# 问题一：随机森林回归from sklearn.ensemble import RandomForestRegressormodel_rf = RandomForestRegressor()model_rf.fit(X_train, y_train)# 问题二：LSTM时间序列预测from tensorflow.keras.models import Sequentialmodel_lstm = Sequential()model_lstm.add(LSTM(50, input_shape=(window_size, n_features)))model_lstm.add(Dense(60 * 2)) # 预测60步，每步两个浓度# 问题三：时间点预测def predict_event_time(predictions, k1, k2): for i, (so2, h2s) in enumerate(predictions): if so2 > k1 or h2s > k2: return i + 10 # t+10为起始点 return None
2025年第十八届"认证杯"数学中国数学建模网络挑战赛B题完整word论文+代码+结果
https://download.csdn.net/download/qq_52590045/905927492025年第十八届"认证杯"数学中国数学建模网络挑战赛C题完整word论文+代码+结果https://download.csdn.net/download/qq_52590045/90592761
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