River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …

This paper focuses on the development of shallow and deep neural networks in the form of
multi-layer perceptron, long-short term memory, and gated recurrent unit to model the short …

In recent years, the Mekong River Basin (MRB), one of the largest river basins in Southeast
Asia, has experienced severe impacts from extreme droughts and floods. Streamflow …

The advent of smart grid technologies has facilitated the integration of new and intermittent
renewable forms of electricity generation in power systems. Advancements are driving …

Many methods used for secret data steganography are based on least significant bit method,
which is suffering from security and the embedded message can be easily hacked. In this …

Electricity generation in Brazil heavily depends on hydroelectric power, making it vulnerable
to fluctuations due to its reliance on weather patterns. Accurately forecasting water inflow …

The operational rule curve is significant for proper reservoir operations and water resources
management of the dam. The optimisation of the release policy is rather a complicated and …

Abstract Decision Support Indicators (DSIs) are metrics designed to inform local and
regional stakeholders about the characteristics of a predicted (or ongoing) event to facilitate …

This work proposes an analytical decision-making framework considering scenario
generation using artificial neural networks and risk-averse stochastic programming to define …

Streamflow forecasting plays a crucial role in the operational planning of hydro-dominant
power systems, providing valuable insights into future water inflows to reservoirs and …