KINDI Center for Computing Research: Recent submissions
Now showing items 81-100 of 178
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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 of Metaheuristic and Exact Algorithm Based on the Divide-And-Conquer Framework for Multisatellite Observation Scheduling
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)Satellite observation scheduling plays a significant role in improving the efficiency of Earth observation systems. To solve the large-scale multisatellite observation scheduling problem, this article proposes an ensemble ... -
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 ... -
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 ... -
Jointly optimized ensemble deep random vector functional link network for semi-supervised classification
( Elsevier Ltd , 2022 , Article)Randomized neural networks have become more and more attractive recently since they use closed-form solutions for parameter training instead of gradient-based approaches. Among them, the random vector functional link network ... -
EEG-based emotion recognition using random Convolutional Neural Networks
( Elsevier Ltd , 2022 , Article)Emotion recognition based on electroencephalogram (EEG) signals is helpful in various fields, including medical healthcare. One possible medical application is to diagnose emotional disorders in patients. Humans tend to ... -
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 ... -
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 ... -
Collaborative Truck-Drone Routing for Contactless Parcel Delivery during the Epidemic
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)The COVID-19 pandemic calls for contactless deliveries. To prevent the further spread of the disease and ensure the timely delivery of supplies, this paper investigates a collaborative truck-drone routing problem for ... -
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 ... -
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 ... -
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 ... -
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 ... -
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 ... -
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 ... -
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 Paper)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 ...
