The state of the art in deep learning applications, challenges, and future prospects: A comprehensive review of flood forecasting and management

V Kumar, HM Azamathulla, KV Sharma, DJ Mehta… - Sustainability, 2023 - mdpi.com
Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …

Wavelet-Seq2Seq-LSTM with attention for time series forecasting of level of dams in hydroelectric power plants

SF Stefenon, LO Seman, LS Aquino… - Energy, 2023 - Elsevier
Reservoir level control in hydroelectric power plants has importance for the stability of the
electric power supply over time and can be used for flood control. In this sense, this paper …

Hybrid Forecasting Methods—A Systematic Review

LB Sina, CA Secco, M Blazevic, K Nazemi - Electronics, 2023 - mdpi.com
Time series forecasting has been performed for decades in both science and industry. The
forecasting models have evolved steadily over time. Statistical methods have been used for …

A novel hybrid model combining βSARMA and LSTM for time series forecasting

B Kumar, N Yadav - Applied Soft Computing, 2023 - Elsevier
Time series forecasting is an important and active research area due to the significance of
prediction and decision-making in several applications. Most commonly used models for …

Water level forecasting using deep learning time-series analysis: A case study of red river of the north

V Atashi, HT Gorji, SM Shahabi, R Kardan, YH Lim - Water, 2022 - mdpi.com
The Red River of the North is vulnerable to floods, which have caused significant damage
and economic loss to inhabitants. A better capability in flood-event prediction is essential to …

Comparing three types of data-driven models for monthly evapotranspiration prediction under heterogeneous climatic conditions

P Aghelpour, V Varshavian, M Khodamorad Pour… - Scientific Reports, 2022 - nature.com
Evapotranspiration is one of the most important hydro-climatological components which
directly affects agricultural productions. Therefore, its forecasting is critical for water …

Hybrid Technique to Improve the River Water Level Forecasting Using Artificial Neural Network‐Based Marine Predators Algorithm

SJ Mohammed, SL Zubaidi, N Al-Ansari… - Advances in Civil …, 2022 - Wiley Online Library
Water level (WL) forecasting has become a difficult undertaking due to spatiotemporal
fluctuations in climatic factors and complex physical processes. This paper proposes a novel …

Binary coati optimization algorithm-multi-kernel least square support vector machine-extreme learning machine model (BCOA-MKLSSVM-ELM): a new hybrid …

SS Sammen, M Ehteram, Z Sheikh Khozani, LM Sidek - Water, 2023 - mdpi.com
Predicting reservoir water levels helps manage droughts and floods. Predicting reservoir
water level is complex because it depends on factors such as climate parameters and …

[PDF][PDF] An Exploration and Prediction of Rainfall and Groundwater Level for the District of Banaskantha, Gujrat, India

NN Maltare, D Sharma, S Patel - International Journal of …, 2023 - theaspd.com
The groundwater level is declining all over the world, especially in India. Some states, such
as Rajasthan and Gujarat, are experiencing very low levels of groundwater. In this study, we …

Desertification simulation using wavelet and box-jenkins time series analysis based on TGSI and albedo remote sensing indices

SH Geloogerdi, A Vali, MR Sharifi - Journal of Arid Environments, 2023 - Elsevier
Desertification has been listed as one of the most critical global environmental issues,
posing a significant threat to life, particularly in arid and semiarid regions. Therefore, gaining …