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Transferable preference learning in multi-objective decision analysis and its application to hydrocracking
Hydrocracking represents a complex and time-consuming chemical process that converts heavy oil fractions into various valuable products with low...
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A hyperparameter study for quantum kernel methods
Quantum kernel methods are a promising method in quantum machine learning thanks to the guarantees connected to them. Their accessibility for...
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TRAA: a two-risk archive algorithm for expensive many-objective optimization
Many engineering problems are essentially expensive multi-/many-objective optimization problems, and surrogate-assisted evolutionary algorithms have...
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Hybrid genetic optimization for quantum feature map design
Kernel methods are an import class of techniques in machine learning. To be effective, good feature maps are crucial for map** non-linearly...
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A novel bayesian network-based ensemble classifier chains for multi-label classification
In this paper, we address the challenges of random label ordering and limited interpretability associated with Ensemble Classifier Chains (ECC) by...
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Reading Between the Lines: Machine Learning Ensemble and Deep Learning for Implied Threat Detection in Textual Data
With the increase in the generation and spread of textual content on social media, natural language processing (NLP) has become an important area of...
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CommentClass: A Robust Ensemble Machine Learning Model for Comment Classification
Enormous amounts of data are generated in the form of feedback or comments from online platforms such as social media, e-commerce, education, and...
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ASR-Fed: agnostic straggler-resilient semi-asynchronous federated learning technique for secured drone network
Federated Learning (FL) has emerged as a transformative artificial intelligence paradigm, facilitating knowledge sharing among distributed edge...
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A Multi-strategy Slime Mould Algorithm for Solving Global Optimization and Engineering Optimization Problems
Aiming at the problems of slow convergence, low accuracy, and easy to fall into local optimum of the slime mould algorithm (SMA), we propose an...
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A semantic-based model with a hybrid feature engineering process for accurate spam detection
Detecting spam emails is essential to maintaining the security and integrity of email communication. Existing research has made significant progress...
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Independent actuation of ferrobots in a plane using a grid of electromagnets
We demonstrate a magnetic actuation platform for independent motion of multiple ferromagnetic robots on a plane by locally varying the magnetic field...
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Privacy-preserving matrix factorization for recommendation systems using Gaussian mechanism and functional mechanism
Building a recommendation system involves analyzing user data, which can potentially leak sensitive information about users. As shown in numerous...
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Fake and propaganda images detection using automated adaptive gaining sharing knowledge algorithm with DenseNet121
An additional tool for swaying public opinion on social media is to present recent developments in the creation of natural language. The term “Deep...
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Parameters optimization and precision enhancement of Takagi–Sugeno fuzzy neural network
Takagi–Sugeno fuzzy neural network (TSFNN) has been widely used in intelligent prediction. The prediction accuracy of TSFNN is impacted by its model...
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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 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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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...
