Recent applications and advances of African Vultures Optimization Algorithm

Artificial Intelligence Review, Год журнала: 2024, Номер 57(12)

Опубликована: Окт. 17, 2024

Язык: Английский

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Causality-driven sequence segmentation assisted soft sensing for multiphase industrial processes

Neurocomputing, Год журнала: 2025, Номер unknown, С. 129612 - 129612

Опубликована: Фев. 1, 2025

Язык: Английский

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A new metaheuristic algorithm for solving multi-objective single-machine scheduling problems

Journal of Intelligent Systems, Год журнала: 2025, Номер 34(1)

Опубликована: Янв. 1, 2025

Abstract Multi-objective scheduling problems are inherently complex due to the need balance competing objectives, such as minimizing total weighted completion time, reducing number of delayed jobs, and maximum delay. To address these challenges, this article introduces meerkat clan algorithm (MCA), inspired by dynamic, cooperative, adaptive behaviors meerkats, which enhances exploration exploitation solution spaces. The MCA is further integrated with traditional branch-and-bound (BAB) method, utilizing it an upper bound significantly improve accuracy efficiency solutions. Comprehensive computational experiments were conducted evaluate MCA’s performance against state-of-the-art algorithms, including bald eagle search optimization (BESOA) standalone BAB method. demonstrated superior scalability efficiency, effectively solving involving up n = 30,000 whereas BESOA was limited handling instances 1,000 jobs. Additionally, integration method achieved exceptional precision for smaller problem instances, 13 jobs effectively. results underscore algorithm’s potential a robust multi-objective problems, combining speed outperform methods. Moreover, hybrid approach integrating provides flexible versatile framework capable addressing wide range scenarios, from small-scale large-scale applications. These findings position transformative tool in both theoretical practical domains.

Язык: Английский

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Atom Search Optimization: a comprehensive review of its variants, applications, and future directions

PeerJ Computer Science, Год журнала: 2025, Номер 11, С. e2722 - e2722

Опубликована: Фев. 28, 2025

The Atom Search Optimization (ASO) algorithm is a recent advancement in metaheuristic optimization inspired by principles of molecular dynamics. It mathematically models and simulates the natural behavior atoms, with interactions governed forces derived from Lennard-Jones potential constraint based on bond-length potentials. Since its inception 2019, it has been successfully applied to various challenges across diverse fields technology science. Despite notable achievements rapidly growing body literature ASO domain, comprehensive study evaluating success implementations still lacking. To address this gap, article provides thorough review half decade advancements research, synthesizing wide range studies highlight key variants, their foundational principles, significant achievements. examines applications, including single- multi-objective problems, introduces well-structured taxonomy guide future exploration ASO-related research. reviewed reveals that several variants algorithm, modifications, hybridizations, implementations, have developed tackle complex problems. Moreover, effectively domains, such as engineering, healthcare medical Internet Things communication, clustering data mining, environmental modeling, security, engineering emerging most prevalent application area. By addressing common researchers face selecting appropriate algorithms for real-world valuable insights into practical applications offers guidance designing tailored specific

Язык: Английский

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A survey of Beluga whale optimization and its variants: Statistical analysis, advances, and structural reviewing

Computer Science Review, Год журнала: 2025, Номер 57, С. 100740 - 100740

Опубликована: Март 3, 2025

Язык: Английский

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Nonlinear Marine Predator Algorithm for Robust Identification of Fractional Hammerstein Nonlinear Model under Impulsive Noise with Application to Heat Exchanger System

Communications in Nonlinear Science and Numerical Simulation, Год журнала: 2025, Номер unknown, С. 108809 - 108809

Опубликована: Март 1, 2025

Язык: Английский

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Breast cancer prediction with feature-selected XGB classifier, optimized by metaheuristic algorithms

Journal Of Big Data, Год журнала: 2025, Номер 12(1)

Опубликована: Апрель 1, 2025

Язык: Английский

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2D-Variation convolution-based generative adversarial network for unsupervised time series anomaly detection: a MSTL enhanced data preprocessing approach

Applied Intelligence, Год журнала: 2025, Номер 55(7)

Опубликована: Апрель 9, 2025

Язык: Английский

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Deep Recurrent Neural Network with Fractional Addax Optimization Algorithm for Influenza Virus Host Prediction

MethodsX, Год журнала: 2025, Номер unknown, С. 103319 - 103319

Опубликована: Апрель 1, 2025

Язык: Английский

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Transformer fault diagnosis using machine learning: a method combining SHAP feature selection and intelligent optimization of LGBM

Energy Informatics, Год журнала: 2025, Номер 8(1)

Опубликована: Апрель 22, 2025

Язык: Английский

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