Storm water management model: Performance review and gap analysis
The storm water management model (SWMM) is a widely used tool for urban drainage
design and planning. Hundreds of peer-reviewed articles and conference proceedings have …
design and planning. Hundreds of peer-reviewed articles and conference proceedings have …
Adaptive neuro-fuzzy approach for solar radiation prediction in Nigeria
In this paper, the accuracy of a soft computing technique is investigated for predicting solar
radiation based on a series of measured meteorological data: monthly mean minimum …
radiation based on a series of measured meteorological data: monthly mean minimum …
Short-term runoff prediction with GRU and LSTM networks without requiring time step optimization during sample generation
Runoff forecasting is an important approach for flood mitigation. Many machine learning
models have been proposed for runoff forecasting in recent years. To reconstruct the time …
models have been proposed for runoff forecasting in recent years. To reconstruct the time …
Deep learning with a long short-term memory networks approach for rainfall-runoff simulation
C Hu, Q Wu, H Li, S Jian, N Li, Z Lou - Water, 2018 - mdpi.com
Considering the high random and non-static property of the rainfall-runoff process, lots of
models are being developed in order to learn about such a complex phenomenon. Recently …
models are being developed in order to learn about such a complex phenomenon. Recently …
Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
Accurate runoff estimation is crucial for optimal reservoir operation and irrigation purposes.
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
A GIS-based flood susceptibility assessment and its map** in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with …
Flood is one of the most prevalent natural disasters that frequently occur in the northern part
of Iran reported in hot spots of flood occurrences. The main aim of the current study was to …
of Iran reported in hot spots of flood occurrences. The main aim of the current study was to …
Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method
Flood is one of the most commonly occurred natural hazards worldwide. Severe flood
occurrences in Kelantan, Malaysia cause damage to both life and property every year. Due …
occurrences in Kelantan, Malaysia cause damage to both life and property every year. Due …
[HTML][HTML] A conceptual metaheuristic-based framework for improving runoff time series simulation in glacierized catchments
Glacio-hydrological modeling is a key task for assessing the influence of snow and glaciers
on water resources, essential for water resources management. The present study aims to …
on water resources, essential for water resources management. The present study aims to …
Flood susceptibility analysis through remote sensing, GIS and frequency ratio model
S Samanta, DK Pal, B Palsamanta - Applied Water Science, 2018 - Springer
Abstract Papua New Guinea (PNG) is saddled with frequent natural disasters like
earthquake, volcanic eruption, landslide, drought, flood etc. Flood, as a hydrological disaster …
earthquake, volcanic eruption, landslide, drought, flood etc. Flood, as a hydrological disaster …
Prediction of rainfall time series using modular soft computingmethods
CL Wu, KW Chau - Engineering applications of artificial intelligence, 2013 - Elsevier
In this paper, several soft computing approaches were employed for rainfall prediction. Two
aspects were considered to improve the accuracy of rainfall prediction:(1) carrying out a data …
aspects were considered to improve the accuracy of rainfall prediction:(1) carrying out a data …