首页> 外国专利> APPARATUS FOR SELECTING METHOD OF TRAINING SEA FOG DISSIPATION PREDICTION MODEL, METHOD FOR SELECTING METHOD OF TRAINING SEA FOG DISSIPATION PREDICTION MODEL, SEA FOG DISSIPATION PREDICTION APPARATUS, AND SEA FOG DISSIPATION PREDICTION METHOD

APPARATUS FOR SELECTING METHOD OF TRAINING SEA FOG DISSIPATION PREDICTION MODEL, METHOD FOR SELECTING METHOD OF TRAINING SEA FOG DISSIPATION PREDICTION MODEL, SEA FOG DISSIPATION PREDICTION APPARATUS, AND SEA FOG DISSIPATION PREDICTION METHOD

机译:海雾消散预测模型的选择方法的装置,海雾消散预测模型的选择方法的方法,海雾消散的预测方法和海雾消散的预测方法

摘要

Provided is an apparatus for selecting a method of training a sea fog dissipation prediction model, capable of training the sea fog dissipation prediction model by each of N learning methods. According to one embodiment of the present invention, the apparatus for selecting a method of training a sea fog dissipation prediction model includes: a memory including at least one instruction; and at least one processor operatively connected to the memory, wherein, when the at least one instruction is executed by the at least one processor, the at least one processor is configured to: acquire various types of sea fog-related observation data; select at least two types of sea fog-related observation data among the acquired various types of sea fog-related observation data by using a first criterion; generate an input data set based on the selected at least two types of sea fog-related observation data; train the sea fog dissipation prediction model by each of N learning methods based on the generated input data set; evaluate the sea fog dissipation prediction model trained by each of the N learning methods by using a second criterion; and select at least two different learning methods according to an evaluation result.;COPYRIGHT KIPO 2020
机译:提供一种用于选择训练海雾消散预测模型的方法的设备,其能够通过N种学习方法中的每一种来训练海雾消散预测模型。根据本发明的一个实施例,一种用于选择训练海雾消散预测模型的方法的设备包括:存储器,其包括至少一个指令;以及至少一个处理器,可操作地连接到所述存储器,其中,当所述至少一个处理器执行所述至少一个指令时,所述至少一个处理器被配置为:获取各种类型的与海雾有关的观测数据;以及通过第一准则,在获取的各种类型的海雾相关观测数据中选择至少两种类型的海雾相关观测数据;根据所选的至少两种类型的与海雾有关的观测数据,生成输入数据集;根据生成的输入数据集,通过N种学习方法分别训练海雾消散预测模型;使用第二个标准评估由N种学习方法中的每一种训练的海雾消散预测模型;并根据评估结果选择至少两种不同的学习方法。COPYRIGHT KIPO 2020

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