Abstract: This paper presents a generic strategy for short-term load forecasting (STLF) based on the support vector regression machines (SVR). Two important improvements to the SVR based load ...
Abstract: This technical note is concerned with the stability analysis of discrete linear systems with time-varying delays. The novelty of the technical note comes from the consideration of a new ...
Abstract: For microgrids with photovoltaic (PV) prosumers, the effective energy sharing management (ESM) is important for the operation. In this paper, a Stackelberg game approach for ESM is proposed.
Abstract: This paper proposes a new hybrid maximum power point tracking (MPPT) algorithm combining grey wolf optimization (GWO) and perturb & observe (P&O) technique for efficient extraction of ...
Abstract: This paper develops a sliding-mode control (SMC) approach for systems with mismatched uncertainties via a nonlinear disturbance observer (DOB). By designing a novel sliding surface based on ...
Abstract: This letter proposes a novel method to improve the results of the three-stage inversion algorithm, using polarimetric synthetic aperture radar interferometry. Since the accuracy of the ...
Abstract: Similar to the efforts to move toward electric vehicles, much research has focused on the idea of a more electric aircraft (MEA). The motivations for this research are similar to that for ...
Abstract: An optically tunable optoelectronic oscillator (OEO) with a wide frequency tunable range incorporating a tunable microwave photonic filter implemented based on phase-modulation to ...
Abstract: Rotated object detection is an important research content in the field of remote-sensing images. However, in the rotated object detection, the inconsistency between the loss function and the ...
Abstract: Recently, the development of autonomous vehicles and intelligent driver assistance systems has drawn a significant amount of attention from the general public. One of the most critical ...
Abstract: Early detection of the motor faults is essential and artificial neural networks are widely used for this purpose. The typical systems usually encapsulate two distinct blocks: feature ...
Abstract: In offline data-driven multiobjective optimization, no new data are available during the optimization process. Approximation models, also known as surrogates, are built using the provided ...
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