In order to realize the effect of intelligent poetry style analysis, this paper applies the text classification algorithm to the poetry style analysis, combines the knowledge representation algorithm to perform text classification and recognition, improves the algorithm, and applies it to the poetry style analysis model. Moreover, this paper combines intelligent algorithms to construct a poetry style analysis system, constructs the system’s functional modules, preprocesses the poetry documents in the corpus, and maps them to the vector space that can be directly processed by the computer. In addition, after constructing the system model, this paper verifies the poetry style analysis system based on the text classification algorithm through simulation experiments. From the research results, the effect of the poetry style analysis method based on the text classification algorithm proposed in this paper is very good, which meets the actual needs of poetry style analysis.

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A tolerance synthesis model is established based on degree of freedom of geometric variations of features in this paper. The method allows a designer to analyze the relationship between geometric variations of features of a part and functional requirement of assembly (FRA). Firstly, tolerance is modeled with DOFs of geometric variations of features and the tolerance zone is expressed with six kinematic DOFs in three-dimensional (3D) space. Secondly, the stack-up of geometric variations of features is formulated as explicit tolerance analysis equations using kinematical coordinate systems associated with each feature. To express mathematically the relationship between given FRA values and the corresponding DOFs of geometric variations of features, the reverse synthesis equations are obtained using a matrix inversion scheme of the tolerance analysis equations. Finally, a case study is used to illustrate the proposed method.

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