"Artificial lung" is a device that simulates breathing process of occupants in a room. This allows you to safely test, e.g., the impact of HVAC systems on the spread of pathogens. The paper describes the con...
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We consider distributionally robust optimal control of stochastic linear systems under signal temporal logic (STL) chance constraints when the disturbance distribution is unknown. By assuming that the underlying predi...
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The design of an antenna requires a careful selection of its parameters to retain the desired ***,this task is time-consuming when the traditional approaches are employed,which represents a significant *** the other h...
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The design of an antenna requires a careful selection of its parameters to retain the desired ***,this task is time-consuming when the traditional approaches are employed,which represents a significant *** the other hand,machine learning presents an effective solution to this challenge through a set of regression models that can robustly assist antenna designers to find out the best set of design parameters to achieve the intended *** this paper,we propose a novel approach for accurately predicting the bandwidth of metamaterial *** proposed approach is based on employing the recently emerged guided whale optimization algorithm using adaptive particle swarm optimization to optimize the parameters of the long-short-term memory(LSTM)deep *** optimized network is used to retrieve the metamaterial bandwidth given a set of *** addition,the superiority of the proposed approach is examined in terms of a comparison with the traditional multilayer perceptron(ML),Knearest neighbors(K-NN),and the basic LSTM in terms of several evaluation criteria such as root mean square error(RMSE),mean absolute error(MAE),and mean bias error(MBE).Experimental results show that the proposed approach could achieve RMSE of(0.003018),MAE of(0.001871),and MBE of(0.000205).These values are better than those of the other competing models.
A method of cryptographic data protection using neural-like networks based on the model of geometric transformations is proposed. Algorithms for non-iterative training of neural-like structures based on a model of geo...
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Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems. However, we show that the current SRG analysis suffers from some pitfalls that limit its applicabi...
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The paper presents methods and technologies for the use of fuzzy models for the analysis and quality control of polymer materials. In accordance with the approaches under consideration, a single reconfigurable compute...
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each dynamically active object, regardless of its own nature, has limited energy, which limits its ability to change state coordinates. The research has scientific importance for non-stationary objects, which do not a...
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An optimality principle is proposed for making investment decisions based on efficiency and risk assessments with a sparse covariance matrix. The method is implemented as a program with a graphical interface and demon...
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In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative ne...
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The method [K]control of Adaptive Multiple-timescale systems (KAMS) has been used as a method of adaptive control for systems with states that evolve at vastly different rates and with uncertain parameters. Prior rese...
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