Browsing KINDI Center for Computing Research by Publisher "Elsevier"
Now showing items 1-20 of 52
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A cultural evolution with a modified selection function and adaptive α-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 ... -
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 resource provisioning framework for bioinformatics applications in multi-cloud environments
( Elsevier , 2018 , Article)The significant advancement in Next Generation Sequencing (NGS) have enabled the generation of several gigabytes of raw data in a single sequencing run. This amount of raw data introduces new scalability challenges in ... -
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. ... -
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 ... -
AI-powered malware detection with Differential Privacy for zero trust security in Internet of Things networks
( Elsevier , 2024 , Article)The widespread usage of Android-powered devices in the Internet of Things (IoT) makes them susceptible to evolving cybersecurity threats. Most healthcare devices in IoT networks, such as smart watches, smart thermometers, ... -
Alzheimer’s disease diagnosis from MRI and SWI fused image using self adaptive differential evolutionary RVFL classifier
( Elsevier , 2025 , Article)Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that involves gradual memory loss and eventually leads to severe cognitive decline at the final stage. Advanced neuroimaging modalities, including magnetic ... -
An enhanced ensemble deep random vector functional link network for driver fatigue recognition
( Elsevier , 2023 , Article)This work investigated the use of an ensemble deep random vector functional link (edRVFL) network for electroencephalogram (EEG)-based driver fatigue recognition. Against the low feature learning capability of the edRVFL ... -
An archive-assisted multi-modal multi-objective evolutionary algorithm
( Elsevier , 2024 , Article)The multi-modal multi-objective optimization problems (MMOPs) pertain to characteristic of the decision space that exhibit multiple sets of Pareto optimal solutions that are either identical or similar. The resolution of ... -
Benchmark problems for large-scale constrained multi-objective optimization with baseline results
( Elsevier , 2024 , Article)The interests in evolutionary constrained multiobjective optimization are rapidly increasing during the past two decades. However, most related studies are limited to small-scale problems, despite the fact that many practical ... -
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 ... -
CloudFlow: A data-aware programming model for cloud workflow applications on modern HPC systems
( Elsevier , 2015 , Article)Traditional High-Performance Computing (HPC) based big-data applications are usually constrained by having to move large amount of data to compute facilities for real-time processing purpose. Modern HPC systems, represented ... -
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 ... -
Constrained large-scale multiobjective optimization based on a competitive and cooperative swarm optimizer
( Elsevier , 2024 , Article)Many engineering application problems can be modeled as constrained multiobjective optimization problems (CMOPs), which have attracted much attention. In solving CMOPs, existing algorithms encounter difficulties in balancing ... -
Deep reinforcement learning as multiobjective optimization benchmarks: Problem formulation and performance assessment
( Elsevier , 2024 , Article)The successful deployment of Deep learning in several challenging tasks has been translated into complex control problems from different domains through Deep Reinforcement Learning (DRL). Although DRL has been extensively ... -
Differential evolution-based mixture distribution models for wind energy potential assessment: A comparative study for coastal regions of China
( Elsevier , 2025 , Article)Mixture distributions generally have higher flexibility than single distributions in describing wind speeds. However, the determination of their components is critical. This work evaluates suitable distributions for the ... -
Dual population approximate constrained Pareto front for constrained multiobjective optimization
( Elsevier , 2023 , Article)For constrained multiobjective optimization problems (CMOPs), the ultimate goal is to obtain a set of well-converged and well-distributed feasible solutions to approximate the constrained Pareto front (CPF). Various ... -
Energy-efficient multi-objective distributed assembly permutation flowshop scheduling by Q-learning based meta-heuristics
( Elsevier , 2024 , Article)This study addresses energy-efficient multi-objective distributed assembly permutation flowshop scheduling problems with minimisation of maximum completion time, mean of earliness and tardiness, and total carbon emission ... -
Ensemble artificial bee colony algorithm with Q-learning for scheduling Bi-objective disassembly line
( Elsevier , 2024 , Article)This study addresses a bi-objective disassembly line scheduling problem (Bi-DLSP), considering interference relationships among tasks. The objectives are to optimize the total disassembly time and the smoothing index ... -
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. ...
