Hypertuned temporal fusion transformer for multi-horizon time series forecasting of dam level in hydroelectric power plants

This paper addresses the challenge of predicting dam level rise in hydroelectric power plants during floods and proposes a solution using an automatic hyperparameters tuning temporal fusion transformer (AutoTFT) model. Hydroelectric power plants play a critical role in long-term energy planning, and accurate prediction of dam level rise is crucial for maintaining operational safety and optimizing energy generation. The AutoTFT model is applied to analyze time series data representing the water storage capacity of a hydroelectric power plant, providing valuable insights for decision-making in emergency situations. The results demonstrate that the AutoTFT model surpasses other deep learning approaches, achieving high accuracy in predicting dam level rise across different prediction horizons. Having a root mean square error (RMSE) of 2.78×10−3 for short-term forecasting and 1.72 considering median-term forecasting, the AutoTFT shows to be promising for time series prediction presented in this paper. The AutoTFT had lower RMSE than the adaptive neuro-fuzzy inference system, long short-term memory, bootstrap aggregation (bagged), sequential learning (boosted), and stacked generalization ensemble learning approaches. The findings underscore the potential of the AutoTFT model for improving operational efficiency, ensuring safety, and optimizing energy generation in hydroelectric power plants during flood events

Star-forming dwarf galaxies in the Virgo cluster: the link between molecular gas, atomic gas, and dust

We present $^{12}$CO(1-0) and $^{12}$CO(2-1) observations of a sample of 20 star-forming dwarfs selected from the Herschel Virgo Cluster Survey, with oxygen abundances ranging from 12 + log(O/H) ~ 8.1 to 8.8. CO emission is observed in ten galaxies and marginally detected in another one. CO fluxes correlate with the FIR 250 $\mu$m emission, and the dwarfs follow the same linear relation that holds for more massive spiral galaxies extended to a wider dynamical range. We compare different methods to estimate H2 molecular masses, namely a metallicity-dependent CO-to-H2 conversion factor and one dependent on H-band luminosity. The molecular-to-stellar mass ratio remains nearly constant at stellar masses <~ 10$^9$ M$_{\odot}$, contrary to the atomic hydrogen fraction, M$_{HI}$/M$_*$, which increases inversely with M$_*$. The flattening of the M$_{H_2}$/M$_*$ ratio at low stellar masses does not seem to be related to the effects of the cluster environment because it occurs for both HI-deficient and HI-normal dwarfs. The molecular-to-atomic ratio is more tightly correlated with stellar surface density than metallicity, confirming that the interstellar gas pressure plays a key role in determining the balance between the two gaseous components of the interstellar medium. Virgo dwarfs follow the same linear trend between molecular gas mass and star formation rate as more massive spirals, but gas depletion timescales, $\tau_{dep}$, are not constant and range between 100 Myr and 6 Gyr. The interaction with the Virgo cluster environment is removing the atomic gas and dust components of the dwarfs, but the molecular gas appears to be less affected at the current stage of evolution within the cluster. However, the correlation between HI deficiency and the molecular gas depletion time suggests that the lack of gas replenishment from the outer regions of the disc is lowering the star formation activity.Comment: 19 pages, 11 figures, accepted for publication in Astronomy & Astrophysic

Water use efficiency in bananas pome type cropsusing empirical coefficient based on leaf area.

The aim of this work was to evaluate the yield and water use efficiency (WUE) of banana ?Prata-Anã? (AAB) and ?BRS Platina? (AAAB) during two cycles of production in a semi-arid climate of Brazil (classified as Aw according Köppen)

PH e condutividade elétrica do solo sob lâminas de irrigação e doses de adubação nitrogenada em bananeira.

O nitrogênio é um dos nutrientes mais necessários ao bom desenvolvimento e produção da bananeira. A adubação nitrogenada pode ser preparada por fontes de sais inorgânicos rapidamente disponíveis como o amônio, o nitrato e a uréia. A utilização da uréia pelos produtores se traduz pelo menor custo que esses fertilizantes possuem, porém, a possibilidade de aumento da acidez do solo, ou seja, a redução do pH e da saturação de base se tornam aspectos indesejados na aplicação desse fertilizante. Nas condições irrigadas, pode haver interações entre os níveis de água aplicados e as dosagens de adubos, fazendo com que o pH do solo e os níveis de condutividade elétrica (CE) do solo apresentem diferentes comportamentos em relação as condição de sequeiro. Além disso, a CE está relacionada ao conteúdo de água presente no solo, sendo que sua alteração está relacionada à diluição dos sais da solução. O objetivo do trabalho foi avaliar o comportamento do pH do solo e da CE do extrato de saturação ao longo do segundo ciclo da bananeira BRS Tropical com três doses de uréia sob quatro lâminas de irrigação nas condições edafoclimáticas do projeto Gorutuba, Norte de Minas.PDF. 097

Regressão linear para predição do estado nutricional de bananeiras tipo prata.

A avaliação do estado nutricional de bananeiras é fundamental para recomendação de adubação e manejo da cultura. Diversos métodos analíticos são utilizados, mas a segurança dos dados e a demora para a obtenção dos resultados dificulta a tomada de decisão que favorece o aparecimento de sintomas de deficiência e consequente queda de produtividade da lavoura