文件名称：Power-Consumption-Prediction-master.rar
文件大小：17.89MB
文件格式：RAR
更新时间：2022-07-11 03:31:16
天池ai 电力 负荷预测
完整数据和完整代码
【文件预览】：
Power-Consumption-Prediction-master
----feature.csv(304KB)
----.spyproject()
--------codestyle.ini(58B)
--------encoding.ini(60B)
--------vcs.ini(87B)
--------workspace.ini(665B)
----seq2order(8KB)
----Clustering_Analysis.ipynb(1KB)
----mlp_power_prediction.py(3KB)
----rfregression.py(4KB)
----ann_mlp.py(8KB)
----create_dataset.py(6KB)
----arima.py(2KB)
----Reference()
--------BussetiOsbandWong-DeepLearningForTimeSeriesModeling.pdf(769KB)
--------Probabilistic energy forecasting_ Global Energy Forecasting Competition 2014 and beyond.pdf(2.19MB)
--------Derivative Dynamic Time Warping.pdf(138KB)
--------2012-A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition.pdf(894KB)
--------2015-Time-series clustering – A decade review.pdf(1.21MB)
--------Clustering of time series data—a survey.pdf(323KB)
--------Weighted dynamic time warping for time series classification.pdf(828KB)
--------2016-Time series k-means_ A new k-means type smooth subspace clustering for time series data.pdf(1.04MB)
--------Long-term prediction of time series by combining direct and MIMO strategies.pdf(205KB)
--------GEFCom2014 probabilistic electric load forecasting An integrated solution.pdf(973KB)
--------Correlation-based-dynamic-time-warping-of-multiv_2012_Expert-Systems-with-Ap.pdf(819KB)
--------2013-Machine Learning Strategies for Time Series Forecasting.pdf(253KB)
--------A-global-averaging-method-for-dynamic-time-warping--with-_2011_Pattern-Recog.pdf(2.49MB)
--------Analysis of Similarity Measures in Times Series Clustering for the Discovery of Building Energy Patterns.pdf(3.2MB)
----power_prediction.py(8KB)
----Explore_Analysis()
--------feature_explore.py(3KB)
--------explore_analysis.py(3KB)
--------explore.py(5KB)
----lazzy.py(10KB)
----dynamic_time_warping.py(3KB)
----ann_smlp.py(6KB)
----.gitignore(649B)
----lazzy_decomposion.py(14KB)
----lazzy_improved.py(15KB)
----.ipynb_checkpoints()
--------Clustering_Analysis-checkpoint.ipynb(72B)
----README.md(286B)
----csv_tansform.py(542B)
----.gitattributes(378B)
----Data()
--------Tianchi_power_9.csv(758KB)
--------weather.csv(23KB)
--------Tianchi_power_prediction_analysis.xlsx(21KB)
--------Tianchi_power_predict_table_mlp.csv(557B)
--------Tianchi_power_predict_table_mlp_rec.csv(557B)
--------target.csv(249KB)
--------Tianchi_power_predict_table.csv(557B)
--------Tianchi_power_predict_table_real.csv(540B)
--------Tianchi_power.7z(1.89MB)
--------Tianchi_power.csv(15.05MB)