As the world becomes more and more competitive, the number of people experiencing stress, anxiety, and other mental health problems is rapidly rising. In today’s society, stress and pressure are affecting everyone, i...
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Renewable energy forecasting is crucially important because of its fluctuation and stochastic characteristics. In this paper, a hybrid model for wind speed and power forecasting using neuro wavelet and long short-term...
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Detection of melanoma in the early stage can provide the patients with more promising treatments. Numerous methods have been proposed for detecting melanoma using computational approaches;however, the application of d...
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This paper proposes a new score function (SF) of interval-valued intuitionistic fuzzy values (IVIFVs) in order to overcome the shortcomings of the existing SFs of IVIFVs, which are not be able to distinguish the ranki...
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Accurate detection of the Physical Cell Identity (PCI) is critical for rapid synchronization and connection establishment in 5G New Radio (5G-NR) systems. This paper introduces a deep learning-based approach for PCI c...
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A distributed optimization problem with Markovian switching targets and stochastic observation noises is considered in this paper. In order to solve target following and renewable following for microgrid(MG) optimal p...
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A distributed optimization problem with Markovian switching targets and stochastic observation noises is considered in this paper. In order to solve target following and renewable following for microgrid(MG) optimal power balancing, and to attenuate observation noises simultaneously, distributed optimization algorithms are developed. The interaction between observation noises and Markovian switching targets may introduce a fundamental tradeoff in reducing the optimization errors and choosing the step size. Furthermore, under infrequent Markovian switching assumptions, the mean-square optimization error bounds, the switching ordinary differential equation(ODE) limit, and the asymptotic distributions of the optimization errors are established rigorously and comprehensively. A simulation example on a DC MG is presented to show the main results of the paper.
This paper presents an optimization framework for routing in software-defined elastic optical networks using reinforcement learning algorithms. We specifically implement and compare the epsilon-greedy bandit, upper co...
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This paper aims to implement an image classification system to detect Steroid and Non-steroid bodybuilders with RGB images using deep learning techniques. The purpose of creating a steroid use detection Deep Learning ...
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Fast charging stations for electric vehicles (EVs) often consist of charging units with multiple modules connected in parallel to achieve high power ratings and can suffer from cyber-attacks in the modern smart grid a...
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The two-dimensional problem of the reflection and transmission of a plane electromagnetic wave symmetrically incident from either the convex or the concave side on a parabolic-cylinder interface separating two differe...
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