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Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques [PDF]
Sensors, 2020 In this article, we propose a new mobility model, called Attractor Based Inter-Swarm collaborationS (ABISS), for improving the surveillance of restricted areas performed by unmanned autonomous vehicles.
Daniel H. Stolfi +3 more
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Solving equations by hybrid evolutionary computation techniques [PDF]
IEEE Transactions on Evolutionary Computation, 2000 Evolutionary computation techniques have mostly been used to solve various optimization and learning problems. This paper describes a novel application of evolutionary computation techniques to equation solving. Several combinations of evolutionary computation techniques and classical numerical methods are proposed to solve linear and partial ...
Jun He, Xin Yao
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Quadrature mirror filter bank design based on hybrid bee colony technique
Automatika, 2021 This paper proposed a modified evolutionary technique formed by the hybridization of the bee colony technique and Nelder–Mead Simplex search technique to optimize the coefficients of Quadrature Mirror Filter (QMF). The performance of QMF can be evaluated
Hitendra Singh +2 more
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An Intelligent Technique for Initial Distribution of Genetic Algorithms
Axioms, 2023 The need to find the global minimum in multivariable functions is a critical problem in many fields of science and technology. Effectively solving this problem requires the creation of initial solution estimates, which are subsequently used by the ...
Vasileios Charilogis +2 more
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Toward an Ideal Particle Swarm Optimizer for Multidimensional Functions
Information, 2022 The Particle Swarm Optimization (PSO) method is a global optimization technique based on the gradual evolution of a population of solutions called particles. The method evolves the particles based on both the best position of each of them in the past and
Vasileios Charilogis, Ioannis G. Tsoulos
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A Feature Construction Method That Combines Particle Swarm Optimization and Grammatical Evolution
Applied Sciences, 2023 The problem of data classification or data fitting is widely applicable in a multitude of scientific areas, and for this reason, a number of machine learning models have been developed. However, in many cases, these models present problems of overfitting
Ioannis G. Tsoulos, Alexandros Tzallas
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Algorithms, 2023 K-Means is a “de facto” standard clustering algorithm due to its simplicity and efficiency. K-Means, though, strongly depends on the initialization of the centroids (seeding method) and often gets stuck in a local sub-optimal solution.
Libero Nigro, Franco Cicirelli
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A Genetic Algorithm Based Optimized Convolutional Neural Network for Face Recognition
International Journal of Applied Mathematics and Computer Science, 2023 Face recognition (FR) is one of the most active research areas in the field of computer vision. Convolutional neural networks (CNNs) have been extensively used in this field due to their good efficiency.
Karlupia Namrata +3 more
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Mathematics, 2021 This paper introduces a robust model predictive controller (MPC) to operate an automatic voltage regulator (AVR). The design strategy tends to handle the uncertainty issue of the AVR parameters.
Mahmoud Elsisi +5 more
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Performance Optimization for a Class of Petri Nets
Sensors, 2023 Petri nets (PNs) are widely used to model flexible manufacturing systems (FMSs). This paper deals with the performance optimization of FMSs modeled by Petri nets that aim to maximize the system’s performance under a given budget by optimizing both ...
Weijie Shi +4 more
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