Browsing Network & Distributed Systems by Publisher "Elsevier"
Now showing items 1-20 of 32
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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 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, ... -
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 ... -
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 ... -
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 ... -
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. ... -
Ensemble reinforcement learning: A survey
( Elsevier , 2023 , Article 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 ... -
Integrated scheduling of multi-constraint open shop and vehicle routing: Mathematical model and learning-driven brain storm optimization algorithm
( Elsevier , 2024 , Article)Recent years have witnessed a surge of interest in integrated production and distribution scheduling problems which can achieve an overall optimization of the production and distribution activities. However, integrated ... -
Knowledge-embedded constrained multiobjective evolutionary algorithm based on structural network control principles for personalized drug targets recognition in cancer
( Elsevier , 2024 , Article)The structural network control principle for identifying personalized drug targets (SNCPDTs) is a kind of constrained multiobjective optimization (CMO) problem with NP-hard features, which makes traditional mathematical ... -
Large-scale data classification based on the integrated fusion of fuzzy learning and graph neural network
( Elsevier , 2024 , Article)Deep learning and fuzzy models provide powerful and practical techniques for solving large-scale deep-learning tasks. The fusion technique on deep learning and fuzzy system are generally classified into ensemble and ... -
Large-scale power system multi-area economic dispatch considering valve point effects with comprehensive learning differential evolution
( Elsevier , 2024 , Article)The role of multi-area economic dispatch (MAED) in power system operation is increasingly significant. It is a non-linear and multi-constraint problem with many local extremes when considering the valve point effects, ... -
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 ... -
Machine learning for the security of healthcare systems based on Internet of Things and edge computing
( Elsevier , 2022 , Book chapter)Using the Internet of Medical Things (IoMT) for treatment and diagnosis has exponentially grown due to its diverse use cases and efficient planning with defined resources. IoMT in the e-healthcare system enables continuous ... -
Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey
( Elsevier , 2024 , Article)Mobile devices have become an essential element in our day-to-day lives. The chances of mobile attacks are rapidly increasing with the growing use of mobile devices. Exploiting vulnerabilities from devices as well as ...
