Tornado optimizer with Coriolis force: a novel bio-inspired meta-heuristic algorithm for solving engineering problems DOI Creative Commons
Malik Braik, Heba Al-Hiary, Hussein Al-Zoubi

и другие.

Artificial Intelligence Review, Год журнала: 2025, Номер 58(4)

Опубликована: Фев. 5, 2025

Язык: Английский

Chaotic RIME optimization algorithm with adaptive mutualism for feature selection problems DOI
Mahmoud Abdel-Salam,

Gang Hu,

Emre Çelik

и другие.

Computers in Biology and Medicine, Год журнала: 2024, Номер 179, С. 108803 - 108803

Опубликована: Июль 1, 2024

Язык: Английский

Процитировано

40
A wind speed forcasting model based on rime optimization based VMD and multi-headed self-attention-LSTM DOI
Wenhui Liu, Yulong Bai,

xiaoxin Yue

и другие.

Energy, Год журнала: 2024, Номер 294, С. 130726 - 130726

Опубликована: Фев. 16, 2024

Язык: Английский

Процитировано

36
Optimization based on the smart behavior of plants with its engineering applications: Ivy algorithm DOI
Mojtaba Ghasemi, Mohsen Zare, Pavel Trojovský

и другие.

Knowledge-Based Systems, Год журнала: 2024, Номер 295, С. 111850 - 111850

Опубликована: Апрель 22, 2024

Язык: Английский

Процитировано

35
Modified crayfish optimization algorithm for solving multiple engineering application problems DOI Creative Commons
Heming Jia,

Xuelian Zhou,

Jinrui Zhang

и другие.

Artificial Intelligence Review, Год журнала: 2024, Номер 57(5)

Опубликована: Апрель 24, 2024

Abstract Crayfish Optimization Algorithm (COA) is innovative and easy to implement, but the crayfish search efficiency decreases in later stage of algorithm, algorithm fall into local optimum. To solve these problems, this paper proposes an modified optimization (MCOA). Based on survival habits crayfish, MCOA environmental renewal mechanism that uses water quality factors guide seek a better environment. In addition, integrating learning strategy based ghost antagonism enhances its ability evade optimality. evaluate performance MCOA, tests were performed using IEEE CEC2020 benchmark function experiments conducted four constraint engineering problems feature selection problems. For constrained improved by 11.16%, 1.46%, 0.08% 0.24%, respectively, compared with COA. average fitness value accuracy are 55.23% 10.85%, respectively. shows solving complex spatial practical application The combination environment updating significantly improves MCOA. This discovery has important implications for development field optimization. Graphical

Язык: Английский

Процитировано

34
SRIME: a strengthened RIME with Latin hypercube sampling and embedded distance-based selection for engineering optimization problems DOI
Rui Zhong, Jun Yu, Chengqi Zhang

и другие.

Neural Computing and Applications, Год журнала: 2024, Номер 36(12), С. 6721 - 6740

Опубликована: Фев. 12, 2024

Язык: Английский

Процитировано

33
MSAO: A multi-strategy boosted snow ablation optimizer for global optimization and real-world engineering applications DOI
Yaning Xiao, Hao Cui, Abdelazim G. Hussien

и другие.

Advanced Engineering Informatics, Год журнала: 2024, Номер 61, С. 102464 - 102464

Опубликована: Март 15, 2024

Язык: Английский

Процитировано

31
FATA: An efficient optimization method based on geophysics DOI

Ailiang Qi,

Dong Zhao, Ali Asghar Heidari

и другие.

Neurocomputing, Год журнала: 2024, Номер 607, С. 128289 - 128289

Опубликована: Авг. 3, 2024

Язык: Английский

Процитировано

31
The Differentiated Creative Search (DCS): Leveraging differentiated knowledge-acquisition and creative realism to address complex optimization problems DOI
Poomin Duankhan, Khamron Sunat, Sirapat Chiewchanwattana

и другие.

Expert Systems with Applications, Год журнала: 2024, Номер 252, С. 123734 - 123734

Опубликована: Март 22, 2024

Язык: Английский

Процитировано

25
Multi-objective RIME algorithm-based techno economic analysis for security constraints load dispatch and power flow including uncertainties model of hybrid power systems DOI Creative Commons
Sundaram B. Pandya, Kanak Kalita, Pradeep Jangir

и другие.

Energy Reports, Год журнала: 2024, Номер 11, С. 4423 - 4451

Опубликована: Апрель 18, 2024

In recent times, the landscape of power systems has undergone significant evolution, particularly with integration diverse renewable energy sources (RESs). This advancement presents an invaluable opportunity to enhance efficiency in modern grid, primarily by bolstering role stochastic RESs. The challenge lies optimal flow (OPF), a multifaceted and non-linear optimization that grows more complex inclusion RESs aims optimize allocation system resources minimize operational cost while maintaining stability security system. Addressing this, current study introduces innovative approach, Multi-Objective RIME (MORIME) algorithm. Drawing inspiration from physical phenomenon rime-ice, called RIME, MORIME seeks effectively tackle OPF issues. algorithm enhances solution accuracy smartly dividing non-dominated sorting crowding distance mechanism. proposed model incorporates three types RESs: solar photovoltaic, wind small-scale hydropower units. While uncertainties speed irradiation are managed through Monte Carlo simulations, small hydro unit is considered constant source. efficacy tested on IEEE 30 bus results indicate method identifies for multi-objective problem satisfying constraints, thereby proving its effectiveness superiority over MOWOA, MOGWO, MOALO, MOMRFO MOAGDE terms Hyper Volume (HV) reciprocal Pareto Sets Proximity (1/PSP) metrices. source code available at: https://github.com/kanak02/MORIME

Язык: Английский

Процитировано

25
Multivariate short-term wind speed prediction based on PSO-VMD-SE-ICEEMDAN two-stage decomposition and Att-S2S DOI
Xiaoying Sun, Haizhong Liu

Energy, Год журнала: 2024, Номер 305, С. 132228 - 132228

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

23