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作 者:许经勇[1] Xu Jingyong(Economics College,Xiamen University,Xiamen City,Fujian Province,361005)
出 处:《黄河科技学院学报》2023年第4期40-46,共7页Journal of Huanghe S&T College
摘 要:发展农村集体经济对坚持社会主义方向、引导广大农民走共同富裕道路,有着深远的意义。与此同时,这也将为加快农村公共事业建设提供财力支撑。由于农村经济体制改革的目标是废除“三级所有、队为基础”的农村人民公社制度,传统的集体统一经营必然随之废除,传统的集体经济赖以依存的载体也就荡然无存。如果说传统意义上的农村集体经济是计划经济的产物,那么,新型的农村集体经济则是市场经济的产物。新型农村集体经济是建立在农村集体产权明晰的基础上。只有建设专业化、集中化、社会化程度很高的高标准市场经济,以适度规模经营的家庭农场和农民合作社为载体的新型双层经营体制才有可能普遍建立起来,新型农村集体经济才有可能得到健康发展。Event prediction requires comprehensive consideration of many factors,and lots of the existing prediction models have some problems,such as sparse data,insufficient consideration of combined features and sequential features of the events,and single prediction type.To solve these problems,a multi-label event prediction method based on relational graph convolutional neural network is proposed by node feature aggregation technology.The proposed model extracts the combination features by using convolution and pooling algorithm,and extracts the sequence features by using long short term memory networks.Finally,the model outputs the probability for all of the predicted events through a fully connected multi-label classifier.The experimental results show that,the proposed model supports predicting multi-date and multi-type events.The maximum F 1 value can achieve 0.85 on specific data set.
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