A modified reverse-based analysis logic mining model with Weighted Random 2 Satisfiability logic in Discrete Hopfield Neural Network and multi-objective training of Modified Niched Genetic Algorithm

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 240, P. 122307 - 122307

Published: Oct. 28, 2023

Language: Английский

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Learning consistent representations with temporal and causal enhancement for knowledge tracing

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 245, P. 123128 - 123128

Published: Jan. 4, 2024

Language: Английский

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Novel logic mining incorporating log linear approach

Journal of King Saud University - Computer and Information Sciences, Journal Year: 2022, Volume and Issue: 34(10), P. 9011 - 9027

Published: Aug. 28, 2022

Mining the best logical rule from data is a challenging task because not all attribute of dataset will contribute towards optimal representation. Even if correct attributes were selected, wrong connection in formula lead to suboptimal representation datasets. These two factors must be carefully considered creating more robust logic mining method. In this paper, we proposed novel by introducing log-linear analysis select which formulate that embedded into energy-based ANN named Discrete Hopfield Neural Network (DHNN). phase, test association for each carried out where have significant level less than α selected before proceeding phase. By using DHNN, via learned and retrieved induced with classification ability. The hybrid model has been tested various real-life datasets was compared several established methods. Based on findings, winning points dominates 3 metrics 5 average rank. achieve highest rank are Accuracy (1.800), Precision (3.500), Mathews Correlation Coefficient (2.700). accordance experimental result obtained, achieved performance statistically p-value. Hence, these findings an advancement existing statistical

Language: Английский

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Progressive Adjacent-Layer coordination symmetric cascade network for semantic segmentation of Multimodal remote sensing images

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 238, P. 121999 - 121999

Published: Oct. 13, 2023

Language: Английский

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Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia

Heliyon, Journal Year: 2023, Volume and Issue: 9(7), P. e17689 - e17689

Published: June 30, 2023

Accurate water level prediction for both lake and river is essential flood warning freshwater resource management. In this study, three machine learning algorithms: multi-layer perceptron neural network (MLP-NN), long short-term memory (LSTM) extreme gradient boosting XGBoost were applied to develop forecasting models in Muda River, Malaysia. The developed using limited amount of daily meteorological data from 2016 2018. Different input scenarios tested investigate the performance models. results evaluation showed that MLP model outperformed LSTM predicting levels, with an overall accuracy score 0.871 compared 0.865 0.831 XGBoost. No noticeable improvement has been achieved after incorporating into Even though lowest reported was by XGBoost, it faster algorithms due its advanced parallel processing capabilities distributed computing architecture. terms different time horizons, found be more accurate than when 7 days ahead, demonstrating superiority capturing long-term dependencies. Therefore, can concluded each ML own merits weaknesses, differs on case because these depends largely quantity quality available training.

Language: Английский

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Secure communication through reliable S-box design: A proposed approach using coset graphs and matrix operations

Heliyon, Journal Year: 2023, Volume and Issue: 9(5), P. e15902 - e15902

Published: May 1, 2023

Protection of sensitive information has been always the major security concern since decades to withstand against illegitimate access and usage. Substitution-boxes (S-boxes) are vital components any modern day cryptographic system that allows us ensure its resistance attacks. The prime problem with creating S-box is we generally unable discover a consistent distribution among numerous features diverse cryptanalysis majority S-boxes investigated in literature good defenses some attacks but susceptible others. Keeping these considerations mind, this paper proposes novel approach for design based on pair coset graphs newly defined operation row column vectors square matrix. Several standard performance assessment criteria used evaluate reliability proposed approach, results demonstrate developed satisfies all criterions being robust secure communication encryption.

Language: Английский

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A graph-based interpretability method for deep neural networks

Neurocomputing, Journal Year: 2023, Volume and Issue: 555, P. 126651 - 126651

Published: Aug. 3, 2023

Language: Английский

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Log-Linear-Based Logic Mining with Multi-Discrete Hopfield Neural Network

Mathematics, Journal Year: 2023, Volume and Issue: 11(9), P. 2121 - 2121

Published: April 30, 2023

Choosing the best attribute from a dataset is crucial step in effective logic mining since it has greatest impact on improving performance of induced logic. This can be achieved by removing any irrelevant attributes that could become logical rule. Numerous strategies are available literature to address this issue. However, these approaches only consider low-order rules, which limit connection clause. Even though some methods produce excellent metrics, incorporating optimal higher-order rules into challenging due large number involved. Furthermore, suboptimal trained an ineffective discrete Hopfield neural network, leads In paper, we propose log-linear analysis during pre-processing phase, multi-unit 3-satisfiability-based reverse with approach. The proposed also integrates network ensure each 3-satisfiability learned separately. context, our employs three unique optimization layers improve final Extensive experiments conducted 15 real-life datasets various fields study. experimental results demonstrated method outperforms state-of-the-art terms widely used metrics.

Language: Английский

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Dynamic object detection using sparse LiDAR data for autonomous machine driving and road safety applications

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 255, P. 124636 - 124636

Published: June 28, 2024

Language: Английский

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An Inductive Reasoning Model based on Interpretable Logical Rules over temporal knowledge graph

Neural Networks, Journal Year: 2024, Volume and Issue: 174, P. 106219 - 106219

Published: Feb. 29, 2024

Language: Английский

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