DATA RECOVERY Web Results

IRTF: A new tensor factorization for irregular multidimensional data ... By integrating the proposed IRTF and TV-CST, we establish an irregular multidimensional data recovery model. From (d), we can observe that our method preserves the color and the edge of the spatial-irregular multidimensional data as compared with traditional tensor factorization with preprocessing.

Waste heat recoveries in data centers: A review - ScienceDirect Waste heat recovery technology is considered as a promising approach to improve energy efficiency, achieve energy and energy cost savings, and mitigate environmental impacts (caused by both carbon emission and waste heat discharge) at the same time.

Nonconvex 3D array image data recovery and pattern recognition under ... In this paper, we present a weighted tensor Schatten-p quasi-norm (0 Tensor network decomposition for data recovery: Recent advancements and ... Tensor network (TN) decomposition stands as a pivotal technique for characterizing the essential features of high-dimensional data, attracting significant interest and achieving notable success in high-dimensional data recovery. Air quality index prediction through TimeGAN data recovery and PSO ... TimeGAN is employed to learn the structure and distribution of air quality data, facilitating the generation of synthetic data through adversarial networks. Subsequently, the missing values in the real data are replaced with the generated data. Distributed neural tensor completion for network monitoring data recovery However, the training process of existing methods is often time-consuming due to massive data and unreasonable network resource allocation. Thus motivated, we propose a distributed neural tensor completion method, named D-NORM, which simultaneously optimizes both recovery accuracy and time. Dynamic performance of an integrated heat pump system coupled free ... Recovering and reusing this waste heat for district heating is an effective strategy to enhance energy efficiency in data centers. To align data center waste heat recovery with heat consumer demand and improve energy utilization, a transient mathematical model of a data center-integrated heat pump district heating system was developed and ... False data injection attacks data recovery in smart grids: A graph ... False data injection (FDI) attacks, one of the most classical cyber attacks, have increasingly posed a significant threat to the security and reliability of power systems [5]. Such attacks, mislead the system state estimation results, by manipulating the measurements of sensors, and thereby affecting the secure operations of the power system [6]. Research on FDI attacks and their data recovery ... Long-term missing wind data recovery using free access databases and ... The conventional interpolation techniques hardly achieve the desired data recovery. Therefore, a framework was proposed for long-term missing wind data recovery based on a deep neural network (DNN) utilizing a free access database (European Center for Medium-Range Weather Forecasts, ECMWF). Kernel Bayesian tensor ring decomposition for multiway data recovery With the aid of side information, the recovery performance of the methods above is improved. However, all matrix-based methods with side information encounter difficulties when dealing with high-order data because they cannot incorporate specific side information enhancements.