Generalized short circuit ratio(g SCR)for grid strength assessment of multi-infeed high-voltage direct current(MIDC)systems is a rigorous theoretical extension of the traditional SCR,which enables SCR to be extended t...
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Generalized short circuit ratio(g SCR)for grid strength assessment of multi-infeed high-voltage direct current(MIDC)systems is a rigorous theoretical extension of the traditional SCR,which enables SCR to be extended to MIDC ***,g SCR is originally based on the assumption of homogeneous MIDC systems,in which all high-voltage direct current(HVDC)converters have an identical control configuration,thus presenting challenges to applications of g SCR to inhomogeneous MIDC *** weaken this assumption,this paper applies matrix perturbation theory to explore the possibility of utilization of g SCR into inhomogeneous MIDC *** of numerical experiments show that in inhomogeneous MIDC systems,the previously proposed g SCR can still be used without ***,critical g SCR(Cg SCR)must be redefined by considering the characteristics of control configurations of HVDC ***,the difference between g SCR and redefined Cg SCR can effectively quantify the pertinent AC grid strength in terms of the static-voltage stability *** performance of the proposed method is demonstrated in a triple-infeed inhomogeneous line commutated converter based high-voltage direct current(LCC-HVDC)system.
In this paper, we consider a K-user interference channel where interference among the users is neither too strong nor too weak, a scenario that is relatively underexplored in the literature. We propose a novel deep le...
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By creating multipath backscatter links and amplify signal strength, reconfigurable intelligent surfaces (RIS) and decode-and-forward (DF) relaying are shown to degrade the latency of the ultrareliable low-latency com...
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In the Internet of Things (IoT), optimizing machine performance through data analysis and improved connectivity is pivotal. Addressing the growing need for environmentally friendly IoT solutions, we focus on "gre...
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Extreme events jeopardize power network operations, causing beyond-design failures and massive supply interruptions. Existing market designs fail to internalize and systematically assess the risk of extreme and rare e...
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Multimodal Sentiment Analysis(SA)is gaining popularity due to its broad application *** existing studies have focused on the SA of single modalities,such as texts or photos,posing challenges in effectively handling so...
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Multimodal Sentiment Analysis(SA)is gaining popularity due to its broad application *** existing studies have focused on the SA of single modalities,such as texts or photos,posing challenges in effectively handling social media data with multiple ***,most multimodal research has concentrated on merely combining the two modalities rather than exploring their complex correlations,leading to unsatisfactory sentiment classification *** by this,we propose a new visualtextual sentiment classification model named Multi-Model Fusion(MMF),which uses a mixed fusion framework for SA to effectively capture the essential information and the intrinsic relationship between the visual and textual *** proposed model comprises three deep neural *** different neural networks are proposed to extract the most emotionally relevant aspects of image and text ***,more discriminative features are gathered for accurate sentiment ***,a multichannel joint fusion modelwith a self-attention technique is proposed to exploit the intrinsic correlation between visual and textual characteristics and obtain emotionally rich information for joint sentiment ***,the results of the three classifiers are integrated using a decision fusion scheme to improve the robustness and generalizability of the proposed *** interpretable visual-textual sentiment classification model is further developed using the Local Interpretable Model-agnostic Explanation model(LIME)to ensure the model’s explainability and *** proposed MMF model has been tested on four real-world sentiment datasets,achieving(99.78%)accuracy on Binary_Getty(BG),(99.12%)on Binary_iStock(BIS),(95.70%)on Twitter,and(79.06%)on the Multi-View Sentiment Analysis(MVSA)*** results demonstrate the superior performance of our MMF model compared to single-model approaches and current state-of-the-art techniques based on model evaluation cr
A recommender system is an approach performed by e-commerce for increasing smooth users’*** pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the ord...
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A recommender system is an approach performed by e-commerce for increasing smooth users’*** pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the order of *** work will present the implementation of sequence pattern mining for recommender systems within the domain of *** work will execute the Systolic tree algorithm for mining the frequent patterns to yield feasible rules for the recommender *** feature selec-tion's objective is to pick a feature subset having the least feature similarity as well as highest relevancy with the target *** will mitigate the feature vector's dimensionality by eliminating redundant,irrelevant,or noisy *** work pre-sents a new hybrid recommender system based on optimized feature selection and systolic *** features were extracted using Term Frequency-Inverse Docu-ment Frequency(TF-IDF),feature selection with the utilization of River Forma-tion Dynamics(RFD),and the Particle Swarm Optimization(PSO)*** systolic tree is used for pattern mining,and based on this,the recommendations are *** proposed methods were evaluated using the MovieLens dataset,and the experimental outcomes confirmed the efficiency of the *** was observed that the RFD feature selection with systolic tree frequent pattern mining with collaborativefiltering,the precision of 0.89 was achieved.
We propose a cross-subcarrier precoder design(CSPD) for massive multiple-input multiple-output(MIMO) orthogonal frequency division multiplexing(OFDM) downlink. This work aims to significantly improve the channel estim...
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We propose a cross-subcarrier precoder design(CSPD) for massive multiple-input multiple-output(MIMO) orthogonal frequency division multiplexing(OFDM) downlink. This work aims to significantly improve the channel estimation and signal detection performance by enhancing the smoothness of the frequency domain effective channel. This is accomplished by designing a few vectors known as the transform domain precoding vectors(TDPVs), which are then transformed into the frequency domain to generate the precoders for a set of subcarriers. To combat the effect of channel aging, the TDPVs are optimized under imperfect channel state information(CSI). The optimal precoder structure is derived by maximizing an upper bound of the ergodic weighted sum-rate(WSR) and utilizing the a posteriori beam-based statistical channel model(BSCM). To avoid the large-dimensional matrix inversion, we propose an algorithm with symplectic optimization. Simulation results indicate that the proposed cross-subcarrier precoder design significantly outperforms conventional methods.
Hybrid switch reluctance motors are the family of switch reluctance motors (SRMs) that attenuate the magnetic saturation and increase the air gap magnetic flux by exploiting permanent magnets. The permanent magnet aux...
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The escalating installation of distributed generation (DG) within active distribution networks (ADNs) diminishes the reliance on fossil fuels, yet it intensifies the disparity between demand and generation across vari...
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The escalating installation of distributed generation (DG) within active distribution networks (ADNs) diminishes the reliance on fossil fuels, yet it intensifies the disparity between demand and generation across various regions. Moreover, due to the intermittent and stochastic characteristics, DG also introduces uncertain forecasting errors, which further increase difficulties for power dispatch. To overcome these challenges, an emerging flexible interconnection device, soft open point (SOP), is introduced. A distributionally robust chance-constrained optimization (DRCCO) model is also proposed to effectively exploit the benefits of SOPs in ADNs under uncertainties. Compared with conventional robust, stochastic and chance-constrained models, the DRCCO model can better balance reliability and economic profits without the exact distribution of uncertainties. More-over, unlike most published works that employ two individual chance constraints to approximate the upper and lower bound constraints (e.g, bus voltage and branch current limitations), joint two-sided chance constraints are introduced and exactly reformulated into conic forms to avoid redundant conservativeness. Based on numerical experiments, we validate that SOPs' employment can significantly enhance the energy efficiency of ADNs by alleviating DG curtailment and load shedding problems. Simulation results also confirm that the proposed joint two-sided DRCCO method can achieve good balance between economic efficiency and reliability while reducing the conservativeness of conventional DRCCO methods.
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