In order to improve the effect of goodwill evaluation and intangible asset management, this paper combines the improved fuzzy comprehensive evaluation method to construct an intelligent algorithm. In order to consider the many influencing factors of intangible asset prices and their own influence, this experiment adopts the ARDL model for analysis. Based on the traditional LSTM model, this paper innovatively introduces sparse principal component analysis for feature dimensionality reduction and, on the other hand, adds a convolutional neural network to the model, which is suitable for feature extraction. In addition, this paper constructs a goodwill evaluation and intangible asset management model based on the improved fuzzy comprehensive evaluation method. The research shows that the improved fuzzy comprehensive evaluation method proposed in this paper has a very good application effect in goodwill evaluation and intangible asset management.
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