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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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Renwu Yan, Yunzhang Liu and Ning Yu
Inspired by the migration and reproduction of species in nature to explore suitable habitats, this paper proposed a new swarm intelligence algorithm called the Migration and Reproduction Algorithm (MARA). This new algorithm discusses how to transform the...
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Martin Jurícek, Roman Parák and Jakub Kudela
The significance of robot manipulators in engineering applications and scientific research has increased substantially in recent years. The utilization of robot manipulators to save labor and increase production accuracy is becoming a common practice in ...
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Francisco-David Hernandez, Domingo Cortes, Marco Antonio Ramirez-Salinas and Luis Alfonso Villa-Vargas
In control research and design it is frequently necessary to explore, evaluate, tune and compare many control strategies. These activities are assisted by software tools of increasing complexity; however, even with the existing high performance tools the...
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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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Valeria Mercuri, Martina Saletta and Claudio Ferretti
As the prevalence and sophistication of cyber threats continue to increase, the development of robust vulnerability detection techniques becomes paramount in ensuring the security of computer systems. Neural models have demonstrated significant potential...
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Sherin M. Omran, Wessam H. El-Behaidy and Aliaa A. A. Youssif
A cryptocurrency is a non-centralized form of money that facilitates financial transactions using cryptographic processes. It can be thought of as a virtual currency or a payment mechanism for sending and receiving money online. Cryptocurrencies have gai...
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Nasser Lotfi and Mazyar Ghadiri Nejad
Multi-objective task graph scheduling is a well-known NP-hard problem that plays a significant role in heterogeneous distributed systems. The solution to the problem is expected to optimize all scheduling objectives. Pretty large state-of-the-art algorit...
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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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Raluca Chitic, Ali Osman Topal and Franck Leprévost
Recently, convolutional neural networks (CNNs) have become the main drivers in many image recognition applications. However, they are vulnerable to adversarial attacks, which can lead to disastrous consequences. This paper introduces ShuffleDetect as a n...
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Zhanghao Qu, Peng Zhang, Yaohua Hu, Huanbo Yang, Taifeng Guo, Kaili Zhang and Junchang Zhang
The stability of vehicles is influenced by the suspension system. At present, there are many studies on the suspension of traditional passenger vehicles, but few are related to agricultural mobile robots. There are structural differences between the susp...
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Raymundo Díaz, Efrain Solares, Victor de-León-Gómez and Francisco G. Salas
Stock portfolio management consists of defining how some investment resources should be allocated to a set of stocks. It is an important component in the functioning of modern societies throughout the world. However, it faces important theoretical and pr...
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Raluca Chitic, Ali Osman Topal and Franck Leprévost
Through the addition of humanly imperceptible noise to an image classified as belonging to a category ????
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, targeted adversarial attacks can lead convolutional neural networks (CNNs) to classify a modified image as belonging to any predefined target...
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Ina Vertommen, Djordje Mitrovic, Karel van Laarhoven, Pieter Piens and Maarten Torbeyns
Numerical optimization is gradually finding its way into drinking water practice. For successful introduction of optimization into the sector, it is important that researchers and utility experts work together on the problem formulation with the water ut...
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Tatiana Karaseva and Eugene Semenkin
Evolutionary approaches are widely applied in solving various types of problems. The paper considers the application of EvolODE and EvolODES approaches to the identification of dynamic systems. EvolODE helps to obtain a model in the form of an ordinary d...
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Jan Strappa, Paola Caymes-Scutari and Germán Bianchini
The problem of wildfire spread prediction presents a high degree of complexity due in large part to the limitations for providing accurate input parameters in real time (e.g., wind speed, temperature, moisture of the soil, etc.). This uncertainty in the ...
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Aleksei Vakhnin and Evgenii Sopov
Unconstrained continuous large-scale global optimization (LSGO) is still a challenging task for a wide range of modern metaheuristic approaches. A cooperative coevolution approach is a good tool for increasing the performance of an evolutionary algorithm...
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Pamela Al Alam, Joseph Constantin, Ibtissam Constantin and Clelia Lopez
Road traffic congestion has became a major problem in most countries because it affects sustainable mobility. Partitioning a transport network into homogeneous areas can be very useful for monitoring traffic as congestion is spatially correlated in adjac...
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Vladimir Stanovov, Shakhnaz Akhmedova, Aleksei Vakhnin, Evgenii Sopov, Eugene Semenkin and Michael Affenzeller
In this study, the modification of the quantum multi-swarm optimization algorithm is proposed for dynamic optimization problems. The modification implies using the search operators from differential evolution algorithm with a certain probability within p...
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Aleksei Vakhnin and Evgenii Sopov
Modern real-valued optimization problems are complex and high-dimensional, and they are known as ?large-scale global optimization (LSGO)? problems. Classic evolutionary algorithms (EAs) perform poorly on this class of problems because of the curse of dim...
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