首页 【Google2023】利用TiDE进行长期预测实战（时间序列密集编码器）

【Google2023】利用TiDE进行长期预测实战（时间序列密集编码器）

上传者： java1314777 | 上传时间： 2023-12-21 16:41:14 | 文件大小： 8.12MB | 文件类型： ZIP
大家好，最近在搞论文所以在研究各种论文的思想，这篇文章给大家带来的是TiDE模型由Goggle在2023.8年发布，其主要的核心思想是：基于多层感知机（MLP）构建的编码器-解码器架构，核心创新在于它结合了线性模型的简洁性和速度优势，同时能有效处理协变量和非线性依赖。论文中号称TiDE在长期时间序列预测基准测试中不仅表现匹敌甚至超越了先前的方法，而且在速度上比最好的基于Transformer的模型快5到10倍。在官方的开源代码中是并没有预测未来数据功能的，因为这种都是学术文章发表论文的时候只看测试集表现。我在自己的框架下给其补上了这一功能同时加上了绘图的功能，非常适合大家发表论文的适合拿来做对比模型。TiDE（时间序列密集编码器）模型是一个基于多层感知机（MLP）的编码器-解码器架构，旨在简化长期时间序列预测。该模型结合了线性模型的简单性和速度，同时能够有效处理协变量和非线性依赖。

文件下载

资源详情

[{"title":"（ 114 个子文件 8.12MB ） 【Google2023】利用TiDE进行长期预测实战（时间序列密集编码器）","children":[{"title":"ETTh1.csv <span style='color:#111;'> 2.47MB </span>","children":null,"spread":false},{"title":"T1trainData-checkpoint.csv <span style='color:#111;'> 560.76KB </span>","children":null,"spread":false},{"title":"MSST2trainData-checkpoint.csv <span style='color:#111;'> 455.11KB </span>","children":null,"spread":false},{"title":"T1testData-checkpoint.csv <span style='color:#111;'> 189.15KB </span>","children":null,"spread":false},{"title":"ETTh1-Test.csv <span style='color:#111;'> 38.37KB </span>","children":null,"spread":false},{"title":"Dockerfile <span style='color:#111;'> 206B </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 184B </span>","children":null,"spread":false},{"title":"model.iml <span style='color:#111;'> 488B </span>","children":null,"spread":false},{"title":"pred.npy <span style='color:#111;'> 2.21MB </span>","children":null,"spread":false},{"title":"true.npy <span style='color:#111;'> 2.21MB </span>","children":null,"spread":false},{"title":"pred.npy <span style='color:#111;'> 2.21MB </span>","children":null,"spread":false},{"title":"true.npy <span style='color:#111;'> 2.21MB </span>","children":null,"spread":false},{"title":"pred.npy <span style='color:#111;'> 2.21MB </span>","children":null,"spread":false},{"title":"true.npy <span style='color:#111;'> 2.21MB </span>","children":null,"spread":false},{"title":"pred.npy <span style='color:#111;'> 378.13KB </span>","children":null,"spread":false},{"title":"true.npy <span style='color:#111;'> 378.13KB </span>","children":null,"spread":false},{"title":"pred.npy <span style='color:#111;'> 315.13KB </span>","children":null,"spread":false},{"title":"true.npy <span style='color:#111;'> 315.13KB </span>","children":null,"spread":false},{"title":"pred.npy <span style='color:#111;'> 54.13KB </span>","children":null,"spread":false},{"title":"true.npy <span style='color:#111;'> 54.13KB </span>","children":null,"spread":false},{"title":"pred.npy <span style='color:#111;'> 31.63KB </span>","children":null,"spread":false},{"title":"true.npy <span style='color:#111;'> 31.63KB </span>","children":null,"spread":false},{"title":"pred.npy <span style='color:#111;'> 31.63KB </span>","children":null,"spread":false},{"title":"true.npy <span style='color:#111;'> 31.63KB </span>","children":null,"spread":false},{"title":"pred.npy <span style='color:#111;'> 31.63KB </span>","children":null,"spread":false},{"title":"true.npy <span style='color:#111;'> 31.63KB </span>","children":null,"spread":false},{"title":"metrics.npy <span style='color:#111;'> 148B </span>","children":null,"spread":false},{"title":"metrics.npy <span style='color:#111;'> 148B </span>","children":null,"spread":false},{"title":"metrics.npy <span style='color:#111;'> 148B </span>","children":null,"spread":false},{"title":"metrics.npy <span style='color:#111;'> 148B </span>","children":null,"spread":false},{"title":"metrics.npy <span style='color:#111;'> 148B </span>","children":null,"spread":false},{"title":"metrics.npy <span style='color:#111;'> 148B </span>","children":null,"spread":false},{"title":"metrics.npy <span style='color:#111;'> 148B </span>","children":null,"spread":false},{"title":"metrics.npy <span style='color:#111;'> 148B </span>","children":null,"spread":false},{"title":"metrics.npy <span style='color:#111;'> 148B </span>","children":null,"spread":false},{"title":"forcast.png <span style='color:#111;'> 39.17KB </span>","children":null,"spread":false},{"title":"MultiWaveletCorrelation.py <span style='color:#111;'> 22.50KB </span>","children":null,"spread":false},{"title":"exp_informer.py <span style='color:#111;'> 16.24KB </span>","children":null,"spread":false},{"title":"exp_informer-checkpoint.py <span style='color:#111;'> 15.98KB </span>","children":null,"spread":false},{"title":"exp_informer (4)-checkpoint.py <span style='color:#111;'> 15.96KB </span>","children":null,"spread":false},{"title":"data_loader-checkpoint.py <span style='color:#111;'> 13.52KB </span>","children":null,"spread":false},{"title":"data_loader.py <span style='color:#111;'> 13.47KB </span>","children":null,"spread":false},{"title":"SelfAttention_Family.py <span style='color:#111;'> 11.78KB </span>","children":null,"spread":false},{"title":"ETSformer_EncDec.py <span style='color:#111;'> 11.13KB </span>","children":null,"spread":false},{"title":"main_informer.py <span style='color:#111;'> 7.59KB </span>","children":null,"spread":false},{"title":"Pyraformer_EncDec.py <span style='color:#111;'> 7.26KB </span>","children":null,"spread":false},{"title":"FourierCorrelation.py <span style='color:#111;'> 7.17KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 7.05KB </span>","children":null,"spread":false},{"title":"TiDE.py <span style='color:#111;'> 6.86KB </span>","children":null,"spread":false},{"title":"Embed.py <span style='color:#111;'> 6.85KB </span>","children":null,"spread":false},{"title":"Autoformer_EncDec.py <span style='color:#111;'> 6.67KB </span>","children":null,"spread":false},{"title":"AutoCorrelation.py <span style='color:#111;'> 6.29KB </span>","children":null,"spread":false},{"title":"timefeatures.py <span style='color:#111;'> 5.43KB </span>","children":null,"spread":false},{"title":"TransformerBlocks.py <span style='color:#111;'> 5.20KB </span>","children":null,"spread":false},{"title":"Embedding.py <span style='color:#111;'> 4.83KB </span>","children":null,"spread":false},{"title":"Transformer_EncDec.py <span style='color:#111;'> 4.81KB </span>","children":null,"spread":false},{"title":"Crossformer_EncDec.py <span style='color:#111;'> 4.23KB </span>","children":null,"spread":false},{"title":"Invertible.py <span style='color:#111;'> 3.22KB </span>","children":null,"spread":false},{"title":"tools.py <span style='color:#111;'> 2.76KB </span>","children":null,"spread":false},{"title":"Conv_Blocks.py <span style='color:#111;'> 2.31KB </span>","children":null,"spread":false},{"title":"exp_basic.py <span style='color:#111;'> 875B </span>","children":null,"spread":false},{"title":"masking.py <span style='color:#111;'> 851B </span>","children":null,"spread":false},{"title":"metrics.py <span style='color:#111;'> 826B </span>","children":null,"spread":false},{"title":"Projection.py <span style='color:#111;'> 745B </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 1B </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"MultiWaveletCorrelation.cpython-39.pyc <span style='color:#111;'> 18.06KB </span>","children":null,"spread":false},{"title":"ETSformer_EncDec.cpython-39.pyc <span style='color:#111;'> 11.86KB </span>","children":null,"spread":false},{"title":"exp_informer.cpython-39.pyc <span style='color:#111;'> 10.64KB </span>","children":null,"spread":false},{"title":"SelfAttention_Family.cpython-39.pyc <span style='color:#111;'> 8.88KB </span>","children":null,"spread":false},{"title":"data_loader.cpython-38.pyc <span style='color:#111;'> 8.88KB </span>","children":null,"spread":false},{"title":"data_loader.cpython-39.pyc <span style='color:#111;'> 8.82KB </span>","children":null,"spread":false},{"title":"exp_informer.cpython-38.pyc <span style='color:#111;'> 8.70KB </span>","children":null,"spread":false},{"title":"Embed.cpython-39.pyc <span style='color:#111;'> 7.26KB </span>","children":null,"spread":false},{"title":"timefeatures.cpython-39.pyc <span style='color:#111;'> 7.16KB </span>","children":null,"spread":false},{"title":"timefeatures.cpython-38.pyc <span style='color:#111;'> 7.11KB </span>","children":null,"spread":false},{"title":"Autoformer_EncDec.cpython-39.pyc <span style='color:#111;'> 6.85KB </span>","children":null,"spread":false},{"title":"Pyraformer_EncDec.cpython-39.pyc <span style='color:#111;'> 6.66KB </span>","children":null,"spread":false},{"title":"Embedding.cpython-39.pyc <span style='color:#111;'> 6.50KB </span>","children":null,"spread":false},{"title":"AutoCorrelation.cpython-39.pyc <span style='color:#111;'> 5.36KB </span>","children":null,"spread":false},{"title":"TransformerBlocks.cpython-39.pyc <span style='color:#111;'> 5.26KB </span>","children":null,"spread":false},{"title":"FourierCorrelation.cpython-39.pyc <span style='color:#111;'> 4.89KB </span>","children":null,"spread":false},{"title":"model.cpython-38.pyc <span style='color:#111;'> 4.81KB </span>","children":null,"spread":false},{"title":"model.cpython-39.pyc <span style='color:#111;'> 4.78KB </span>","children":null,"spread":false},{"title":"Transformer_EncDec.cpython-39.pyc <span style='color:#111;'> 4.48KB </span>","children":null,"spread":false},{"title":"Crossformer_EncDec.cpython-39.pyc <span style='color:#111;'> 4.38KB </span>","children":null,"spread":false},{"title":"Invertible.cpython-39.pyc <span style='color:#111;'> 3.68KB </span>","children":null,"spread":false},{"title":"tools.cpython-39.pyc <span style='color:#111;'> 3.21KB </span>","children":null,"spread":false},{"title":"tools.cpython-38.pyc <span style='color:#111;'> 3.18KB </span>","children":null,"spread":false},{"title":"Conv_Blocks.cpython-39.pyc <span style='color:#111;'> 2.41KB </span>","children":null,"spread":false},{"title":"exp_basic.cpython-39.pyc <span style='color:#111;'> 1.54KB </span>","children":null,"spread":false},{"title":"exp_basic.cpython-38.pyc <span style='color:#111;'> 1.50KB </span>","children":null,"spread":false},{"title":"masking.cpython-39.pyc <span style='color:#111;'> 1.43KB </span>","children":null,"spread":false},{"title":"metrics.cpython-39.pyc <span style='color:#111;'> 1.42KB </span>","children":null,"spread":false},{"title":"metrics.cpython-38.pyc <span style='color:#111;'> 1.38KB </span>","children":null,"spread":false},{"title":"masking.cpython-38.pyc <span style='color:#111;'> 1.38KB </span>","children":null,"spread":false},{"title":"Projection.cpython-39.pyc <span style='color:#111;'> 1.19KB </span>","children":null,"spread":false},{"title":"......","children":null,"spread":false},{"title":"<span style='color:steelblue;'>文件过多，未全部展示</span>","children":null,"spread":false}],"spread":true}]

评论信息

其他资源

免责申明

【只为小站】的资源来自网友分享，仅供学习研究，请务必在下载后24小时内给予删除，不得用于其他任何用途，否则后果自负。基于互联网的特殊性，【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查；无论 【只为小站】 经营者是否已进行审查，用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明

个人信息

下载历史

相关资源标签

热门下载

最新下载