This study examines a cooperative non-orthogonal multiple access (NOMA) network utilizing an energy- constrained unmanned aerial vehicle (UAV) relay (UAVR) to expand coverage and improve network throughput. In order t...
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This study examines a cooperative non-orthogonal multiple access (NOMA) network utilizing an energy- constrained unmanned aerial vehicle (UAV) relay (UAVR) to expand coverage and improve network throughput. In order to provide energy to the UAVR, we consider the hybrid simultaneous wireless information and power transmission (SWIPT) method, which allows the UAVR to harvest energy from the source (i.e., sink node) signal. Herein, a hybrid time switching (TS)-based and power splitting (PS)-based relaying scheme is applied to improve the UAVR's energy harvesting (EH) efficiency and the system performance. Given this context, we derive the closed-form expression of the outage probability (OP) for the sensors to evaluate the network performance. Based on the achieved analytical results, we apply the bat algorithm optimization (BAO) method to determine the optimal working point (as a fraction of received power and power allocation coefficients, and the 3-D positions of the UAVR) for the system such that the OP is minimized. The numerical analysis indicates that BAO is effective in both exploring and exploiting solutions, making it a suitable choice for similar non-convex optimization problems in continuous search spaces for cooperative NOMA IoT networks.
This work aims to design a simple and powerful optimal observer for electric vehicles (EV) propelled by permanent magnet synchronous motor (PMSM) using synergetic theory. The development of suggested synergetic observ...
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This work aims to design a simple and powerful optimal observer for electric vehicles (EV) propelled by permanent magnet synchronous motor (PMSM) using synergetic theory. The development of suggested synergetic observer (SynO) based on the selected two manifolds of the back-EMF method which are the special merit of SynO is insensible of parametric and nonparametric deviations. The system is modeled by using small signal method with 99.35% accuracy. Moreover, to optimize the coefficients of observers, the bat algorithm optimization is executed in this work. The proposed SynO are compared with SMO by experimental tests on 0.4 kW, 3-phase PMSM using a TI F28335 digital signal processor board considering various dynamic operating conditions. The experimental results reveal that the performance of optimal SynO for accurate speed estimation of EV are better than the SMO, as well as good robustness against measurement noise, and reduced the chattering phenomena.
In this study, a new strategy based on integrating geostatistical seismic inversion and optimized support vector regression (OSVR) will be utilized to transform multi seismic attributes to sand fraction log. In first ...
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In this study, a new strategy based on integrating geostatistical seismic inversion and optimized support vector regression (OSVR) will be utilized to transform multi seismic attributes to sand fraction log. In first step, owing to compatibility relation between acoustic impedance (AI) and sand fraction, a high resolution value of this important attribute was extracted through a geostatistical seismic inversion (GSI). In second step, in addition to AI, several physical attributes are obtained from seismic data and then all of extracted attributes (AI and other seismic attributes) evaluated by step-wise regression for selecting best attributes that have highest effect on predicting sand fraction. In final step, selected attributes have been fed in the bat inspired optimized support vector regression as input and the sand fraction log is estimated. For the assessment of proposed strategy, the values of predicted sand fraction are compared with their real corresponding values in a blind well. It will be evident from the results that the proposed strategy is qualified for modeling the sand fraction as a function of seismic attributes.
This article proposes a new strategy based on a hybrid method that combines the gravitational search algorithm (GSA) with the batalgorithm (bat) to solve a single-objective optimization problem. It first runs GSA, fo...
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This article proposes a new strategy based on a hybrid method that combines the gravitational search algorithm (GSA) with the batalgorithm (bat) to solve a single-objective optimization problem. It first runs GSA, followed by bat as the second step. The proposed approach relies on a parameter between 0 and 1 to address the problem of falling into local research because the lack of a local search mechanism increases intensity search, whereas diversity remains high and easily falls into the local optimum. The improvement is equivalent to the speed of the original bat. Access speed is increased for the best solution. All solutions in the population are updated before the end of the operation of the proposed algorithm. The diversification feature of bat has solved the problem of weakness in diversity observed in the algorithm by applying the parameters used in bat. Moreover, balance is achieved through the intensification properties of the algorithms.
Digital audio watermarking still remains one of the most interesting techniques for multimedia copyright protection. In this paper, bat inspired optimization approach is exploited to design an optimal audio watermarki...
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ISBN:
(纸本)9781509004782
Digital audio watermarking still remains one of the most interesting techniques for multimedia copyright protection. In this paper, bat inspired optimization approach is exploited to design an optimal audio watermarking algorithm for copyright protection. First, the original audio signal is decomposed by the Discrete Wavelet Transform (DWT) into low and high frequency parts. The low frequency part is then segmented into several 2D blocks, and QR factorization is subsequently applied to each one. The watermark, which is a binary logo, is embedded by quantizing the coefficients of resulting R matrices. Since the quantization step is signal-dependent, bat algorithm optimization is used to find a suitable one for each audio signal. This allows to obtain the highest possible robustness without losing the transparency of the watermark. Simulation tests show that the proposed method not only maintains high quality of the audio signal, but also is robust against common signal processing manipulations such as noise addition, re-sampling, filtering and MPEG 1 Layer III compression.
Digital audio watermarking still remains one of the most interesting techniques for multimedia copyright protection. In this paper, bat inspired optimization approach is exploited to design an optimal audio watermarki...
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ISBN:
(纸本)9781509004799
Digital audio watermarking still remains one of the most interesting techniques for multimedia copyright protection. In this paper, bat inspired optimization approach is exploited to design an optimal audio watermarking algorithm for copyright protection. First, the original audio signal is decomposed by the Discrete Wavelet Transform (DWT) into low and high frequency parts. The low frequency part is then segmented into several 2-D blocks, and QR factorization is subsequently applied to each one. The watermark, which is a binary logo, is embedded by quantizing the coefficients of resulting R matrices. Since the quantization step is signal-dependent, bat algorithm optimization is used to find a suitable one for each audio signal. This allows to obtain the highest possible robustness without losing the transparency of the watermark. Simulation tests show that the proposed method not only maintains high quality of the audio signal, but also is robust against common signal processing manipulations such as noise addition, re-sampling, filtering and MPEG 1 Layer III compression.
The aim of this paper is to provide a new suitable method for smart grid state estimation. Based on the non-linearity of methods used to solve the state estimation problem, in addition to the ability to solve such iss...
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The aim of this paper is to provide a new suitable method for smart grid state estimation. Based on the non-linearity of methods used to solve the state estimation problem, in addition to the ability to solve such issues, it is also necessary to be responsive and have acceptable accuracy. In this article, a new metrology of optimization, batalgorithm (BA), based on the Weighted Least Square (WLS) method is presented. This algorithm is equipped with a new self-adaptive learning that improves the performance of BA and has a better effect on optimization. batalgorithm can estimate voltage and angle output values by weighted least square method. The advantages of this method are lower cost function, faster solution and globally-locally better search in comparison with other algorithms.
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