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Subgraph generation applied in GraphSAGE deal with imbalanced node classification
In graph neural network applications, GraphSAGE applies inductive learning and has been widely applied in important research topics such as node...
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A Review of Anonymization Algorithms and Methods in Big Data
In the era of big data, with the increase in volume and complexity of data, the main challenge is how to use big data while preserving the privacy of...
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Deep reinforcement learning based mapless navigation for industrial AMRs: advancements in generalization via potential risk state augmentation
This article introduces a novel Deep Reinforcement Learning (DRL)-based approach for mapless navigation in Industrial Autonomous Mobile Robots,...
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DQMMBSC: design of an augmented deep Q-learning model for mining optimisation in IIoT via hybrid-bioinspired blockchain shards and contextual consensus
Single-chained blockchains are highly secure but cannot be scaled to larger IIoT (Internet of Industrial Things) network scenarios due to storage...
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A hybridization of multiple imputation and one-class bagging ensemble approach for missing value and class imbalance problem
Class imbalance in a dataset leads to erroneous outcomes that engrave the learning techniques and high misclassification cost in the minority class....
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Improving predictive performance in e-learning through hybrid 2-tier feature selection and hyper parameter-optimized 3-tier ensemble modeling
The paper presents a new feature selection technique developed in detail here to address improved prediction accuracy not only for the...
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Towards Cardinality-Aware Evidential Combination Rules in Dempster–Shafer Theory
The Dempster–Shafer theory has garnered significant attention for effectively managing uncertainty across various disciplines. However, the core...
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Representing a Model for the Anonymization of Big Data Stream Using In-Memory Processing
In light of the escalating privacy risks in the big data era, this paper introduces an innovative model for the anonymization of big data streams,...
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Fast Global Image Smoothing via Quasi Weighted Least Squares
Image smoothing is a long-studied research area with tremendous approaches proposed. However, how to perform high-quality image smoothing with less...
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Multiobjective optimization-based trajectory planning for laser 3D scanner robots
In our industrial material defect detecting processes, the multi criteria is considered in two-level motion planning structure. Firstly, the feed...
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SIM-GCN: similarity graph convolutional networks for charges prediction
In recent years, the analysis of legal judgments and the prediction of outcomes based on case factual descriptions have become hot research topics in...
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Context-aware cross feature attentive network for click-through rate predictions
Click-through rate (CTR) prediction aims to estimate the likelihood that a user will interact with an item. It has gained significant attention in...
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A novel artificial electric field strategy for economic load dispatch problem with renewable penetration
This article presents an innovative method to address the economic load dispatch (ELD) problem in power systems incorporating renewable energy...
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An improved approach for incomplete information modeling in the evidence theory and its application in classification
Incomplete information modeling and fusion under uncertain circumstances remain a significant open problem in practical engineering. In this study,...
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Statistical inference on multicomponent stress–strength reliability with non-identical component strengths using progressively censored data from Kumaraswamy distribution
In this article, we draw inferences on stress–strength reliability in a multicomponent system with non-identical strength components based on the...
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An enhanced energy and distance based optimized clustering and dynamic adaptive cluster-based routing in software defined vehicular network
Software-Defined Vehicular Networks (SDVN) have been established to facilitate secure and adaptable vehicle communication within the dynamic...
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Apple Leaf Disease Detection Using Transfer Learning
Automated detection of plant diseases is crucial as it simplifies the task of monitoring large farms and identifies diseases at their early stages to...
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Production scheduling decision-making technology for multiple CNC machining centers with constraints on serviceable time
The tool’s life statistics module in CNC machining centers typically associates tool’s usage time with the program’s running duration, leading to the...
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Optimal feature with modified bi-directional long short-term memory for big data classification in healthcare application
Artificial intelligence together with its applications are advancing in all fields, particularly medical science. A considerable quantity of clinical...
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SRGAN-enhanced unsafe operation detection and classification of heavy construction machinery using cascade learning
In the inherently hazardous construction industry, where injuries are frequent, the unsafe operation of heavy construction machinery significantly...
