时间序列预测模型实战案例深度学习华为MTS-Mixers模型

上传者: java1314777 | 上传时间: 2023-12-25 19:58:03 | 文件大小: 51.93MB | 文件类型: ZIP
首先我们要对时间序列概念有一个基本的了解时间序列预测大致分为两种一种是单元时间序列预测另一种是多元时间序列预测单元时间序列预测是指只考虑一个时间序列的预测模型。它通常用于预测单一变量的未来值,例如股票价格、销售量等。在单元时间序列预测中,我们需要对历史数据进行分析,确定趋势、季节性和周期性等因素,并使用这些因素来预测未来的值。常见的单元时间序列预测模型有移动平均模型(MA)自回归模型(AR)自回归移动平均模型(ARMA)差分自回归移动平均模型(ARIMA)后期我也会讲一些最新的预测模型包括Informer,TPA-LSTM,ARIMA,XGBOOST,Holt-winter,移动平均法等等一系列关于时间序列预测的模型,包括深度学习和机器学习方向的模型我都会讲,你可以根据需求选取适合你自己的模型进行预测,如果有需要可以+个关注。

文件下载

资源详情

[{"title":"( 70 个子文件 51.93MB ) 时间序列预测模型实战案例深度学习华为MTS-Mixers模型","children":[{"title":"layers","children":[{"title":"TransformerBlocks.py <span style='color:#111;'> 5.20KB </span>","children":null,"spread":false},{"title":"Projection.py <span style='color:#111;'> 745B </span>","children":null,"spread":false},{"title":"Invertible.py <span style='color:#111;'> 3.22KB </span>","children":null,"spread":false},{"title":"Embedding.py <span style='color:#111;'> 4.83KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"Invertible.cpython-39.pyc <span style='color:#111;'> 3.68KB </span>","children":null,"spread":false},{"title":"Embedding.cpython-39.pyc <span style='color:#111;'> 6.50KB </span>","children":null,"spread":false},{"title":"Projection.cpython-39.pyc <span style='color:#111;'> 1.19KB </span>","children":null,"spread":false},{"title":"TransformerBlocks.cpython-39.pyc <span style='color:#111;'> 5.26KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"clean.sh <span style='color:#111;'> 67B </span>","children":null,"spread":false},{"title":"utils","children":[{"title":"decomposition.py <span style='color:#111;'> 1.52KB </span>","children":null,"spread":false},{"title":"metrics.py <span style='color:#111;'> 361B </span>","children":null,"spread":false},{"title":"masking.py <span style='color:#111;'> 831B </span>","children":null,"spread":false},{"title":"timefeatures.py <span style='color:#111;'> 3.66KB </span>","children":null,"spread":false},{"title":"tools.py <span style='color:#111;'> 3.00KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"timefeatures.cpython-39.pyc <span style='color:#111;'> 5.18KB </span>","children":null,"spread":false},{"title":"tools.cpython-39.pyc <span style='color:#111;'> 3.39KB </span>","children":null,"spread":false},{"title":"decomposition.cpython-39.pyc <span style='color:#111;'> 2.17KB </span>","children":null,"spread":false},{"title":"metrics.cpython-39.pyc <span style='color:#111;'> 764B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"test_results","children":[{"title":"Transformer_sum14_ftMS_sl128_ll64_pl4_dm512_nh1_el2_dl1_df2048_fc1_ebtimeF_0","children":[{"title":"0.pdf <span style='color:#111;'> 11.36KB </span>","children":null,"spread":false}],"spread":true},{"title":"Transformer_sum14_ftMS_sl64_ll32_pl4_dm512_nh1_el2_dl1_df2048_fc1_ebtimeF_0","children":[{"title":"0.pdf <span style='color:#111;'> 10.99KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":".idea","children":[{"title":"workspace.xml <span style='color:#111;'> 8.96KB </span>","children":null,"spread":false},{"title":"misc.xml <span style='color:#111;'> 185B </span>","children":null,"spread":false},{"title":"MTS-Mixers-main.iml <span style='color:#111;'> 482B </span>","children":null,"spread":false},{"title":"inspectionProfiles","children":[{"title":"Project_Default.xml <span style='color:#111;'> 1.34KB </span>","children":null,"spread":false},{"title":"profiles_settings.xml <span style='color:#111;'> 174B </span>","children":null,"spread":false}],"spread":true},{"title":"modules.xml <span style='color:#111;'> 289B </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 50B </span>","children":null,"spread":false},{"title":"aws.xml <span style='color:#111;'> 304B </span>","children":null,"spread":false}],"spread":true},{"title":"exp","children":[{"title":"exp_basic.py <span style='color:#111;'> 878B </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"exp_main.cpython-39.pyc <span style='color:#111;'> 9.03KB </span>","children":null,"spread":false},{"title":"exp_basic.cpython-39.pyc <span style='color:#111;'> 1.53KB </span>","children":null,"spread":false}],"spread":true},{"title":"exp_main.py <span style='color:#111;'> 14.68KB </span>","children":null,"spread":false}],"spread":true},{"title":"run.py <span style='color:#111;'> 9.12KB </span>","children":null,"spread":false},{"title":"requirements.txt <span style='color:#111;'> 95B </span>","children":null,"spread":false},{"title":"models","children":[{"title":"MTSMixer.py <span style='color:#111;'> 3.52KB </span>","children":null,"spread":false},{"title":"DLinear.py <span style='color:#111;'> 3.58KB </span>","children":null,"spread":false},{"title":"MTSAttn.py <span style='color:#111;'> 2.03KB </span>","children":null,"spread":false},{"title":"Transformer.py <span style='color:#111;'> 2.43KB </span>","children":null,"spread":false},{"title":"SCINet.py <span style='color:#111;'> 4.02KB </span>","children":null,"spread":false},{"title":"Transformer_lite.py <span style='color:#111;'> 2.21KB </span>","children":null,"spread":false},{"title":"MTSD.py <span style='color:#111;'> 1.83KB </span>","children":null,"spread":false},{"title":"MTSMatrix.py <span style='color:#111;'> 2.17KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"MTSMixer.cpython-39.pyc <span style='color:#111;'> 4.27KB </span>","children":null,"spread":false},{"title":"DLinear.cpython-39.pyc <span style='color:#111;'> 2.86KB </span>","children":null,"spread":false},{"title":"MTSMatrix.cpython-39.pyc <span style='color:#111;'> 3.08KB </span>","children":null,"spread":false},{"title":"Transformer.cpython-39.pyc <span style='color:#111;'> 1.92KB </span>","children":null,"spread":false},{"title":"MTSD.cpython-39.pyc <span style='color:#111;'> 2.32KB </span>","children":null,"spread":false},{"title":"FNet.cpython-39.pyc <span style='color:#111;'> 2.09KB </span>","children":null,"spread":false},{"title":"Transformer_lite.cpython-39.pyc <span style='color:#111;'> 2.68KB </span>","children":null,"spread":false},{"title":"MTSAttn.cpython-39.pyc <span style='color:#111;'> 2.59KB </span>","children":null,"spread":false},{"title":"SCINet.cpython-39.pyc <span style='color:#111;'> 3.48KB </span>","children":null,"spread":false}],"spread":false},{"title":"FNet.py <span style='color:#111;'> 1.54KB </span>","children":null,"spread":false}],"spread":true},{"title":"checkpoints","children":[{"title":"Transformer_sum14_ftMS_sl128_ll64_pl4_dm512_nh1_el2_dl1_df2048_fc1_ebtimeF_0","children":[{"title":"checkpoint.pth <span style='color:#111;'> 28.16MB </span>","children":null,"spread":false}],"spread":true},{"title":"Transformer_sum14_ftMS_sl64_ll32_pl4_dm512_nh1_el2_dl1_df2048_fc1_ebtimeF_0","children":[{"title":"checkpoint.pth <span style='color:#111;'> 28.18MB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":".gitignore <span style='color:#111;'> 31B </span>","children":null,"spread":false},{"title":"data_provider","children":[{"title":"__init__.py <span style='color:#111;'> 1B </span>","children":null,"spread":false},{"title":"data_loader.py <span style='color:#111;'> 14.83KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"__init__.cpython-39.pyc <span style='color:#111;'> 160B </span>","children":null,"spread":false},{"title":"data_loader.cpython-39.pyc <span style='color:#111;'> 11.32KB </span>","children":null,"spread":false},{"title":"data_factory.cpython-39.pyc <span style='color:#111;'> 1.12KB </span>","children":null,"spread":false}],"spread":false},{"title":"data_factory.py <span style='color:#111;'> 1.42KB </span>","children":null,"spread":false}],"spread":true},{"title":"results","children":[{"title":"Transformer_sum14_ftM_sl64_ll32_pl4_dm512_nh1_el2_dl1_df2048_fc1_ebtimeF_0","children":[{"title":"real_prediction.npy <span style='color:#111;'> 144B </span>","children":null,"spread":false}],"spread":true},{"title":"Transformer_sum_ftM_sl126_ll48_pl1_dm512_nh1_el2_dl1_df2048_fc1_ebtimeF_0","children":[{"title":"real_prediction.npy <span style='color:#111;'> 156B </span>","children":null,"spread":false}],"spread":false},{"title":"Transformer_sum_ftM_sl126_ll48_pl4_dm512_nh1_el2_dl1_df2048_fc1_ebtimeF_0","children":[{"title":"real_prediction.npy <span style='color:#111;'> 144B </span>","children":null,"spread":false}],"spread":false},{"title":"Transformer_sum14_ftM_sl126_ll48_pl4_dm512_nh1_el2_dl1_df2048_fc1_ebtimeF_0","children":[{"title":"real_prediction.npy <span style='color:#111;'> 144B </span>","children":null,"spread":false}],"spread":false},{"title":"Transformer_sum14_ftMS_sl128_ll64_pl4_dm512_nh1_el2_dl1_df2048_fc1_ebtimeF_0","children":[{"title":"real_prediction.npy <span style='color:#111;'> 144B </span>","children":null,"spread":false}],"spread":false},{"title":"Transformer_sum14_ftMS_sl64_ll32_pl4_dm512_nh1_el2_dl1_df2048_fc1_ebtimeF_0","children":[{"title":"real_prediction.npy <span style='color:#111;'> 144B </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"tranform.py <span style='color:#111;'> 166B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 5.01KB </span>","children":null,"spread":false},{"title":"script.md <span style='color:#111;'> 4.77KB </span>","children":null,"spread":false}],"spread":true}]

评论信息

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