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Rafael Lahoz-Beltra
Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc. and population dynamical proce...
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Ioannis G. Tsoulos, Alexandros Tzallas and Evangelos Karvounis
Radial basis function networks are widely used in a multitude of applications in various scientific areas in both classification and data fitting problems. These networks deal with the above problems by adjusting their parameters through various optimiza...
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Jalal Al-Afandi and András Horváth
Genetic Algorithms are stochastic optimization methods where solution candidates, complying to a specific problem representation, are evaluated according to a predefined fitness function. These approaches can provide solutions in various tasks even, wher...
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Rubén Ferrero-Guillén, Javier Díez-González, Paula Verde, Rubén Álvarez and Hilde Perez
The obtainment of a methodology for maximizing the social distancing by increasing the distance among the school desks in the classrooms during the coronavirus pandemic through a Genetic Algorithm optimization.
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Juan Murillo-Morera, Carlos Castro-Herrera, Javier Arroyo, Ruben Fuentes-Fernandez
Pág. 114 - 137
Today, it is common for software projects to collect measurement data through development processes. With these data, defect prediction software can try to estimate the defect proneness of a software module, with the objective of assisting and guiding so...
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Raymundo Peña-García, Rodolfo Daniel Velázquez-Sánchez, Cristian Gómez-Daza-Argumedo, Jonathan Omega Escobedo-Alva, Ricardo Tapia-Herrera and Jesús Alberto Meda-Campaña
This research introduces a physics-based identification technique utilizing genetic algorithms. The primary objective is to derive a parametric matrix, denoted as A, describing the time-invariant linear model governing the longitudinal dynamics of an air...
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Esra?a Alkafaween, Ahmad Hassanat, Ehab Essa and Samir Elmougy
The genetic algorithm (GA) is a well-known metaheuristic approach for dealing with complex problems with a wide search space. In genetic algorithms (GAs), the quality of individuals in the initial population is important in determining the final optimal ...
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Kevin Mero, Nelson Salgado, Jaime Meza, Janeth Pacheco-Delgado and Sebastián Ventura
Unemployment, a significant economic and social challenge, triggers repercussions that affect individual workers and companies, generating a national economic impact. Forecasting the unemployment rate becomes essential for policymakers, allowing them to ...
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Jose A. Montenegro and Antonio Muñoz
In this manuscript, we present EventGeoScout, an innovative framework for collaborative geographic information management, tailored to meet the needs of the dynamically changing landscape of geographic data integration and quality enhancement. EventGeoSc...
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Mohamed A. Damos, Jun Zhu, Weilian Li, Elhadi Khalifa, Abubakr Hassan, Rashad Elhabob, Alaa Hm and Esra Ei
Social media platforms play a vital role in determining valuable tourist objectives, which greatly aids in optimizing tourist path planning. As data classification and analysis methods have advanced, machine learning (ML) algorithms such as the k-means a...
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Michael van de Noort and Peter T. Ireland
Double-Wall Effusion Cooling schemes present an opportunity for aeroengine designers to achieve high overall cooling effectiveness and convective cooling efficiency in High-Pressure Turbine blades with reduced coolant usage compared to conventional cooli...
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Parag C. Pendharkar
This paper proposes a genetic algorithm-based Markov Chain approach that can be used for non-parametric estimation of regression coefficients and their statistical confidence bounds. The proposed approach can generate samples from an unknown probability ...
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Mukhtar Zhassuzak, Marat Akhmet, Yedilkhan Amirgaliyev and Zholdas Buribayev
Unpredictable strings are sequences of data with complex and erratic behavior, which makes them an object of interest in various scientific fields. Unpredictable strings related to chaos theory was investigated using a genetic algorithm. This paper prese...
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Ioannis G. Tsoulos and V. N. Stavrou
In the current research, we consider the solution of dispersion relations addressed to solid state physics by using artificial neural networks (ANNs). Most specifically, in a double semiconductor heterostructure, we theoretically investigate the dispersi...
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Panagiotis Farmakis, Athanasios Chassiakos and Stylianos Karatzas
Hub-and-Spoke (H&S) network modeling is a form of transport topology optimization in which network joins are connected through intermediate hub nodes. The Short Sea Shipping (SSS) problem aims to efficiently disperse passenger flows involving multipl...
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Furkan Rabee and Zahir M. Hussain
Optimization using genetic algorithms (GA) is a well-known strategy in several scientific disciplines. The crossover is an essential operator of the genetic algorithm. It has been an active area of research to develop sustainable forms for this operand. ...
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Alessia Donato and David Carfì
In this paper, we propose a new method of optimization based on genetic algorithms using the MATLAB toolbox ?Global Optimization?. The algorithm finds layers moduli of a flexible pavement through the measurement of pavement surface deflections under assi...
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Sevilay Kilmen and Okan Bulut
Psychological scales play a key role in the assessment, screening, and diagnosis of latent variables, such as emotions, mental health, and well-being. In practice, researchers need shorter scales of psychological traits to save administration time and co...
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Alexandru-Razvan Manescu and Bogdan Dumitrescu
In this paper, a novel global optimization approach in the form of an adaptive hyper-heuristic, namely HyperDE, is proposed. As the naming suggests, the method is based on the Differential Evolution (DE) heuristic, which is a well-established optimizatio...
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Ioannis G. Tsoulos and Vasileios Charilogis
In the present work, an innovative two-phase method is presented for parameter tuning in radial basis function artificial neural networks. These kinds of machine learning models find application in many scientific fields in classification problems or in ...
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