KINDI Center for Computing Research: Recent submissions
Now showing items 181-200 of 274
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Inpatient Discharges Forecasting for Singapore Hospitals by Machine Learning
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)Hospitals can predetermine the admission rate and facilitate resource allocation based on valid emergency requests and bed capacity estimation. The excess unoccupied beds can be determined with the help of forecasting the ... -
Random vector functional link neural network based ensemble deep learning for short-term load forecasting
( Elsevier Ltd , 2022 , Article)Electric load forecasting is essential for the planning and maintenance of power systems. However, its un-stationary and non-linear properties impose significant difficulties in predicting future demand. This paper proposes ... -
Takagi–Sugeno fuzzy based power system fault section diagnosis models via genetic learning adaptive GSK algorithm
( Elsevier B.V. , 2022 , Article)To effectively deal with the operating uncertainties of protective relays and circuit breakers existing in the power system faults, an improved fault section diagnosis (FSD) method is proposed by using Takagi–Sugeno fuzzy ... -
Experimental evaluation of stochastic configuration networks: Is SC algorithm inferior to hyper-parameter optimization method?
( Elsevier Ltd , 2022 , Article)To overcome the pitfalls of Random Vector Functional Link (RVFL), a network called Stochastic Configuration Networks (SCN) has been proposed. By constraining and adaptively selecting the range of randomized parameters using ... -
Ensemble deep learning: A review
( Elsevier Ltd , 2022 , Other)Ensemble learning combines several individual models to obtain better generalization performance. Currently, deep learning architectures are showing better performance compared to the shallow or traditional models. Deep ... -
Weighting and pruning based ensemble deep random vector functional link network for tabular data classification
( Elsevier Ltd , 2022 , Article)In this paper, we first integrate normalization to the Ensemble Deep Random Vector Functional Link network (edRVFL). This re-normalization step can help the network avoid divergence of the hidden features. Then, we propose ... -
Automated layer-wise solution for ensemble deep randomized feed-forward neural network
( Elsevier B.V. , 2022 , Article)The randomized feed-forward neural network is a single hidden layer feed-forward neural network that enables efficient learning by optimizing only the output weights. The ensemble deep learning framework significantly ... -
Significant wave height forecasting using hybrid ensemble deep randomized networks with neurons pruning
( Elsevier Ltd , 2023 , Article)The reliable control of wave energy devices highly relies on the forecasts of wave heights. However, the dynamic characteristics and significant fluctuation of waves’ historical data pose challenges to precise predictions. ... -
Dynamic ensemble deep echo state network for significant wave height forecasting
( Elsevier Ltd , 2023 , Article)Forecasts of the wave heights can assist in the data-driven control of wave energy systems. However, the dynamic properties and extreme fluctuations of the historical observations pose challenges to the construction of ... -
Graph ensemble deep random vector functional link network for traffic forecasting
(2022 , Article)Traffic forecasting is crucial to achieving a smart city as it facilitates public transportation management, autonomous driving, and the resource relocation of the sharing economy. Traffic forecasting belongs to the ... -
A decomposition-based hybrid ensemble CNN framework for driver fatigue recognition
( Elsevier Inc. , 2023 , Article)Electroencephalogram (EEG) has become increasingly popular in driver fatigue monitoring systems. Several decomposition methods have been attempted to analyze the EEG signals that are complex, nonlinear and non-stationary ... -
Evolutionary Multitask Optimization: Fundamental research questions, practices, and directions for the future
( Elsevier B.V. , 2022 , Article)Transfer Optimization has gained a remarkable attention from the Swarm and Evolutionary Computation community in the recent years. It is undeniable that the concepts underlying Transfer Optimization are formulated on solid ... -
A comprehensive review of the deep learning-based tumor analysis approaches in histopathological images: segmentation, classification and multi-learning tasks
( Springer , 2023 , Article)Medical Imaging has become a vital technique that has been embraced in the diagnosis and treatment process of cancer. Histopathological slides, which microscopically examine the suspicious tissue, are considered the golden ... -
An iterative cyclic tri-strategy hybrid stochastic fractal with adaptive differential algorithm for global numerical optimization
( Elsevier Inc. , 2023 , Article)Many real-life problems can be formulated as numerical optimization problems. Such problems pose a challenge for researchers when designing efficient techniques that are capable of finding the desired solution without ... -
Compressive sensing based electronic nose platform
( Elsevier , 2017 , Article)Electronic nose (EN) systems play a significant role for gas monitoring and identification in gas plants. Using an EN system which consists of an array of sensors provides a high performance. Nevertheless, this performance ... -
Smart energy usage and visualization based on micro-moments
( Springer Verlag , 2020 , Conference)Due to global energy demands and overwhelming environmental dilemmas, exorbitant domestic energy usage is a colossal barrier towards energy efficiency. Tremendous research efforts have been poured into a plethora of methods ... -
The simultaneous impact of EV charging and PV inverter reactive power on the hosting distribution system's performance: A case study in kuwait
( MDPI AG , 2020 , Article)Recently, electric vehicles (EVs) have become an increasingly important topic in the field of sustainable transportation research, alongside distributed generation, reactive power compensation, charging optimization, and ... -
Lightweight KPABE Architecture Enabled in Mesh Networked Resource-Constrained IoT Devices
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Internet of Things (IoT) environments are widely employed in industrial applications including intelligent transportation systems, healthcare systems, and building energy management systems. For such environments of highly ... -
Qatar Green Schools Initiative: Energy Management System with Cost-Efficient and Lightweight Networked IoT
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference)With the growing need of developing real-time energy management and automation systems, building energy efficiency is of large focus in recent research. In particular, school buildings require special attention to occupants' ... -
Performance Evaluation of No-Pairing ECC-Based KPABE on IoT Platforms
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference)Internet of Things (IoT) networks operating in lightweight resource-constrained devices have been growing constantly in a wide range of areas. Such networks collect sensitive information over time that represent the users' ...
