911 to 920 of 3,851 Results
Jun 23, 2025 -
Conjunto de dados referente à pesquisa de simulação de produção e purificação de biolubrificantes por meio de destilação molecular
Tabular Data - 538 B - 5 Variables, 6 Observations - UNF:6:ICd8mx1ufTXN2cXXL89mzQ==
Dados de emulação da Destilação molecular no Aspen Plus para duas misturas binárias (DBP/DBS) e (DEHP/DEHS). |
Jun 23, 2025 -
Conjunto de dados referente à pesquisa de simulação de produção e purificação de biolubrificantes por meio de destilação molecular
Tabular Data - 1.1 KB - 11 Variables, 16 Observations - UNF:6:TLsDo60lBp+k8xLfeJRIFg==
Estimativa de propriedades termodinamicas por contribuição de grupo para os biolubrificantes |
Jun 20, 2025
Reis, Julio Cesar dos; Regino, André Gomes; Rossanez, Anderson, 2025, "KGevol: grafos de conhecimento dinâmicos extraídos de informação textual não estruturada", https://doi.org/10.25824/redu/TLQCEY, Repositório de Dados de Pesquisa da Unicamp, V1
Datasets related to the research project KGevol: dynamic knowledge graphs extracted from unstructured textual information. This project studied novel methods to represent knowledge conveyed in textual documents. Our investigation characterized the evolution of facts extracted fro... |
Almeida, Iago Oliveira de; Mereles, Arthur Guilherme; Okabe, Eduardo Paiva; Dedini, Katia Lucchesi Cavalca; Daniel, Gregory Bregion, 2025, "Lamar dataset: a study on rotating machinery failures", https://doi.org/10.25824/redu/HRCMHE, Repositório de Dados de Pesquisa da Unicamp, V2
The dataset was collected in February 2024 at the Rotating Machinery Laboratory (LAMAR from Portuguese, Laboratório de Máquinas Rotativas) in the School of Mechanical Engineering at the State University of Campinas. It provides experimental observations of common faults in rotors... |
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Jun 20, 2025 -
Lamar dataset: a study on rotating machinery failures
Adobe PDF - 383.4 KB -
MD5: 73f4cb693d25968660cadee1dd465b5a
Instructions |
Jun 20, 2025 -
Experimental database of pressure and void waves in a transient vertical air-water flow
ZIP Archive - 8.9 GB -
MD5: bc7cead70e6a0431356ecd16f5b6e8d4
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Jun 16, 2025
Silva, Leonardo Rodrigues da; Coelho, Guilherme Palermo, 2025, "Replication data for: study of economic variables for stock market trend prediction via machine learning", https://doi.org/10.25824/redu/LISCF2, Repositório de Dados de Pesquisa da Unicamp, V1
This package contains the input datasets, experimental results, and source codes developed during the scientific initiation research project entitled Study of Economic Variables for Stock Market Trend Prediction via Machine Learning, funded by FAPESP and conducted at the Universi... |
Jun 16, 2025 -
Replication data for: study of economic variables for stock market trend prediction via machine learning
ZIP Archive - 697.2 KB -
MD5: 967fad1223d8f42d2111cdb116f85237
This file contains all the input datasets used throughout the research. This includes historical stock price data (obtained via the Yahoo Finance API), macroeconomic indicators (e.g., SELIC, IPCA, PIB), and microeconomic indicators (e.g., ROE, P/L, VPA) used as features in the ma... |
Jun 16, 2025 -
Replication data for: study of economic variables for stock market trend prediction via machine learning
ZIP Archive - 5.2 MB -
MD5: cb3df9d7e614021508d84a5cdd2bf77f
This file includes the complete experimental results, such as model evaluation metrics (MAE, MSE, RMSE, R²), prediction graphs, comparison tables of different strategies (including the proposed method and the buy-and-hold approach), and return simulations. |
Jun 16, 2025 -
Replication data for: study of economic variables for stock market trend prediction via machine learning
ZIP Archive - 1.2 MB -
MD5: 1800f98e377aff63bc375fe8f47648ea
This file contains all the Python source codes used in the study. |
