SOIL TEMPERATURE PREDICTION USING CONVOLUTIONAL NEURAL NETWORK BASED ON ENSEMBLE EMPIRICAL MODE DECOMPOSITION

Soil Temperature Prediction Using Convolutional Neural Network Based on Ensemble Empirical Mode Decomposition

Soil temperature plays an important role in agriculture, industry and other fields.Accurate soil temperature prediction can help improve productivity and avoid risks in many fields.At present, many machine learning methods have been applied to soil temperature prediction such as support vector regression (SVR), artificial neural network (ANN), long

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Apolipoprotein A-I Milano: sex-related differences in the concentration and composition of apoA-I- and apoB-containing lipoprotein particles.

The presence of apolipoprotein (apo) A-IMilano (A-IM) mutant of apoA-I has a marked effect on plasma lipoproteins of A-IM carriers including variable hypertriglyceridemia, increased levels of very low density lipoproteins (VLDL), slightly elevated levels of triglyceride-enriched low density lipoproteins (LDL) and greatly reduced levels of high dens

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