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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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Hassen Louati, Ali Louati, Rahma Lahyani, Elham Kariri and Abdullah Albanyan
Responding to the critical health crisis triggered by respiratory illnesses, notably COVID-19, this study introduces an innovative and resource-conscious methodology for analyzing chest X-ray images. We unveil a cutting-edge technique that marries neural...
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Enrique González-Núñez, Luis A. Trejo and Michael Kampouridis
This research aims at applying the Artificial Organic Network (AON), a nature-inspired, supervised, metaheuristic machine learning framework, to develop a new algorithm based on this machine learning class. The focus of the new algorithm is to model and ...
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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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Feng Cheng, Shuchun Jia and Wei Gao
In order to tackle the issue of carbon emissions in logistics and distribution, a vehicle routing model was proposed with the aim of minimizing the overall cost, which includes the vehicle?s fixed cost, transportation costs, and carbon emission costs. An...
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Jianying Wei, Yuming Liu, Xiaochun Lu, Yu Feng and Yadi Wang
Tunnel construction projects are a classic type of repetitive project, and hold a crucial position in the construction industry. The linear scheduling method (LSM) has been in the spotlight in scheduling optimization for repetitive construction projects ...
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Tahsin Koroglu and Elanur Ekici
In recent years, wind energy has become remarkably popular among renewable energy sources due to its low installation costs and easy maintenance. Having high energy potential is of great importance in the selection of regions where wind energy investment...
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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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María Elena Tejeda-del-Cueto, Manuel Alberto Flores-Alfaro, Miguel Toledo-Velázquez, Lorena del Carmen Santos-Cortes, José Hernández-Hernández and Marco Osvaldo Vigueras-Zúñiga
The objective of this study is to develop a genetic algorithm that uses the IGP parameterization to increase the lift coefficient (CL) of three airfoils to be used on wings of unmanned aerial vehicles (UAVs). The geometry of three baseline airfoils was m...
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Shuling Zhao and Sishuo Zhao
Due to the intensification of economic globalization and the impact of global warming, the development of methods to reduce shipping costs and reduce carbon emissions has become crucial. In this study, a multi-objective optimization algorithm was designe...
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