A deep recurrent neural network with long short-term memory units (DRNN-LSTM) model is
developed to forecast aggregated power load and the photovoltaic (PV) power output in …

Titanium is an ideal material choice for orthopaedic and dental implants, and hence a
significant amount of research has been focused towards augmenting the therapeutic …

The key challenge of expensive optimization problems (EOP) is that evaluating the true
fitness value of the solution is computationally expensive. A common method to deal with …

Nanomedicine has seen a significant rise in the development of new research tools and
clinically functional devices. In this regard, significant advances and new commercial …

Advances in dataset collection and machine learning (ML) algorithms are important
contributors to the stability analysis in industrial engineering, especially to slope stability …

Hybrid renewable system is a particular type of energy systems which can be used as
Distributed Generation (DG) resources to reduce network losses and increase its efficiency …

This paper presents a new integrated model predictive control (IMPC) method that combines
power management and adaptive velocity control during vehicle-following scenarios in …

Distribution of products throughout a supply chain could be managed via multimodal
transportation networks. This will be more likely in long-haul transportation where a decision …

This paper proposes rain-fall optimization algorithm (RFO), a new nature-inspired algorithm
based on behavior of raindrops, for solving of real-valued numerical optimization problems …

This study formulates the effects of two different historical data types on electrical energy
consumption of ASEAN-5 counties. On this basis, optimized GEP (gene expression …