Optimizing Emergency Department Staff Configurations Through Simulation and Montecarlo Clustering Search Algorithm (Mcsa)

Published: Jan. 1, 2025

Language: Английский

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A Hybrid Deep Learning Approach for Improved Detection and Prediction of Brain Stroke

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(9), P. 4639 - 4639

Published: April 22, 2025

Brain stroke is the leading cause of death and disability globally; hence, early identification prediction are critical for better patient outcomes. Traditional diagnostic procedures, such as manually interpreting clinical images, time consuming error prone. This research investigates use hybrid deep learning models, recurrent neural networks (RNNs), long short-term memory (LSTM), convolutional (CNNs), to improve accuracy. The current study compared performance these individual models with developed model on brain dataset. By merging we reached an overall accuracy 96% in identifying risk low, medium, or high. categorization may offer healthcare practitioners actionable insights by assisting them allowing make decisions. technique represents a substantial improvement preventive practices. model’s can further be tested more complicated demographic data that will help generalize real-world applications. Furthermore, combining this electronic health records (EHR) systems also assist identification, tailored therapies, improved management, enhancing outcomes lowering costs.

Language: Английский

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An RNA Evolutionary Algorithm Based on Gradient Descent for Function Optimization

Journal of Computational Design and Engineering, Journal Year: 2024, Volume and Issue: 11(4), P. 332 - 357

Published: July 3, 2024

Abstract The optimization of numerical functions with multiple independent variables was a significant challenge numerous practical applications in process control systems, data fitting, and engineering designs. Although RNA genetic algorithms offer clear benefits function optimization, including rapid convergence, they have low accuracy can easily become trapped local optima. To address these issues, new heuristic algorithm proposed, gradient descent-based algorithm. Specifically, adaptive moment estimation (Adam) employed as mutation operator to improve the development ability Additionally, two operators inspired by inner-loop structure molecules were introduced: an crossover operator. These enhance global exploration early stages evolution enable it escape from consists stages: pre-evolutionary stage that employs identify individuals vicinity optimal region post-evolutionary applies descent further solution’s quality. When compared current advanced for solving problems, Adam Genetic Algorithm (RNA-GA) produced better solutions. In comparison RNA-GA (GA) across 17 benchmark functions, ranked first best result average rank 1.58 according Friedman test. set 29 CEC2017 suite, such African Vulture Optimization Algorithm, Dung Beetle Optimization, Whale Grey Wolf Optimizer, 1.724 Our not only achieved improvements over but also performed excellently among various achieving high precision optimization.

Language: Английский

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Fuzzy multi-objective optimization for sustainable agricultural water management of irrigation networks

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 372, P. 123347 - 123347

Published: Nov. 20, 2024

Language: Английский

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