电脑桌面
添加易通论缘成稿毕设投稿到电脑桌面
安装后可以在桌面快捷访问

2026数据科学与大数据技术一套 基于深度学习的零售库存预测补货系统设计4.27-AI4.18(论文+前后端程序代码源码+数据库源数据表+运行说明)定稿.zip

2026数据科学与大数据技术一套 基于深度学习的零售库存预测补货系统设计4.27-AI4.18(论文+前后端程序代码源码+数据库源数据表+运行说明)定稿.zip
收起资源包目录
  • bdu26bd103fengzeyu基于深度学习的零售库存预测补货系统
    • .idea
      • dataSources
        • 147b0c9e-5fdb-428e-9da5-32b2652787f8
          • storage_v2
            • _src_
              • schema
                • information_schema.FNRwLQ.meta(76 B)
                • mysql.osA4Bg.meta(63 B)
                • performance_schema.kIw0nw.meta(76 B)
                • sys.zb4BAA.meta(61 B)
        • 147b0c9e-5fdb-428e-9da5-32b2652787f8.xml(50.87 KB)
      • inspectionProfiles
        • profiles_settings.xml(174 B)
      • .gitignore(190 B)
      • bdu26bd103fengzeyu基于深度学习的零售库存预测补货系统.iml(511 B)
      • dataSources.local.xml(1.12 KB)
      • dataSources.xml(530 B)
      • misc.xml(328 B)
      • modules.xml(397 B)
      • workspace.xml(6.53 KB)
    • .vscode
      • settings.json(4 B)
    • bdu26db103fengzeyubackend
      • .pytest_cache
        • v
          • cache
            • nodeids(2 B)
            • stepwise(2 B)
        • .gitignore(39 B)
        • CACHEDIR.TAG(191 B)
        • README.md(310 B)
      • __pycache__
        • app103fengzeyu.cpython-313.pyc(3.21 KB)
      • models
        • __pycache__
          • gru_model103fengzeyu.cpython-310.pyc(5.82 KB)
          • lstm_model103fengzeyu.cpython-310.pyc(5.84 KB)
          • prophet_model103fengzeyu.cpython-310.pyc(3.72 KB)
        • cache
          • lstm_09ca8bfd22a288b69c27e74c24c99022.h5(425.04 KB)
          • prophet_014f981f5ba26c7fdaf0bd538cd87d24.pkl(33.26 KB)
          • prophet_017b8a24459fb14d4da030f8053be756.pkl(31.9 KB)
          • prophet_09d1f9997be3b123168c2893e8795211.pkl(33.09 KB)
          • prophet_0dff5fb3547a6f3d2ed815f65ac9960f.pkl(32.67 KB)
          • prophet_0f1a50acea82eccfa4006d60122614f0.pkl(33.01 KB)
          • prophet_11f1b10b2fef9eead1c295b200be1b4f.pkl(24.33 KB)
          • prophet_1201bc7680f6f31d8d49adb06491916a.pkl(23.99 KB)
          • prophet_195a0989dd0ffa5244b81fdf89845ccf.pkl(33.61 KB)
          • prophet_254d95b2f68655c3858d59056c19fe05.pkl(34.54 KB)
          • prophet_255f52ed7ca2ef8df2023522af7b0682.pkl(25.44 KB)
          • prophet_27649de436a78b4d2fc61819b97f80e8.pkl(32.92 KB)
          • prophet_291aeada3ddb3694ffc0c0bb197a9064.pkl(33.6 KB)
          • prophet_2bfc146999a2e0008e22d99617146895.pkl(22.29 KB)
          • prophet_2c9fdf7ef5f3cce183078462e8f2c320.pkl(32.93 KB)
          • prophet_2d5a6c793328b198999afd5b9f1bae03.pkl(34.12 KB)
          • prophet_2fc668de078c857f7eec393f97829d80.pkl(33.01 KB)
          • prophet_3b78f50a58592b28a6e4f00ff48d6df7.pkl(30.28 KB)
          • prophet_3ba8675abc2db21eb4fcdd8f484534f3.pkl(33.69 KB)
          • prophet_3bbb6fc772f1c9685cf55a17acaf21d1.pkl(32.84 KB)
          • prophet_4b9726971b202d6bd1217144e56a772a.pkl(29.85 KB)
          • prophet_4c413987e34785b1ab29e2914aa2fb8f.pkl(33.52 KB)
          • prophet_69a2910b5ab9ab06f8fba9ae3597a545.pkl(31.99 KB)
          • prophet_6d737ad8663b2129ef78be942bae4d78.pkl(30.37 KB)
          • prophet_6db5dbc1f802944f5b35c1ae3b646302.pkl(33.94 KB)
          • prophet_6eeed2490327ca1e198b32b17e79e850.pkl(33.6 KB)
          • prophet_752d798de98be7575c9f9a1ddd3a9093.pkl(33.09 KB)
          • prophet_7a7dcb9fe5bfca908f28fde192aed66a.pkl(30.54 KB)
          • prophet_83543e5e154120ef9b81422c0fed7e05.pkl(31.48 KB)
          • prophet_869f66846d6d9dcafa886fcc989b9eaf.pkl(20.17 KB)
          • prophet_89defeeec901b1ed8481a0a60a4a47e7.pkl(24.16 KB)
          • prophet_8c739b34e729c8345b7e1f3e0e7ac08f.pkl(32.93 KB)
          • prophet_96ca2aa7afb39886402d9ef7a04b0b3f.pkl(33.43 KB)
          • prophet_a00387f0a2a98e2bb57e9d99d5da76b0.pkl(23.4 KB)
          • prophet_a02ff0f0b7ae83616b0e9e456e22aa54.pkl(32.84 KB)
          • prophet_a091ef45c6dd563e5eecce960100518e.pkl(34.2 KB)
          • prophet_a3402df722966b79839172f241a0bb16.pkl(32.5 KB)
          • prophet_a3ab43d9b83869e5c365a0c6f8448480.pkl(33.44 KB)
          • prophet_a457ab35e9d6706f3947f14bc3f02170.pkl(29 KB)
          • prophet_abd320feab4ce5272c5970069e001f1f.pkl(33.18 KB)
          • prophet_ac8663e191888f7d9dcab41ff3dedac8.pkl(30.88 KB)
          • prophet_af97e6b94e45cbff8bdbc2528ea8b4ea.pkl(31.99 KB)
          • prophet_b7350b9b9023883a240467eddb34d4a6.pkl(33.27 KB)
          • prophet_cc9d295fbab845fbe20834cdd1a06519.pkl(29.35 KB)
          • prophet_d1b1fe9435fde821a036fbd50223996f.pkl(33.86 KB)
          • prophet_d3b1786e7bfe561ec22cf4e8653d8b48.pkl(34.12 KB)
          • prophet_d6306440aea56a7059d1b972673a17d3.pkl(33.43 KB)
          • prophet_f171c18b23ab14de52eeaa6850ab0009.pkl(25.43 KB)
          • prophet_f53d523fa7f5e19f08dd9190518651b3.pkl(33.94 KB)
          • prophet_f6ed38deef657e9cde9e975dbb6fb4eb.pkl(33.18 KB)
          • prophet_f7520f50ba81c7c082f419bbf99a3adb.pkl(33.43 KB)
          • scaler_09ca8bfd22a288b69c27e74c24c99022.pkl(521 B)
        • gru_model103fengzeyu.py(6.7 KB)
        • lstm_model103fengzeyu.py(6.78 KB)
        • prophet_model103fengzeyu.py(3.38 KB)
      • src
        • __pycache__
          • __init__.cpython-310.pyc(229 B)
          • alert_service103fengzeyu.cpython-310.pyc(14.27 KB)
          • alert_service103fengzeyu.cpython-313.pyc(23.77 KB)
          • analytics_service103fengzeyu.cpython-310.pyc(6.45 KB)
          • auth_service103fengzeyu.cpython-310.pyc(3.06 KB)
          • data_service103fengzeyu.cpython-310.pyc(7.84 KB)
          • data_service103fengzeyu.cpython-313.pyc(13.96 KB)
          • layered_scheduler103fengzeyu.cpython-310.pyc(3.82 KB)
          • model_admin_service103fengzeyu.cpython-310.pyc(5.81 KB)
          • notification_service103fengzeyu.cpython-310.pyc(12.17 KB)
          • notification_service103fengzeyu.cpython-313.pyc(16.5 KB)
          • order_service103fengzeyu.cpython-310.pyc(18.34 KB)
          • order_service103fengzeyu.cpython-313.pyc(27.31 KB)
          • prediction_service103fengzeyu.cpython-310.pyc(10.45 KB)
          • prediction_service103fengzeyu.cpython-313.pyc(16.49 KB)
          • routes103fengzeyu.cpython-310.pyc(15.59 KB)
          • routes103fengzeyu.cpython-313.pyc(26.43 KB)
        • __init__.py(19 B)
        • alert_service103fengzeyu.py(23.19 KB)
        • analytics_service103fengzeyu.py(8.39 KB)
        • auth_service103fengzeyu.py(4.01 KB)
        • data_service103fengzeyu.py(13.6 KB)
        • layered_scheduler103fengzeyu.py(4.2 KB)
        • model_admin_service103fengzeyu.py(7.48 KB)
        • notification_service103fengzeyu.py(16.07 KB)
        • order_service103fengzeyu.py(27.21 KB)
        • prediction_service103fengzeyu.py(16.75 KB)
        • routes103fengzeyu.py(18.59 KB)
      • utils
        • __pycache__
          • auth103fengzeyu.cpython-310.pyc(2.4 KB)
          • data_processor103fengzeyu.cpython-310.pyc(15.32 KB)
          • data_processor103fengzeyu.cpython-313.pyc(28.28 KB)
          • database103fengzeyu.cpython-310.pyc(23.58 KB)
          • database103fengzeyu.cpython-311.pyc(25.81 KB)
          • database103fengzeyu.cpython-313.pyc(33.44 KB)
          • inventory_calculator103fengzeyu.cpython-310.pyc(5.04 KB)
          • user_manager103fengzeyu.cpython-310.pyc(4.59 KB)
        • auth103fengzeyu.py(2.52 KB)
        • data_processor103fengzeyu.py(22.69 KB)
        • database103fengzeyu.py(28.9 KB)
        • inventory_calculator103fengzeyu.py(7.24 KB)
        • user_manager103fengzeyu.py(5.46 KB)
      • .env(152 B)
      • .env.example(221 B)
      • alerts_cache.json(26.77 KB)
      • app103fengzeyu.py(4.09 KB)
      • requirements.txt(202 B)预览内容
    • bdu26db103fengzeyudata
      • OnlineRetail1.csv(44 MB)
    • bdu26db103fengzeyufrontend
      • build
        • static
          • css
            • main.86008d80.css(13.4 KB)
          • js
            • main.76d9838d.js(2.62 MB)
            • main.76d9838d.js.LICENSE.txt(43.77 KB)预览内容
        • asset-manifest.json(240 B)
        • index.html(349 B)
      • public
        • index.html(273 B)
      • src
        • components
          • AdminDashboard.css(6.55 KB)
          • AdminDashboard103fengzeyu.js(11.97 KB)
          • AdminNotifications.css(1.1 KB)
          • AdminNotifications103fengzeyu.js(5.51 KB)
          • AdminPrediction.css(702 B)
          • AdminPrediction103fengzeyu.js(10.25 KB)
          • AdminProductManagement.css(881 B)
          • AdminProductManagement103fengzeyu.js(10.46 KB)
          • ChangePassword.css(518 B)
          • ChangePassword103fengzeyu.js(4.21 KB)
          • DecisionCenter103fengzeyu.js(8.84 KB)
          • Login.css(2.51 KB)
          • Login103fengzeyu.js(4.81 KB)
          • ModelAdminPanel103fengzeyu.js(10.76 KB)
          • OrderHistory.css(240 B)
          • OrderHistory103fengzeyu.js(6.06 KB)
          • ShopPage.css(1.08 KB)
          • ShopPage103fengzeyu.js(9.11 KB)
          • UserCenter.css(132 B)
          • UserCenter103fengzeyu.js(4.14 KB)
          • UserProfile.css(507 B)
          • UserProfile103fengzeyu.js(5.02 KB)
        • utils
          • api103fengzeyu.js(7.4 KB)
          • messageManager103fengzeyu.js(1.64 KB)
        • App.css(5.03 KB)
        • App103fengzeyu.js(11.57 KB)
        • index.js(275 B)
      • .env(148 B)
      • package-lock.json(703.18 KB)
      • package.json(818 B)
    • .gitignore(316 B)
  • 数据科学与大数据技术 基于深度学习的零售库存预测补货系统设计4.27-AI4.18_1.docx(2.82 MB)预览内容
  • OnlineRetail1.csv(44 MB)
  • readme.txt(3.87 KB)预览内容
CAD预览不完整,只显示大致框架 可联系客服看全图和细节

1、当您付费下载文档后,您只拥有了使用权限,并不意味着购买了版权,文档只能用于自身使用.。
2、本站所有内容均由合作方或网友上传,本站不对文档的完整性、权威性及其观点立场正确性做任何保证或承诺!文档内容仅供研究参考,付费前请自行鉴别。
3、如文档内容存在违规,或者侵犯商业秘密、侵犯著作权等,请点击“违规举报”。

碎片内容

2026数据科学与大数据技术一套 基于深度学习的零售库存预测补货系统设计4.27-AI4.18(论文+前后端程序代码源码+数据库源数据表+运行说明)定稿.zip

您可能关注的文档

发表评论取消回复

  
专业设计+ 关注
机构认证
内容提供者

该用户很懒,什么也没介绍

确认删除?
qq
  • 联系点击这里给我发消息
搜索教程
联系客服
  • 联系客服
回到顶部