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An evolutionary algorithm of linear complexity: application to training of de...
The performance of deep neural networks, such as Deep Belief Networks formed by Restricted Boltzmann Machines (RBMs), strongly depends on their training, which is the process of... -
Computation of the improvement directions of the Pareto front and its applica...
This paper introduces the mathematical development and algorithm of the Improvement-Directions Mapping (IDM) method, which computes improvement directions to "push" the current... -
The improvement direction mapping method
The Improvement Direction Mapping (IDM) is a novel multi-objective local-search method, that independently steers a solution set towards promising regions by computing... -
A two-stage mono-and multi-objective method for the optimization of general U...
This paper introduces a two-stage method based on bio-inspired algorithms for the design optimization of a class of general Stewart platforms. The first stage performs a... -
Parameter Calibration of the Patch Growing Algorithm for Urban Land Change Si...
Urban growth modelling is a current trend in geo-computation due to its impact on the local living environment and the quality of life. The FUTure Urban-Regional Environment... -
Mechatronic design of a planar robot using multiobjective optimization
The concurrent design optimization of robots refers to the problem of optimizing parameters that affects different kinds of features at the same time. For instance, this work... -
A self-validating method via the unification of multiple models for consisten...
Mathematical models are used for simulating the electrochemical phenomena of proton-exchange-membrane (PEM) fuel cells. They differ in the scale, modeling variables, precision... -
A reaction–convection–diffusion model for PEM fuel cells
In this paper, we present a novel 1D singularly perturbed reaction–convection–diffusion mathematical model, with non-linear coefficients (SP-RCD model), for the physical... -
A Broyden-based algorithm for multi-objective local-search optimization
In multi-objective optimization, the direction vectors in the objective space that improve the current non-dominated set are named improvement directions. The Improvement... -
Roughness Parameter Estimation for flood numerical simulation using Different...
A methodology to estimate parameters necessary to carry out numerical simulations of flood phenomena is presented, that may be useful for detecting flood-prone areas. Geospatial... -
Design optimization and parameter estimation of a PEMFC using nature-inspired...
With the increasing demand for electrical energy and the challenges related to its production, along with the need to be environmentally friendly to achieve sustainability for... -
The directed multi-objective estimation distribution algorithm (D-MOEDA)
Improvement Direction Mapping (IDM) methods have been applied as a local search strategy to hybridize global search algorithms. A natural question is whether this concept could... -
Enhancing Epidemic Prediction Using Simulated Annealing for Parameter Optimiz...
Understanding and predicting outbreaks of epidemics has become a major focus since COVID-19. Researchers have explored various methods, from basic curve fitting to complex...
