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Francisco Florez-Revuelta
This paper presents a new evolutionary approach, EvoSplit, for the distribution of multi-label data sets into disjoint subsets for supervised machine learning. Currently, data set providers either divide a data set randomly or using iterative stratificat...
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Francisco J. Soltero, Pablo Fernández-Blanco and J. Ignacio Hidalgo
Technical indicators use graphic representations of datasets by applying various mathematical formulas to financial time series of prices. These formulas comprise a set of rules and parameters whose values are not necessarily known and depend on many fac...
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Debalina Banerjee Chattapadhyay, Jagadeesh Putta and Rama Mohan Rao P
Risk identification and management are the two most important parts of construction project management. Better risk management can help in determining the future consequences, but identifying possible risk factors has a direct and indirect impact on the ...
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Uday K. Chakraborty
The Jaya algorithm is arguably one of the fastest-emerging metaheuristics amongst the newest members of the evolutionary computation family. The present paper proposes a new, improved Jaya algorithm by modifying the update strategies of the best and the ...
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Andrea Brunello, Enrico Marzano, Angelo Montanari and Guido Sciavicco
Temporal information plays a very important role in many analysis tasks, and can be encoded in at least two different ways. It can be modeled by discrete sequences of events as, for example, in the business intelligence domain, with the aim of tracking t...
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Rosa Senatore, Antonio Della Cioppa and Angelo Marcelli
Background: The use of Artificial Intelligence (AI) systems for automatic diagnoses is increasingly in the clinical field, being a useful support for the identification of several diseases. Nonetheless, the acceptance of AI-based diagnoses by the physici...
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Kleopatra Pirpinia, Peter A. N. Bosman, Jan-Jakob Sonke, Marcel van Herk and Tanja Alderliesten
Current state-of-the-art medical deformable image registration (DIR) methods optimize a weighted sum of key objectives of interest. Having a pre-determined weight combination that leads to high-quality results for any instance of a specific DIR problem (...
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Georgios K. Bekas and Georgios E. Stavroulakis
The present study investigates the potential of the implementation of machine learning techniques in optimized multi storey reinforced concrete frames. The variables that are taken into account in the objective function of the optimization problem are th...
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Georgios K. Bekas, Georgios E. Stavroulakis
Pág. 1 - 12
The present study investigates the potential of the implementation of machine learning techniques in optimized multi storey reinforced concrete frames. The variables that are taken into account in the objective function of the optimization problem are th...
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Ignacio Rodríguez-Rodríguez, José-Víctor Rodríguez, Domingo-Javier Pardo-Quiles, Purificación Heras-González and Ioannis Chatzigiannakis
Gender-Based Violence (GBV) is a serious problem that societies and governments must address using all applicable resources. This requires adequate planning in order to optimize both resources and budget, which demands a thorough understanding of the mag...
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Javier Sandoval
Pág. 125 - 133
Abstract AuthorsDownloadsReferencesHow to Cite
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Jayashree Piri, Puspanjali Mohapatra, Raghunath Dey, Biswaranjan Acharya, Vassilis C. Gerogiannis and Andreas Kanavos
The efficiency and the effectiveness of a machine learning (ML) model are greatly influenced by feature selection (FS), a crucial preprocessing step in machine learning that seeks out the ideal set of characteristics with the maximum accuracy possible. D...
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Derry Pramono Adi, Lukman Junaedi, Frismanda, Agustinus Bimo Gumelar, Andreas Agung Kristanto
Pág. 60 - 74
Initially, the goal of Machine Learning (ML) advancements is faster computation time and lower computation resources, while the curse of dimensionality burdens both computation time and resource. This paper describes the benefits of the Feature Selection...
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Arturo Benjamín Hurtado-Pérez, Abraham de Jesús Pablo-Sotelo, Fabián Ramírez-López, Jorge Javier Hernández-Gómez and Miguel Felix Mata-Rivera
Launching satellites into the Earth?s orbit is a critical area of research, and very demanding satellite services increase exponentially as modern society takes shape. At the same time, the costs of developing and launching satellite missions with shorte...
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Juan Ma, Qiang Yang, Mingzhi Zhang, Yao Chen, Wenyi Zhao, Chengyu Ouyang and Dongping Ming
Accurately predicting landslide deformation based on monitoring data is key to successful early warning of landslide disasters. Landslide displacement?time curves offer an intuitive reflection of the landslide motion process and deformation predictions o...
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Dennis Delali Kwesi Wayo, Sonny Irawan, Alfrendo Satyanaga and Jong Kim
Data-driven models with some evolutionary optimization algorithms, such as particle swarm optimization (PSO) and ant colony optimization (ACO) for hydraulic fracturing of shale reservoirs, have in recent times been validated as one of the best-performing...
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Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah and Malak EL-Amir
Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as...
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Xiaoyu Han, Chenyu Li, Zifan Wang and Guohua Liu
Neural architecture search (NAS) has shown great potential in discovering powerful and flexible network models, becoming an important branch of automatic machine learning (AutoML). Although search methods based on reinforcement learning and evolutionary ...
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Christian Callegari, Pietro Ducange, Michela Fazzolari and Massimo Vecchio
The problem analyzed in this paper deals with the classification of Internet traffic. During the last years, this problem has experienced a new hype, as classification of Internet traffic has become essential to perform advanced network management. As a ...
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Sergiu Zaharia, Traian Rebedea and Stefan Trausan-Matu
The research presented in the paper aims at increasing the capacity to identify security weaknesses in programming languages that are less supported by specialized security analysis tools, based on the knowledge gathered from securing the popular ones, f...
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