Qatar University Institutional Repository
The top service priorities of QSpace are to collect materials originating from faculty, students, and guests of Qatar University, provide necessary metadata to fulfill a complete bibliographic record, provide open access full-text content to everyone, and preserve content in a secure format for long-term continued access.
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Recent Submissions
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An evolutionary multiobjective method based on dominance and decomposition for feature selection in classification
( Science China Press , 2024 , Article)Feature selection in classification can be considered a multiobjective problem with the objectives of increasing classification accuracy and decreasing the size of the selected feature subset. Dominance-based and ... -
Support Vector Machine Based Models with Sparse Auto-encoder Based Features for Classification Problem
( Springer Science and Business Media Deutschland GmbH , 2023 , Conference Paper)Auto-encoder is a special type of artificial neural network (ANN) that is used to learn informative features from data. In the literature, the generalization performance of several machine learning models have been improved ... -
Double Regularization-Based RVFL and edRVFL Networks for Sparse-Dataset Classification
( Springer Science and Business Media Deutschland GmbH , 2023 , Conference Paper)In our previous work, the random vector functional link network (RVFL) and the ensemble deep RVFL network (edRVFL) have been proven to be competitive for tabular-dataset classification, and their sparse pre-trained versions ... -
Adaptive Scaling for U-Net in Time Series Classification
( Springer Science and Business Media Deutschland GmbH , 2023 , Conference Paper)Convolutional Neural Networks such as U-Net are recently getting popular among researchers in many applications, such as Biomedical Image Segmentation. U-Net is one of the popular deep Convolutional Neural Networks which ... -
UNIFIED DISCRETE DIFFUSION FOR SIMULTANEOUS VISION-LANGUAGE GENERATION
( International Conference on Learning Representations, ICLR , 2023 , Conference Paper)The recently developed discrete diffusion models perform extraordinarily well in the text-to-image task, showing significant promise for handling the multi-modality signals. In this work, we harness these traits and present ... -
A spectral-ensemble deep random vector functional link network for passive brain-computer interface
( Elsevier , 2023 , Article)Randomized neural networks (RNNs) have shown outstanding performance in many different fields. The superiority of having fewer training parameters and closed-form solutions makes them popular in small datasets analysis. ... -
Problem feature based meta-heuristics with Q-learning for solving urban traffic light scheduling problems
( Elsevier , 2023 , Article)An urban traffic light scheduling problem (UTLSP) is studied by using problem feature based meta-heuristics with Q-learning. The goal is to minimize the network-wise total delay time within a time window by finding a ... -
Ensemble reinforcement learning: A survey
( Elsevier , 2023 , Review)Reinforcement Learning (RL) has emerged as a highly effective technique for addressing various scientific and applied problems. Despite its success, certain complex tasks remain challenging to be addressed solely with a ... -
Orthogonal Experimental Design Based Binary Optimization Without Iteration for Fault Section Diagnosis of Power Systems
( IEEE Computer Society , 2024 , Article)Fault section diagnosis (FSD) is considerably indispensable for the continuous and reliable electricity supply. In general, the analytical model of FSD is solved by derivative-free intelligent metaheuristic algorithms. ... -
Online learning using deep random vector functional link network
( Elsevier , 2023 , Article)Deep neural networks have shown their promise in recent years with their state-of-the-art results. Yet, backpropagation-based methods may suffer from time-consuming training process and catastrophic forgetting when performing ... -
A problem-specific knowledge based artificial bee colony algorithm for scheduling distributed permutation flowshop problems with peak power consumption
( Elsevier , 2023 , Article)A distributed permutation flowshop scheduling problem (DPFSP) with peak power consumption is addressed in this work. The instantaneous energy consumption of each factory cannot exceed a threshold. First, a mathematical ... -
A cultural evolution with a modified selection function and adaptive ?-cognition procedure for numerical optimization
( Elsevier , 2023 , Article)In recent years, several population-based evolutionary and swarm algorithms have been developed and used in the literature. This work introduces an improved Cultural Algorithm with a modified selection function and a dynamic ... -
Online dynamic ensemble deep random vector functional link neural network for forecasting
( Elsevier , 2023 , Article)This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). The edRVFL stacks multiple randomized layers to enhance the single-layer RVFL's ... -
Random vector functional link network: Recent developments, applications, and future directions
( Elsevier , 2023 , Article)Neural networks have been successfully employed in various domains such as classification, regression and clustering, etc. Generally, the back propagation (BP) based iterative approaches are used to train the neural networks, ... -
Probabilistic Wind Power Forecasting Using Optimized Deep Auto-Regressive Recurrent Neural Networks
( IEEE Computer Society , 2023 , Article)Wind power forecasting is very crucial for power system planning and scheduling. Deep neural networks (DNNs) are widely used in forecasting applications due to their exceptional performance. However, the DNNs' architectural ... -
Ensemble meta-heuristics and Q-learning for staff dissatisfaction constrained surgery scheduling and rescheduling
( Elsevier , 2024 , Article)In this study, we investigate the multi-objective surgery scheduling and rescheduling problems with considering medical staff dissatisfaction and fuzzy surgery time. Rescheduling is activated when emergency patients arrive. ... -
Boosted multilayer feedforward neural network with multiple output layers
( Elsevier , 2024 , Article)This research introduces the Boosted Ensemble deep Multi-Layer Layer Perceptron (EdMLP) architecture with multiple output layers, a novel enhancement for the traditional Multi-Layer Perceptron (MLP). By adopting a layer-wise ... -
Recurrent ensemble random vector functional link neural network for financial time series forecasting
( Elsevier , 2024 , Article)Financial time series forecasting is crucial in empowering investors to make well-informed decisions, manage risks effectively, and strategically plan their investment activities. However, the non-stationary and non-linear ... -
Accurate parameters extraction of photovoltaic models with multi-strategy gaining-sharing knowledge-based algorithm
( Elsevier , 2024 , Article)The determination of photovoltaic (PV) model parameters has essential theoretical and practical significance for the performance evaluation, power monitoring, and power generation efficiency calculation of PV systems. In ... -
Low-rank and global-representation-key-based attention for graph transformer
( Elsevier , 2023 , Article)Transformer architectures have been applied to graph-specific data such as protein structure and shopper lists, and they perform accurately on graph/node classification and prediction tasks. Researchers have proved that ...
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