最近,长短时记忆网络(LSTM)再次成为研究热点,今年发布的xLSTM与Vision-LSTM,以其创新的思路和应用,引发了学术界的广泛关注。这些新颖的模型不仅克服了以往LSTM在存储决策、信息处理等方面的局限性,更在处理视觉数据与时序数据的方式上,展现出令人惊艳的效果。
在当今迅速发展的科技背景下,电力行业的智能化变革正如火如荼进行。近日,国网吉林省电力有限公司经济技术研究院迎来重大里程碑——成功获得了名为“基于负荷挖掘和LSTM神经网络的电力负荷预测方法”的专利。这一消息不仅引发了业内的广泛关注,更为未来电力行业的数字化转型注入了新的活力。
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LSTM Research Identifies 91 RNA Viruses in Parasitic WormsNew research shows that parasitic nematodes, responsible for infecting more than a billion people globally, carry viruses that may solve the puzzle of why some cause serious diseases. A study led ...
A research team has unveiled a new method for assessing the freshness of bighead carp heads in cold chain logistics using ...
基于深度学习的大风订正预报研究全文请用PC端下载 地址:http://www.hyyb.org.cn/Magazine/Show.aspx?ID=3601读书小笔记作者:杨凡1 刘志丰2 任兆鹏1 崔天伦3 于洋3单位:1. 青岛市气象服务中心, ...
Devise uses AI to detect infectious diseases and determine patients’ antibiotic susceptibilities in 15 minutes ...
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