3 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l else: print("erro 3") IQAI_pm2_5.append(IAQI_3) IAQI.append(IAQI_3) # 臭氧 IAQI的计算 elif i ==4: if data[row][i]<=100: IAQI_h = 50 IAQI_l = 0 BP_h = 100 BP_l = 0 IAQI_4 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i]<=160: IAQI_h = 100 IAQI_l = 50 BP_h = 160 BP_l = 100 IAQI_4 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i]<=215: IAQI_h = 150 IAQI_l = 100 BP_h = 215 BP_l = 160 IAQI_4 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i] <= 265: IAQI_h = 200 IAQI_l = 150 BP_h = 265 BP_l = 215 IAQI_4 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i] <= 800: IAQI_h = 300 IAQI_l = 200 BP_h = 800 BP_l = 265 IAQI_4 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l else: print("erro 4") IQAI_o3.append(IAQI_4) IAQI.append(IAQI_4) # 一氧化碳 IAQI 的计算 else: if data[row][i] <=2: IAQI_h = 50 IAQI_l = 0 BP_h = 2 BP_l = 0 IAQI_5 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l elif data[row][i]<=4: IAQI_h = 100 IAQI_l = 50 BP_h = 4 BP_l = 2 IAQI_5 = ((IAQI_h -IAQI_l)/(BP_h-BP_l))*(data[row][i]-BP_l)+IAQI_l else: print("erro 5") # IQAI_co.append(IAQI_5) IAQI.append(IAQI_5) # print(IAQI) # 取最大的IAQI IAQI_max = (max(IAQI)) IAQI_max = math.ceil(IAQI_max) AQI_max.append(IAQI_max) AQI_max_plot.append(IAQI_max) print(AQI_max ,end = '') #将获得的AQI列表写入原excel表格 def write(list): bg = op.load_workbook(r"A3_new.xlsx") # 应先将excel文件放入到工作目录下 sheet = bg["1"] # “Sheet1”表示将数据写入到excel文件的sheet1下 for i in range(1, len(list) + 1): sheet.cell(i,16, list[i - 1])# sheet.cell(1,1,num_list[0])表示将num_list列表的第0个数据1写入到excel表格的第一行第一列 bg.save("A3_new.xlsx") # 对文件�