DM test results of different models for forecasting.
<p>DM test results of different models for forecasting.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
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| _version_ | 1852019491059269632 |
|---|---|
| author | Chengjin Yang (16464079) |
| author2 | Yanzhong Zhai (21511941) Zehua Liu (3919058) |
| author2_role | author author |
| author_facet | Chengjin Yang (16464079) Yanzhong Zhai (21511941) Zehua Liu (3919058) |
| author_role | author |
| dc.creator.none.fl_str_mv | Chengjin Yang (16464079) Yanzhong Zhai (21511941) Zehua Liu (3919058) |
| dc.date.none.fl_str_mv | 2025-06-09T17:32:11Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0323714.t006 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/DM_test_results_of_different_models_for_forecasting_/29271657 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biochemistry Biotechnology Science Policy Infectious Diseases Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified sustainable agricultural practices series denoising method module wavelet transform maize price volatility generate attention vectors convolutional enhancement network china &# 8217 key temporal features input features along five major corn corn price forecasting paper effectively captures term memory network term memory capabilities unique bidirectional structure corn price data improve prediction accuracy accurately predicting short data fully demonstrate local features corn sector corn prices prediction accuracy effectively separating accurately extracts term trends term dependencies data complexity bidirectional time bidirectional processing xlink "> trend information thereby enhancing signal details r2 values producing regions planting decisions multiple scales mse values mape values mae values increase uncertainty income stability filter time factors jeopardize extensive experimentation excellent performance different datasets dataset utilized complex dependencies |
| dc.title.none.fl_str_mv | DM test results of different models for forecasting. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>DM test results of different models for forecasting.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_99e24fa4b9f526edb2140df9ee6bc069 |
| identifier_str_mv | 10.1371/journal.pone.0323714.t006 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29271657 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | DM test results of different models for forecasting.Chengjin Yang (16464079)Yanzhong Zhai (21511941)Zehua Liu (3919058)BiochemistryBiotechnologyScience PolicyInfectious DiseasesPlant BiologyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedsustainable agricultural practicesseries denoising methodmodule wavelet transformmaize price volatilitygenerate attention vectorsconvolutional enhancement networkchina &# 8217key temporal featuresinput features alongfive major corncorn price forecastingpaper effectively capturesterm memory networkterm memory capabilitiesunique bidirectional structurecorn price dataimprove prediction accuracyaccurately predicting shortdata fully demonstratelocal featurescorn sectorcorn pricesprediction accuracyeffectively separatingaccurately extractsterm trendsterm dependenciesdata complexitybidirectional timebidirectional processingxlink ">trend informationthereby enhancingsignal detailsr2 valuesproducing regionsplanting decisionsmultiple scalesmse valuesmape valuesmae valuesincrease uncertaintyincome stabilityfilter timefactors jeopardizeextensive experimentationexcellent performancedifferent datasetsdataset utilizedcomplex dependencies<p>DM test results of different models for forecasting.</p>2025-06-09T17:32:11ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0323714.t006https://figshare.com/articles/dataset/DM_test_results_of_different_models_for_forecasting_/29271657CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/292716572025-06-09T17:32:11Z |
| spellingShingle | DM test results of different models for forecasting. Chengjin Yang (16464079) Biochemistry Biotechnology Science Policy Infectious Diseases Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified sustainable agricultural practices series denoising method module wavelet transform maize price volatility generate attention vectors convolutional enhancement network china &# 8217 key temporal features input features along five major corn corn price forecasting paper effectively captures term memory network term memory capabilities unique bidirectional structure corn price data improve prediction accuracy accurately predicting short data fully demonstrate local features corn sector corn prices prediction accuracy effectively separating accurately extracts term trends term dependencies data complexity bidirectional time bidirectional processing xlink "> trend information thereby enhancing signal details r2 values producing regions planting decisions multiple scales mse values mape values mae values increase uncertainty income stability filter time factors jeopardize extensive experimentation excellent performance different datasets dataset utilized complex dependencies |
| status_str | publishedVersion |
| title | DM test results of different models for forecasting. |
| title_full | DM test results of different models for forecasting. |
| title_fullStr | DM test results of different models for forecasting. |
| title_full_unstemmed | DM test results of different models for forecasting. |
| title_short | DM test results of different models for forecasting. |
| title_sort | DM test results of different models for forecasting. |
| topic | Biochemistry Biotechnology Science Policy Infectious Diseases Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified sustainable agricultural practices series denoising method module wavelet transform maize price volatility generate attention vectors convolutional enhancement network china &# 8217 key temporal features input features along five major corn corn price forecasting paper effectively captures term memory network term memory capabilities unique bidirectional structure corn price data improve prediction accuracy accurately predicting short data fully demonstrate local features corn sector corn prices prediction accuracy effectively separating accurately extracts term trends term dependencies data complexity bidirectional time bidirectional processing xlink "> trend information thereby enhancing signal details r2 values producing regions planting decisions multiple scales mse values mape values mae values increase uncertainty income stability filter time factors jeopardize extensive experimentation excellent performance different datasets dataset utilized complex dependencies |