Sensory evaluation method for predicting baked food based on BP neural network

Abstract

The invention discloses a sensory evaluation method for predicting baked food based on a BP neural network. The method comprises the steps that S1, baking the baked food under different cooking conditions; S2, performing fuzzy sensory evaluation on the baked food to form a fuzzy sensory score; S3, creating data sets of different cooking conditions and fuzzy sensory scores of the baked food; S4, constructing an artificial neural network learning model based on a BP algorithm by taking different cooking condition data of the baked food data set as an input layer and taking the fuzzy sensory score as an output layer, and training until the artificial neural network learning model is stable; and S5, taking different cooking condition data of the unknown baked food as an input layer, and predicting a fuzzy sensory score of the unknown baked food according to the artificial neural network learning model. The cooking effect of the food can be predicted through the cooking parameters, the prediction accuracy of the model is high, cooking condition reference can be conveniently provided for a user, and the cooking effect of the steaming and baking integrated machine is predicted.

Description

technical field [0001] The invention belongs to the field of food evaluation methods, in particular to a sensory evaluation method for predicting baked food based on BP neural network. Background technique [0002] As a cooking appliance with fast-growing sales, the all-in-one steamer and oven has been welcomed by consumers. In the cooking process of the integrated steam and oven, parameters such as time, temperature, and humidity are usually set as the baking conditions, but these parameter conditions are usually divided into high, medium, and low levels. When setting these cooking parameters, users often do not know what these parameters mean. The expected cooking effect, so the user will appear to be at a loss for the settings of these parameters. Since the mathematical relationship between these cooking parameters and cooking results is not particularly obvious, it is difficult to predict using mathematical formulas. [0003] As a mathematical modeling method, the neur...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a sensory evaluation method for predicting baked food based on BP neural network, so as to solve the problem that the user cannot grasp the expected cooking effect of the parameters when setting the baking parameters using the steaming and baking machine, so as to improve the quality of food baking. quality, understand the technical problems of the performance of the steamer

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