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processing algorithm » processing algorithms (Expand Search)
new algorithm » deer algorithm (Expand Search), rd algorithm (Expand Search)
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elements new » elements _ (Expand Search), elementi per (Expand Search)
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. The ANN reliability is directly related to the success of the training process. …”
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Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection
Published 2024“…Although Evolutionary Algorithms (EAs) have shown promise in the literature for feature selection, creating EAs for high dimensions is still challenging. …”
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Data Redundancy Management in Connected Environments
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conferenceObject -
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Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer
Published 2023“…The execution time of the proposed LFCARO is less than 1 sec. for 10 numerical problems and less than 1.5 sec. for the resource scheduling of residential distribution systems. Based on the average Friedman’s ranking test values, the proposed algorithm stands first with 1.82 for numerical and real-world scheduling problems.…”
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Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer
Published 2023“…The execution time of the proposed LFCARO is less than 1 sec. for 10 numerical problems and less than 1.5 sec. for the resource scheduling of residential distribution systems. Based on the average Friedman’s ranking test values, the proposed algorithm stands first with 1.82 for numerical and real-world scheduling problems. …”
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309
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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Privacy-Preserving Framework for Blockchain-Based Stock Exchange Platform
Published 2022“…Moreover, to ensure long-term unlinkability, the process of anonymization is repeated at regular time intervals (every trading session). …”
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Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
Published 2025“…In addition to the deployment without requiring an explicit model of the plant, the simulation results demonstrate that the proposed solution modifies vehicle dynamics and maneuverability in most cases compared to the model-based conventional controller. Furthermore, the reduction in sideslip angle, excellent traction through minimizing tire slip ratio, avoiding oversteering and understeering, and maintaining an acceptable range of energy optimization are demonstrated for DRL controllers, especially for the TD3 and CL TD3 algorithms.…”
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313
Design of adaptive arrays based on element position perturbations
Published 1993Get full text
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A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
Published 2011Get full text
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masterThesis -
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Large-scale annotation dataset for fetal head biometry in ultrasound images
Published 2023“…Its detailed annotations, broad compatibility, and ethical compliance make it a highly reusable and adaptable tool for the development of algorithms aimed at improving maternal and Fetal health.…”
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A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm
Published 2023“…The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. …”
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Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024“…This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). To evaluate FSAs effectively, controlled environments are required, and the use of synthetic datasets offers significant advantages. …”
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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function
Published 2020“…The performance is calculated first and an LMI-based algorithm is developed to design a state feedback control law with constant gain matrices which robustly stabilizes the system in the mean-square quadratically stable sense.…”
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