This paper investigates the effectiveness and efficiency of two competitive (predator-prey) evolutionary procedures for training multi-layer perceptron classifiers: Co-Adaptive Neural Network Training, and a modified ...
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We revisit the problem of optimizing a fitness function of unknown dimension;that is, we face a function defined over bit-strings of large length N, but only n N of them have an influence on the fitness. Neither the p...
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We present a comparison of step size adaptation methods for evolution strategies, covering recent developments in the field. Following recent work by Hansen et al. we formulate a concise list of performance criteria: ...
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Due to the excessive cost of Monte Carlo simulation, metamodel is now frequently used to accelerate the process of robustness estimation. In this paper, we explore the use of multiple metamodels for robustness evaluat...
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Green communication has become a hot topic in the field of wireless communication. This paper aims to improve the Quality of Service (QoS) of the system and minimizes the energy consumption by the spectrum-energy coop...
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This paper describes the experimental tests and numerical analyses performed to characterize the dynamic behaviour of the principal tower of the San Felice sul Panaro Fortress (Modena, Italy). After the Emilia earthqu...
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ISBN:
(纸本)9786188284418
This paper describes the experimental tests and numerical analyses performed to characterize the dynamic behaviour of the principal tower of the San Felice sul Panaro Fortress (Modena, Italy). After the Emilia earthquake that occurred in 2012, the Fortress reported serious damage, such as severe cracks on the walls and collapses of several towers and the roof. As a part of a research that aims at evaluating the vulnerability of the Fortress and designing retrofitting interventions, full-scale ambient vibration tests were performed to evaluate the dynamic properties of the principal tower. Afterwards, a Finite Element (FE) model is calibrated to obtain a good match between the numerical and experimental modal properties. The optimization process is carried out through an improved surrogate-assisted evolutionary strategy. Due to the serious damage of the Fortress, the effective stiffness of the cracked masonry and the efficiency of connection at the interface between the principal tower and the rest of the Fortress are considered the main uncertain quantities to be calibrated. A multi-objective optimization is performed, considering the frequency and mode shape residuals. These are defined as the difference between experimental and numerical modal properties. The multi-objective optimization is reduced to a series of a single-objective optimization adopting the weighted sum method. The set of optimal solutions that form the Pareto front is obtained performing the optimization for different values of the weighting factors. Then, two criteria are used and compared in order to find the preferred solution among the Pareto front solutions. Finally, a comparison of the identified structural parameters obtained varying the weighting factors for natural frequencies and mode shapes in the optimization process is presented, highlighting the importance of a proper choice of the weighting factors.
This paper proposes EAs that utilize fuzzy values directly as the genotype values. In the proposed method, each element in a genotype is a fuzzy value. The author extends EA operations for the fuzzy-valued genotypes. ...
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ISBN:
(纸本)9781467322591
This paper proposes EAs that utilize fuzzy values directly as the genotype values. In the proposed method, each element in a genotype is a fuzzy value. The author extends EA operations for the fuzzy-valued genotypes. Section 2 describes the extensions of EA operations including population initialization, fitness evaluation, and reproduction. The fitness evaluation methods are extended according to application problems, and the reproduction methods are extended according to EA variations.
Predicting the propagation of forest fires is a crucial point to mitigate their effects. Therefore, several computational tools or simulators have been developed to predict the fire propagation. Such tools consider th...
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Predicting the propagation of forest fires is a crucial point to mitigate their effects. Therefore, several computational tools or simulators have been developed to predict the fire propagation. Such tools consider the scenario (topography, vegetation types, fire front situation), and the particular conditions where the fire is evolving (vegetation conditions, meteorological conditions) to predict the fire propagation. However, these parameters are usually difficult to measure or estimate precisely, and there is a high degree of uncertainty in many of them. This uncertainty provokes a certain lack of accuracy in the predictions with the consequent risks. So, it is necessary to apply methods to reduce the uncertainty in the input parameters. This work presents a comparison of ESSIM-EA and ESSIM-DE: two methods to reduce the uncertainty in the input parameters. These methods combine evolutionary algorithms, Parallelism and Statistical Analysis to improve the propagation prediction.
Despite its known shortcomings, penalty function approaches are among the most commonly used constraint handling methods in the field of evolutionary computation. In this paper, we argue that some of the techniques us...
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In this paper, we use EVEBO, an election-inspired optimization algorithm, to solve the BTS (i.e. transceiver) localization problem. The proposed method tries to solve the classic and very important problem of achievin...
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