Python实现STID多元时间序列预测

上传者: m0_57362105 | 上传时间: 2022-11-04 12:04:50 | 文件大小: 930KB | 文件类型: ZIP
Python实现STID多元时间序列预测 多元时间序列 (MTS) 预测在广泛的应用中起着至关重要的作用。STID 基于简单的多层感知器 (MLP) 同时实现最佳性能和效率。

文件下载

资源详情

[{"title":"( 40 个子文件 930KB ) Python实现STID多元时间序列预测","children":[{"title":"STID-master","children":[{"title":"figures","children":[{"title":"main_results.png <span style='color:#111;'> 451.92KB </span>","children":null,"spread":false},{"title":"STID_architecture.png <span style='color:#111;'> 62.28KB </span>","children":null,"spread":false},{"title":"efficiency_and_ablation.png <span style='color:#111;'> 200.30KB </span>","children":null,"spread":false},{"title":"visualizations.png <span style='color:#111;'> 203.75KB </span>","children":null,"spread":false}],"spread":true},{"title":"basicts","children":[{"title":"runners","children":[{"title":"base_traffic_runner.py <span style='color:#111;'> 10.86KB </span>","children":null,"spread":false},{"title":"base_runner.py <span style='color:#111;'> 11.19KB </span>","children":null,"spread":false},{"title":"STID_runner.py <span style='color:#111;'> 2.38KB </span>","children":null,"spread":false}],"spread":true},{"title":"metrics","children":[{"title":"mae.py <span style='color:#111;'> 515B </span>","children":null,"spread":false},{"title":"rmse.py <span style='color:#111;'> 640B </span>","children":null,"spread":false},{"title":"mape.py <span style='color:#111;'> 690B </span>","children":null,"spread":false}],"spread":true},{"title":"data","children":[{"title":"transforms.py <span style='color:#111;'> 761B </span>","children":null,"spread":false},{"title":"base_dataset.py <span style='color:#111;'> 1.73KB </span>","children":null,"spread":false}],"spread":true},{"title":"losses","children":[{"title":"losses.py <span style='color:#111;'> 351B </span>","children":null,"spread":false}],"spread":true},{"title":"run.py <span style='color:#111;'> 1.13KB </span>","children":null,"spread":false},{"title":"options","children":[{"title":"STID","children":[{"title":"STID_PEMS04.py <span style='color:#111;'> 3.13KB </span>","children":null,"spread":false},{"title":"STID_PEMS-BAY.py <span style='color:#111;'> 3.12KB </span>","children":null,"spread":false},{"title":"STID_PEMS07.py <span style='color:#111;'> 3.11KB </span>","children":null,"spread":false},{"title":"STID_Electricity336.py <span style='color:#111;'> 3.14KB </span>","children":null,"spread":false},{"title":"STID_PEMS08.py <span style='color:#111;'> 3.12KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"archs","children":[{"title":"STID_arch","children":[{"title":"mlp.py <span style='color:#111;'> 927B </span>","children":null,"spread":false},{"title":"STID_arch.py <span style='color:#111;'> 4.20KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 50B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"utils","children":[{"title":"options.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"serialization.py <span style='color:#111;'> 1.98KB </span>","children":null,"spread":false},{"title":"distance.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"misc.py <span style='color:#111;'> 795B </span>","children":null,"spread":false},{"title":"adjacent_matrix_norm.py <span style='color:#111;'> 3.72KB </span>","children":null,"spread":false},{"title":"registry.py <span style='color:#111;'> 2.08KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"requirements.txt <span style='color:#111;'> 652B </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 232B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 3.96KB </span>","children":null,"spread":false},{"title":"scripts","children":[{"title":"data_preparation","children":[{"title":"PEMS-BAY","children":[{"title":"generate_training_data.py <span style='color:#111;'> 5.54KB </span>","children":null,"spread":false}],"spread":true},{"title":"PEMS04","children":[{"title":"generate_training_data.py <span style='color:#111;'> 6.06KB </span>","children":null,"spread":false},{"title":"generate_adj_mx.py <span style='color:#111;'> 7.09KB </span>","children":null,"spread":false}],"spread":true},{"title":"Electricity336","children":[{"title":"generate_training_data.py <span style='color:#111;'> 5.61KB </span>","children":null,"spread":false}],"spread":true},{"title":"PEMS08","children":[{"title":"generate_training_data.py <span style='color:#111;'> 6.06KB </span>","children":null,"spread":false},{"title":"generate_adj_mx.py <span style='color:#111;'> 7.09KB </span>","children":null,"spread":false}],"spread":true},{"title":"PEMS07","children":[{"title":"generate_training_data.py <span style='color:#111;'> 6.06KB </span>","children":null,"spread":false},{"title":"generate_adj_mx.py <span style='color:#111;'> 7.09KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true},{"title":"datasets","children":[{"title":"README.md <span style='color:#111;'> 16B </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"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