| Summary: | Following the progress made in the construction of high-speed processors, the limiting effect of the way data is entered into the computer on the speed of information transfer has become more apparent. By using processing devices, in addition to achieving higher speed in the data retrieval stage, it is also possible to use their pre-processing capabilities and change the data format. Considering the importance of the topic and the work that has been done in this field, the need to discover the knowledge of the existing features with the help of choosing the appropriate feature for the classification of texts is well felt. In this article, genetic algorithm and fuzzy logic have been used to present a method for classifying texts in insurance booklets. This system is based on several stages. These steps include the learning phase that examines a set of educational texts to extract the characteristics of the categories to be the characteristics of each category; the test phase of the system is used to classify uncategorized texts. The proposed method's accuracy has been assessed using a collection of patient notebooks, and the outcomes indicate an accuracy of around 98% for the classification.
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