- \n
- \u65e0\u8bb0\u5fc6\u6027：\u4e0b\u4e00\u6b65\u7684\u72b6\u6001\u53ea\u4f9d\u8d56\u5f53\u524d\u72b6\u6001，\u4e0e\u66f4\u65e9\u72b6\u6001\u65e0\u5173\u3002<\/li>\n
- \u72b6\u6001\u7a7a\u95f4：\u7cfb\u7edf\u6240\u6709\u53ef\u80fd\u7684\u72b6\u6001\u6784\u6210\u7684\u96c6\u5408\u3002<\/li>\n
- \u8f6c\u79fb\u6982\u7387：\u4ece\u4e00\u4e2a\u72b6\u6001\u8f6c\u79fb\u5230\u53e6\u4e00\u4e2a\u72b6\u6001\u7684\u6982\u7387，\u6240\u6709\u4ece\u4e00\u4e2a\u72b6\u6001\u51fa\u53d1\u7684\u8f6c\u79fb\u6982\u7387\u4e4b\u548c\u4e3a1.<\/li>\n<\/ul>\n
3.\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\u5efa\u6a21\u6b65\u9aa4：（\u4ee5\u5929\u6c14\u9884\u62a5\u4e3a\u4f8b)<\/h4>\n
- \n
- \u5b9a\u4e49\u72b6\u6001\u7a7a\u95f4：\u5217\u51fa\u6240\u6709\u53ef\u80fd\u7684\u72b6\u6001，\u6bd4\u5982S1=\u3010\u2018\u6674\u2019，\u2018\u96e8\u2019\u3011<\/li>\n
- \u51c6\u5907\u5386\u53f2\u6570\u636e：\u51c6\u5907\u4e00\u4e32\u5df2\u77e5\u7684\u5929\u6c14\u5e8f\u5217，\u6bd4\u5982\u00a0['\u6674','\u6674','\u96e8','\u96e8','\u6674','\u96e8']<\/li>\n
- \u7edf\u8ba1\u8f6c\u79fb\u6b21\u6570：\u904d\u5386\u6574\u4e2a\u5e8f\u5217，\u7edf\u8ba1\u4ece\u4e00\u79cd\u72b6\u6001\u8f6c\u79fb\u5230\u53e6\u4e00\u79cd\u72b6\u6001\u7684\u6b21\u6570，\u6784\u9020\u8f6c\u79fb\u9891\u6570\u77e9\u9635<\/li>\n
- \u8ba1\u7b97\u8f6c\u79fb\u6982\u7387：\u628a\u8f6c\u79fb\u9891\u6570\u77e9\u9635\u7684\u6bcf\u4e00\u884c\u9664\u4ee5\u6bcf\u4e00\u884c\u7684\u603b\u548c，\u5f97\u5230\u8f6c\u79fb\u6982\u7387\u77e9\u9635<\/li>\n
- \u9884\u6d4b\u672a\u6765：\u7528\u5f53\u524d\u7684\u72b6\u6001\u4f5c\u4e3a\u521d\u59cb\u77e9\u9635，\u7528\u8f6c\u79fb\u6982\u7387\u77e9\u9635\u9884\u6d4b\u660e\u5929\u53ef\u80fd\u7684\u5929\u6c14，\u82e5\u8981\u9884\u6d4b\u591a\u6b21，\u9700\u8981\u7528\u77e9\u9635\u4e58\u6cd5\u5faa\u73af\u8fed\u4ee3<\/li>\n<\/ul>\n
4.\u5929\u6c14\u9884\u62a5\u7684\u4f8b\u5b50：<\/h4>\n
- \u5b9a\u4e49\u72b6\u6001\u3001\u51c6\u5907\u5386\u53f2\u6570\u636e\u3001\u8fd4\u56de\u8f6c\u79fb\u6982\u7387<\/li>\n
S1 = ['\u6674','\u96e8']
\npossibility = ['\u6674','\u6674','\u96e8','\u96e8','\u6674','\u96e8']<\/p>\ndef calculate(lst):
\n\u00a0 \u00a0 p11 = 0
\n\u00a0 \u00a0 p12 = 0
\n\u00a0 \u00a0 p21 = 0
\n\u00a0 \u00a0 p22 = 0
\n\u00a0 \u00a0 for i in range(len(lst)-1):
\n\u00a0 \u00a0 \u00a0 \u00a0 if lst[i] == '\u6674':
\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 if lst[i+1] == '\u6674':
\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 p11 += 1
\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 else:
\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 p12 += 1
\n\u00a0 \u00a0 \u00a0 \u00a0 else:
\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 if lst[i+1] == '\u6674':
\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 p21 += 1
\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 else:
\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 p22 += 1
\n\u00a0 \u00a0 return p11,p12,p21,p22
\np11,p12,p21,p22 = calculate(possibility)
\nP11,P12,P21,P22 = p11 \/ (p11+p12),p12\/(p11+p12),p21\/(p21+p22),p22\/(p21+p22)
\nP11,P12,P21,P22<\/p>\n\u00a0 \u00a0 \u00a0 \u00a0 2.\u6784\u9020\u8f6c\u79fb\u6982\u7387\u77e9\u9635\u3001\u9884\u6d4b\u672a\u6765\u4e00\u5929\u7684\u5929\u6c14\u60c5\u51b5<\/p>\n
import numpy as np
\nmatrix = np.array([[P11,P12],[P21,P22]])
\nini = [1,0] \u00a0 \u00a0 #\u521d\u59cb\u72b6\u6001
\nresult = np.dot(ini,matrix)
\nprint('\u660e\u5929\u6709{:.2f}\u6982\u7387\u6674\u5929,\u6709{:.2f}\u6982\u7387\u96e8\u5929'.format(result[0],result[1]))<\/p>\n\u660e\u5929\u67090.33\u6982\u7387\u6674\u5929,\u67090.67\u6982\u7387\u96e8\u5929<\/p>\n
\u00a0 \u00a0 \u00a0 \u00a0 3.\u9884\u6d4b\u672a\u6765\u4e94\u5929\u7684\u5929\u6c14\u60c5\u51b5<\/p>\n
def pre(days,matrix):
\n\u00a0 \u00a0 current = ini \u00a0 \u00a0 #\u5f53\u524d\u72b6\u6001
\n\u00a0 \u00a0 result1 = []
\n\u00a0 \u00a0 for i in range(days):
\n\u00a0 \u00a0 \u00a0 \u00a0current = np.dot(current,matrix)
\n\u00a0 \u00a0 \u00a0 \u00a0result1.append(current.copy())
\n\u00a0 \u00a0 return result1
\npredictions = pre(5,matrix)
\nprint('\u672a\u6765\u4e94\u5929\u5929\u6c14\u9884\u62a5')
\nfor i in range(5):
\n\u00a0 \u00a0 print('\u7b2c{}\u5929{:.2f}\u6982\u7387\u6674\u5929,\u6709{:.2f}\u6982\u7387\u96e8\u5929'.format(i+1,predictions[i][0],predictions[i][1]))
\n\u00a0 \u00a0\u00a0<\/p>\n\u672a\u6765\u4e94\u5929\u5929\u6c14\u9884\u62a5
\n\u7b2c1\u59290.33\u6982\u7387\u6674\u5929,\u67090.67\u6982\u7387\u96e8\u5929
\n\u7b2c2\u59290.44\u6982\u7387\u6674\u5929,\u67090.56\u6982\u7387\u96e8\u5929
\n\u7b2c3\u59290.43\u6982\u7387\u6674\u5929,\u67090.57\u6982\u7387\u96e8\u5929
\n\u7b2c4\u59290.43\u6982\u7387\u6674\u5929,\u67090.57\u6982\u7387\u96e8\u5929
\n\u7b2c5\u59290.43\u6982\u7387\u6674\u5929,\u67090.57\u6982\u7387\u96e8\u5929<\/p>\n\u00a0 \u00a0 \u00a0 \u00a0 4.\u5c06\u7ed3\u679c\u53ef\u89c6\u5316，\u76f4\u89c2\u5206\u6790<\/p>\n
import matplotlib.pyplot as plt
\nimport matplotlib.pyplot as plt
\nimport numpy as np<\/p>\nimport warnings
\nwarnings.filterwarnings('ignore') \u00a0 \u00a0 \u00a0#\u5ffd\u7565\u8fd0\u884c\u65f6\u8b66\u544a\u4fe1\u606f<\/p>\nplt.rcParams['axes.unicode_minus'] = False \u00a0 \u00a0 \u00a0#\u4fee\u590d\u8d1f\u53f7\u663e\u793a
\nplt.rcParams['font.sans-serif'] = ['SimHei'] \u00a0<\/p>\n# \u539f\u59cb\u6570\u636e
\ndays_orig = np.arange(1, len(possibility) + 1)
\ny_orig = [0 if w == '\u6674' else 1 for w in possibility] \u00a0 # \u6674=0, \u96e8=1<\/p>\n# \u9884\u6d4b\u6570\u636e
\npredictions = pre(5, matrix)
\npred_\u6674\u5929 = [p[0] for p in predictions] \u00a0 \u00a0# \u6bcf\u5929\u6674\u5929\u7684\u6982\u7387
\npred_\u96e8\u5929 = [p[1] for p in predictions] \u00a0 \u00a0# \u6bcf\u5929\u96e8\u5929\u7684\u6982\u7387
\ndays_pred = np.arange(len(possibility) + 1, len(possibility) + 6)<\/p>\n\nplt.figure(figsize=(10, 5))
\nplt.scatter(days_orig, y_orig, color='blue', label='\u539f\u59cb\u5929\u6c14(0=\u6674,1=\u96e8)', s=50, zorder=5) \u00a0 \u00a0#zorder\u56fe\u5c42\u663e\u793a
\nplt.plot(days_pred, pred_\u6674\u5929, 'o–', color='orange', label='\u9884\u6d4b\u6982\u7387(\u6674\u5929)', alpha=0.8)
\nplt.plot(days_pred, pred_\u96e8\u5929, 's–', color='green', label='\u9884\u6d4b\u6982\u7387(\u96e8\u5929)', alpha=0.8)<\/p>\nplt.title('\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\u5929\u6c14\u9884\u6d4b')
\nplt.xlabel('\u5929\u6570')
\nplt.ylabel('\u6982\u7387 \/ \u5929\u6c14\u72b6\u6001')
\nplt.xticks(range(1, len(possibility) + 6))
\nplt.legend()
\nplt.grid(True, alpha=0.3)
\nplt.show()<\/p>\n![](\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260808120846-6a771c4ede932.png\")
<\/p>\n\u4ece\u56fe\u7247\u53ef\u4ee5\u770b\u51fa，\u672a\u6765\u51e0\u5929\u662f\u96e8\u5929\u7684\u6982\u7387\u8f83\u5927\u3002\u540c\u65f6，\u53ef\u4ee5\u770b\u5230，\u4ece\u7b2c8\u5929\u5f00\u59cb，\u9884\u6d4b\u6982\u7387\u8d8b\u4e8e\u7a33\u5b9a\u3002<\/p>\n
5.\u5b8c\u6574\u4ee3\u7801：<\/h4>\n
S1 = ['\u6674','\u96e8']
\npossibility = ['\u6674','\u6674','\u96e8','\u96e8','\u6674','\u96e8']<\/p>\ndef calculate(lst):
\n p11 = 0
\n p12 = 0
\n p21 = 0
\n p22 = 0
\n for i in range(len(lst)-1):
\n if lst[i] == '\u6674':
\n if lst[i+1] == '\u6674':
\n p11 += 1
\n else:
\n p12 += 1
\n else:
\n if lst[i+1] == '\u6674':
\n p21 += 1
\n else:
\n p22 += 1
\n return p11,p12,p21,p22
\np11,p12,p21,p22 = calculate(possibility)
\nP11,P12,P21,P22 = p11 \/ (p11+p12),p12\/(p11+p12),p21\/(p21+p22),p22\/(p21+p22)<\/p>\nimport numpy as np
\nmatrix = np.array([[P11,P12],[P21,P22]])
\nini = [1,0] #\u521d\u59cb\u72b6\u6001
\nresult = np.dot(ini,matrix)
\nprint('\u660e\u5929\u6709{:.2f}\u6982\u7387\u6674\u5929,\u6709{:.2f}\u6982\u7387\u96e8\u5929'.format(result[0],result[1]))<\/p>\ndef pre(days,matrix):
\n current = ini #\u5f53\u524d\u72b6\u6001
\n result1 = []
\n for i in range(days):
\n current = np.dot(current,matrix)
\n result1.append(current.copy())
\n return result1
\npredictions = pre(5,matrix)
\nprint('\u672a\u6765\u4e94\u5929\u5929\u6c14\u9884\u62a5')
\nfor i in range(5):
\n print('\u7b2c{}\u5929{:.2f}\u6982\u7387\u6674\u5929,\u6709{:.2f}\u6982\u7387\u96e8\u5929'.format(i+1,predictions[i][0],predictions[i][1]))<\/p>\nimport matplotlib.pyplot as plt
\nimport matplotlib.pyplot as plt
\nimport numpy as np<\/p>\nimport warnings
\nwarnings.filterwarnings('ignore') #\u5ffd\u7565\u8fd0\u884c\u65f6\u8b66\u544a\u4fe1\u606f<\/p>\nplt.rcParams['axes.unicode_minus'] = False #\u4fee\u590d\u8d1f\u53f7\u663e\u793a
\nplt.rcParams['font.sans-serif'] = ['SimHei'] <\/p>\n# \u539f\u59cb\u6570\u636e
\ndays_orig = np.arange(1, len(possibility) + 1)
\ny_orig = [0 if w == '\u6674' else 1 for w in possibility] # \u6674=0, \u96e8=1<\/p>\n# \u9884\u6d4b\u6570\u636e
\npredictions = pre(5, matrix)
\npred_\u6674\u5929 = [p[0] for p in predictions] # \u6bcf\u5929\u6674\u5929\u7684\u6982\u7387
\npred_\u96e8\u5929 = [p[1] for p in predictions] # \u6bcf\u5929\u96e8\u5929\u7684\u6982\u7387
\ndays_pred = np.arange(len(possibility) + 1, len(possibility) + 6)<\/p>\n# \u753b\u56fe
\nplt.figure(figsize=(10, 5))<\/p>\n# \u539f\u59cb\u5929\u6c14\u7528\u6563\u70b9
\nplt.scatter(days_orig, y_orig, color='blue', label='\u539f\u59cb\u5929\u6c14(0=\u6674,1=\u96e8)', s=50, zorder=5) #zorder\u56fe\u5c42\u663e\u793a<\/p>\n# \u9884\u6d4b\u6982\u7387\u7528\u4e24\u6761\u6298\u7ebf
\nplt.plot(days_pred, pred_\u6674\u5929, 'o–', color='orange', label='\u9884\u6d4b\u6982\u7387(\u6674\u5929)', alpha=0.8)
\nplt.plot(days_pred, pred_\u96e8\u5929, 's–', color='green', label='\u9884\u6d4b\u6982\u7387(\u96e8\u5929)', alpha=0.8)<\/p>\nplt.title('\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\u5929\u6c14\u9884\u6d4b')
\nplt.xlabel('\u5929\u6570')
\nplt.ylabel('\u6982\u7387 \/ \u5929\u6c14\u72b6\u6001')
\nplt.xticks(range(1, len(possibility) + 6))
\nplt.legend()
\nplt.grid(True, alpha=0.3)
\nplt.show()<\/p>\n\u00a0<\/p>\n
6.\u603b\u7ed3：<\/h4>\n
\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\u7528\u4e8e\u201c\u4e0b\u4e00\u6b65\u53ea\u4e0e\u5f53\u524d\u6709\u5173\u201d\u7684\u573a\u666f，\u5982\u5929\u6c14\u9884\u62a5\u3001\u80a1\u7968\u9884\u6d4b\u3001\u81ea\u7136\u8bed\u8a00\u5904\u7406\u3002\u4f18\u70b9\u662f\u6a21\u578b\u7b80\u5355\u3001\u6613\u4e8e\u7406\u89e3，\u5c40\u9650\u6027\u662f\u4ec5\u4f9d\u8d56\u5f53\u524d\u72b6\u6001，\u53ef\u80fd\u65e0\u6cd5\u6355\u6349\u66f4\u957f\u671f\u7684\u5386\u53f2\u89c4\u5f8b\u3002<\/p>\n
\u8be5\u5929\u6c14\u9884\u62a5\u4f8b\u5b50，\u72b6\u6001\u7a7a\u95f4\u60c5\u51b5\u5c11\u3001\u5386\u53f2\u6570\u636e\u6709\u9650，\u76f8\u5bf9\u7b80\u5355，\u5bf9\u4e8e\u5927\u6570\u636e\u96c6，\u9700\u8981\u66f4\u591a\u7684\u5904\u7406\u3002<\/p>\n
\u00a0<\/p>\n
\u00a0<\/p>\n
\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"
1.\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\u662f\u4ec0\u4e48？\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\u662f\u4e00\u79cd\u7528\u4e8e\u63cf\u8ff0\u7cfb\u7edf\u72b6\u6001\u968f\u65f6\u95f4\u53d8\u5316\u7684\u6570\u5b66\u6a21\u578b，\u5b83\u7684\u6838\u5fc3\u662f，\u672a\u6765\u53ea\u4e0e\u73b0\u5728\u6709\u5173，\u4e0e\u8fc7\u53bb\u65e0\u5173\u30022.\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\u7684\u7279\u5f81？\u65e0\u8bb0\u5fc6\u6027：\u4e0b\u4e00\u6b65\u7684\u72b6\u6001\u53ea\u4f9d\u8d56\u5f53\u524d\u72b6\u6001，\u4e0e\u66f4\u65e9\u72b6\u6001\u65e0\u5173\u3002\u72b6\u6001\u7a7a\u95f4：\u7cfb\u7edf\u6240\u6709\u53ef\u80fd\u7684\u72b6\u6001\u6784\u6210\u7684\u96c6\u5408\u3002\u8f6c\u79fb\u6982\u7387：\u4ece\u4e00\u4e2a\u72b6\u6001\u8f6c\u79fb\u5230\u53e6\u4e00\u4e2a\u72b6\u6001\u7684\u6982\u7387，\u6240\u6709\u4ece\u4e00\u4e2a\u72b6\u6001\u51fa\u53d1\u7684\u8f6c\u79fb\u6982\u7387\u4e4b\u548c\u4e3a1.3.\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\u5efa<\/p>\n","protected":false},"author":2,"featured_media":91938,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[50,1482,427],"topic":[],"class_list":["post-91939","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server","tag-50","tag-1482","tag-427"],"yoast_head":"\n
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