摘要
由一名新闻记者兼机器人与机器学习每日新闻编辑-调查人员讨论波尔兹曼机器的新发现。根据NewsRx记者在北京的新闻报道，研究表明：“时间序列数据预测在系统控制、社会管理和经济生产中起着至关重要的作用，针对时间序列数据的复杂性和DE EP学习算法的大量，提出了一种基于广义学习结构的网络模型来处理时间序列预测任务。”本研究的资助者包括国家重点研究与发展计划、教育部（教育部）人文社会科学项目、国家自然科学基金(NSFC)。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Boltzmann Machines. According to news reporting from Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Time series data prediction i s crucial in system control, social management, and economic production. For the complex features of time series data and the massive amount of arithmetic in de ep learning, a novel network model is proposed based on the broad learning archi tecture to handle time series prediction tasks.” Funders for this research include National Key Research and Development Program of China, MOE (Ministry of Education in China) Project of Humanities and Social Sciences, National Natural Science Foundation of China (NSFC).
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