Path Planning Algorithm of English Retrieval based on Associative Memory Neural Network
Hehua Qiu · 2022 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers · 2022
English collocation retrieval is to extract the phrases or idioms combined with various grammatical relations from the corpus, which is used to systematically analyze and study the collocations of words. In the absence of such corpus retrieval tools, English teachers mainly use the traditional method of definition and description to identify and analyze synonyms. In order to further enrich the English vocabulary of English learners, combined with the related algorithms of similarity, this paper proposes an English retrieval path planning algorithm based on associative memory neural network. The algorithm implements a search mechanism that uses the adjacency list data structure and restricts the search area to reasonably limit the search area of the algorithm. The BP algorithm based on the associative memory neural network model greatly reduces the network training times of the sample variable system. The system effectively reduces the network training time of the sample variable system, and provides the algorithm basis for the BP algorithm to be applied to occasions with high real-time requirements. Combined with the practical application of the path planning algorithm in the English retrieval system, through the hierarchical scheduling of tasks of different importance, a satisfactory decision result is obtained. The algorithm has the advantages of small search space and fast solution speed. Simulation results verify the effectiveness of the algorithm.