Artificial neural network training method, cooking taste optimization method, computer readable storage medium and cooking equipment

Abstract

The invention provides a cooking taste optimization method. The method comprises the steps that cooking is carried out according to preset cooking parameters in the cooking process; in the cooking process, cooking gas is detected to obtain gas component data; an actual taste quantized value is analyzed according to the gas component data; after cooking is finished, an ideal taste quantized value input by a user is acquired, and ideal cooking parameters are analyzed according to the ideal taste quantized value; and cooking is carried out according to the ideal cooking parameters. The actual taste quantized value can be analyzed according to the gas component data; therefore, after the cooking is finished, the user can input the ideal taste quantized value by referring to the actual taste quantized value; and the ideal cooking parameters can be analyzed from the ideal taste quantized value, so that cooking equipment cooks according to the ideal cooking parameters in the next cooking process, the cooking taste of dishes cooked by the cooking equipment is optimized, and the taste of the user is better met.

Description

technical field [0001] The invention relates to the technical field of intelligent cooking equipment, in particular to a cooking taste optimization method, a training method for an artificial neural network, a computer-readable storage medium and cooking equipment. Background technique [0002] The cooking equipment currently on the market is usually equipped with cooking utensils and seasoning feeding devices. During the process of cooking dishes with cooking utensils, seasoning feeding devices are used to automatically add seasonings to the dishes being cooked, thereby realizing full automation. cooking. This kind of cooking equipment controls the cooking utensils and seasoning feeding device according to preset cooking parameters. For example, the cooking utensils are cooked according to the preset heating power and heating time, and the seasoning feeding device is cooked according to the preset Seasonings are automatically added according to the amount of ingredients ad...

AI Technical Summary

Problems solved by technology

At present, the way for users to optimize the cooking taste is usually to modify the cooking parameters according to the deviation between the cooking taste of the dishes and the taste they want after tasting the dishes. It is difficult for high-level users to grasp the relationship between cooking parameters and cooking taste. Therefore, if users with low cooking skills directly modify cooking parameters according to cooking taste, the optimized cooking taste may still not meet the user's taste.

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