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Evolutionary multi-objective design of autoencoder for compact representation of histopathology images
(2021-08-01)
Deep learning can cope with complex tasks; however, it suffers from the crucial problem of high dimensionality which makes it intractable to learn the patterns and classify the data. Importantly, having a fixed model cannot ...
Leadership based multi-objective optimization with applications in energy systems.
(2013-12-01)
Multi-objective optimization metaheuristics (MOMs) are powerful methods for solving complex optimization problems but can require a large number of function evaluations to find optimal solutions. Thus, an efficient ...
Robust controller design for active trailer steering systems of articulated vehicles using multi-objective optimization
(2019-08-01)
This thesis presents and evaluates an approach to the robust controller design for active trailer steering (ATS) systems to increase the safety of articulated vehicles. By applying a multi-objective evolutionary algorithm ...
Optimal vehicle structural design for weight reduction using iterative finite element analysis
(2012-06-01)
The design and analysis of an automotive structure is an important stage of the vehicle design process. The structural characteristics have significant impact on the vehicle performance. During the design process it is ...
Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization
(2015-04-01)
To acquire the maximum efficiency for solar electricity conversion, a solar panel has to absorb nearly every single photon of light emitted from the sun. The shape of the solar panel itself plays an important role in ...
Development and modeling of a lab-scale integrated copper-chlorine cycle for hydrogen production
(2020-08-01)
Hydrogen is one of the most important energy carriers, clean fuels, and storage media in the upcoming future. Hydrogen production through the thermochemical copper-chlorine (Cu-Cl) cycle is one of the most promising methods ...
Enhancing meta-heuristic algorithms using center-based sampling at population level
(2023-11-01)
In recent years, center-based sampling has demonstrated impressive results to enhance the efficiency and effectiveness of meta-heuristic algorithms. The strategy of center-based sampling can be utilized at either the ...
Improving binary optimization algorithms using genuine uniform initialization
(2023-12-01)
Population-based metaheuristic algorithms play a crucial role in solving complex optimization problems. The effectiveness of these algorithms is significantly influenced by the initial population of candidate solutions. ...
Optimized clean hydrogen production using nuclear small modular reactor and concentrated solar power as a renewable energy source
(2022-12-01)
According to current predictions, hydrogen will serve as a key fuel and energy source by decreasing greenhouse gas (GHG) emissions. In this research an integral Pressurized Water Reactor-type Small Modular Reactor (iPWR-type ...