Analysis of AI MT Based on Fuzzy Algorithm

Abstract

The advancement of artificial intelligence technology is highly dependent on advancements in computer technology. The former created the technology for the latter. In the near future, we believe computer artificial intelligence technology will be further developed and better serve people. In other words, the data or note producer will edit the bridge segments with prominent contradictions in each program and broadcast them through the network with the titles that people are interested in, which has gotten a lot of attention and comments. This paper investigates a new fuzzy evaluation model by starting with the current situation. This paper investigates fuzzy algorithm-based artificial intelligence machine translation. The order of machine translation follows the trend in the figure, whereas the distribution of HEMTM machine translation is more concentrated under the HEMTM model. The average reliability ratio of the data mining algorithm is 0.97, the average reliability ratio of the decision tree algorithm is 0.84, the average reliability ratio of the machine learning algorithm is 0.71, and the average reliability ratio of the fuzzy algorithm is 1.34 when the vocabulary index is 15. The proportion of fuzzy algorithms in this paper is the highest of the four algorithms. It can be transformed into the contraction of frequency-domain coefficients in artificial intelligence machine translation using a fuzzy algorithm, greatly simplifying the operation. However, it will cause the ringing effect of fuzzy algorithm boundary in machine translation because it cannot well express the singular information of signals such as boundary. The extent of this effect is determined by the artificial intelligence machine translation breadth.