Computational intelligence methods in simulation and modeling of structures: A state-of-the-art review using bibliometric maps
The modeling and simulation of structural systems is a task that requires high precision and
reliable results to ensure the stability and safety of construction projects of all kinds. For …
reliable results to ensure the stability and safety of construction projects of all kinds. For …
Bibliometric literature review of adaptive learning systems
In this review paper, we computationally analyze a vast volume of published articles in the
field of Adaptive Learning, as obtained by the Scopus Database. Particularly, we use a …
field of Adaptive Learning, as obtained by the Scopus Database. Particularly, we use a …
Use of artificial intelligence for predicting parameters of sustainable concrete and raw ingredient effects and interactions
Incorporating waste material, such as recycled coarse aggregate concrete (RCAC), into
construction material can reduce environmental pollution. It is also well-known that the …
construction material can reduce environmental pollution. It is also well-known that the …
A general framework of high-performance machine learning algorithms: application in structural mechanics
Data-driven models utilizing powerful artificial intelligence (AI) algorithms have been
implemented over the past two decades in different fields of simulation-based engineering …
implemented over the past two decades in different fields of simulation-based engineering …
A collection of 30 multidimensional functions for global optimization benchmarking
A collection of thirty mathematical functions that can be used for optimization purposes is
presented and investigated in detail. The functions are defined in multiple dimensions, for …
presented and investigated in detail. The functions are defined in multiple dimensions, for …
NPROS: a not so pure random orthogonal search algorithm—a suite of random optimization algorithms driven by reinforcement learning
We live in a world where waves of novel nature-inspired metaheuristic algorithms keep
hitting the shore repeatedly. This never-ending surge of new metaheuristic algorithms is …
hitting the shore repeatedly. This never-ending surge of new metaheuristic algorithms is …
A majority–minority cellular automata algorithm for global optimization
Cellular automata (CA) are discrete dynamical systems that can give rise to complex
behaviors under certain conditions. Its operation is based on simple local interactions …
behaviors under certain conditions. Its operation is based on simple local interactions …
Pure random search with virtual extension of feasible region
EA Tsvetkov, RA Krymov - Journal of Optimization Theory and Applications, 2022 - Springer
We propose a modification of the pure random search algorithm for cases when the global
optimum point can be located near the boundary of a feasible region. If the feasible region is …
optimum point can be located near the boundary of a feasible region. If the feasible region is …
A New Algorithm Inspired on Reversible Elementary Cellular Automata for Global Optimization
JC Seck-Tuoh-Mora, O Lopez-Arias… - IEEE …, 2022 - ieeexplore.ieee.org
This work presents a new global optimization algorithm of functions inspired by the dynamic
behavior of reversible cellular automata, denominated Reversible Elementary Cellular …
behavior of reversible cellular automata, denominated Reversible Elementary Cellular …
Random orthogonal search with triangular and quadratic distributions (TROS and QROS): parameterless algorithms for global optimization
In this paper, the behavior and performance of Pure Random Orthogonal Search (PROS), a
parameter-free evolutionary algorithm (EA) that outperforms many existing EAs on the well …
parameter-free evolutionary algorithm (EA) that outperforms many existing EAs on the well …