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Thanks to the rapid development of deep learning, big data analysistechnology is not only widely used in the field of natural language processing,but also more mature in the field of numerical prediction. It is of greatsignificance for the subject heat prediction and analysis of science andtechnology demand data. How to apply theme features to accurately predict thetheme heat of science and technology demand is the core to solve this problem.In this paper, a prediction method of subject heat of science and technologydemand based on time convolution network (TCN) is proposed to obtain thesubject feature representation of science and technology demand. Time seriesprediction is carried out based on TCN network and self attention mechanism,which increases the accuracy of subject heat prediction of science andtechnology demand data Experiments show that the prediction accuracy of thisalgorithm is better than other time series prediction methods on the realscience and technology demand datasets.

Prediction Algorithm for Heat Demand of Science and Technology Topics Based on Time Convolution Network