Enhancing sand cat swarm optimization based on multi-strategy mixing for solving engineering optimization problems DOI
Wenchuan Wang, Zheng Han, Zhao Zhang

et al.

Evolutionary Intelligence, Journal Year: 2024, Volume and Issue: 18(1)

Published: Nov. 16, 2024

Language: Английский

Advancing Truss Structure Optimization— A Multi-Objective Weighted Average Algorithm with Enhanced Convergence and Diversity DOI Creative Commons

Divya Adalja,

Kanak Kalita, Lenka Čepová

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104241 - 104241

Published: Feb. 1, 2025

Language: Английский

Citations

3
An enhanced ivy algorithm fusing multiple strategies for global optimization problems DOI

Chunqiang Zhang,

Wenzhou Lin, Gang Hu

et al.

Advances in Engineering Software, Journal Year: 2025, Volume and Issue: 203, P. 103862 - 103862

Published: Feb. 6, 2025

Language: Английский

Citations

1
Enhanced monthly streamflow prediction using an input–output bi-decomposition data driven model considering meteorological and climate information DOI

Qiucen Guo,

Xuehua Zhao, Yuhang Zhao

et al.

Stochastic Environmental Research and Risk Assessment, Journal Year: 2024, Volume and Issue: 38(8), P. 3059 - 3077

Published: April 27, 2024

Language: Английский

Citations

5
A Multi-strategy Slime Mould Algorithm for Solving Global Optimization and Engineering Optimization Problems DOI
Wenchuan Wang,

Wenhui Tao,

Wei-can Tian

et al.

Evolutionary Intelligence, Journal Year: 2024, Volume and Issue: 17(5-6), P. 3865 - 3889

Published: July 15, 2024

Language: Английский

Citations

3
Advancing Engineering Solutions with Protozoa-Based Differential Evolution: A Hybrid Optimization Approach DOI Creative Commons
Hussam N. Fakhouri, Faten Hamad, Abdelraouf Ishtaiwi

et al.

Automation, Journal Year: 2025, Volume and Issue: 6(2), P. 13 - 13

Published: March 28, 2025

This paper presents a novel Hybrid Artificial Protozoa Optimizer with Differential Evolution (HPDE), combining the biologically inspired principles of (APO) powerful optimization strategies (DE) to address complex and engineering design challenges. The HPDE algorithm is designed balance exploration exploitation features, utilizing innovative features such as autotrophic heterotrophic foraging behaviors, dormancy, reproduction processes alongside DE strategy. performance was evaluated on CEC2014 benchmark functions, it compared against two sets state-of-the-art optimizers comprising 23 different algorithms. results demonstrate HPDE’s good performance, outperforming competitors in 24 functions out 30 from first set second set. Additionally, has been successfully applied range problems, including robot gripper optimization, welded beam pressure vessel spring speed reducer cantilever three-bar truss optimization. consistently showcase solving these problems when competing

Language: Английский

Citations

0
A novel reward-based golden jackal optimization algorithm uses mix-weighted dynamic and random opposition learning to solve optimization problems DOI

Sarada Mohapatra,

Priteesha Sarangi,

Prabhujit Mohapatra

et al.

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(5)

Published: April 28, 2025

Language: Английский

Citations

0
Diversity-enhanced adaptive golden jackal optimization based on multi-strategy and its engineering applications DOI
Wenjie Wang,

Boqin Zhang,

Zhao Liu

et al.

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(5)

Published: April 28, 2025

Language: Английский

Citations

0
Artificial Rabbit Optimizer with deep learning for fall detection of disabled people in the IoT Environment DOI Creative Commons

Eatedal Alabdulkreem,

Mesfer Alduhayyem,

Mohammed Abdullah Al-Hagery

et al.

AIMS Mathematics, Journal Year: 2024, Volume and Issue: 9(6), P. 15486 - 15504

Published: Jan. 1, 2024

<abstract> <p>Fall detection (FD) for disabled persons in the Internet of Things (IoT) platform contains a combination sensor technologies and data analytics automatically identifying responding to samples falls. In this regard, IoT devices like wearable sensors or ambient from personal space role vital play always monitoring user's movements. FD employs deep learning (DL) an using sensors, namely accelerometers depth cameras, capture connected human DL approaches are frequently recurrent neural networks (RNNs) convolutional (CNNs) that have been trained on various databases recognizing patterns with The methods then executed edge cloud environments real-time investigation incoming data. This method differentiates normal activities potential falls, triggering alerts reports caregivers emergency numbers once fall is identified. We designed Artificial Rabbit Optimizer DL-based classification (ARODL-FDC) system environment. ARODL-FDC approach proposes detect categorize events assist elderly people people. technique comprises four-stage process. Initially, preprocessing input performed by Gaussian filtering (GF). applies residual network (ResNet) model feature extraction purposes. Besides, ARO algorithm has utilized better hyperparameter choice ResNet algorithm. At final stage, full Elman Neural Network (FENN) recognition events. experimental results can be tested dataset. simulation inferred reaches promising performance over compared models concerning measures.</p> </abstract>

Language: Английский

Citations

2
CGJO: a novel complex-valued encoding golden jackal optimization DOI Creative Commons
Jinzhong Zhang, Gang Zhang,

Min Kong

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 23, 2024

Golden jackal optimization (GJO) is inspired by mundane characteristics and collaborative hunting behaviour, which mimics foraging, trespassing encompassing, capturing prey to refresh a jackal's position. However, the GJO has several limitations, such as slow convergence rate, low computational accuracy, premature convergence, poor solution efficiency, weak exploration exploitation. To enhance global detection ability this paper proposes novel complex-valued encoding golden (CGJO) achieve function engineering design. The strategy deploys dual-diploid organization encode real imaginary portions of converts dual-dimensional region single-dimensional manifestation region, increases population diversity, restricts search stagnation, expands area, promotes information exchange, fosters collaboration efficiency improves accuracy. CGJO not only exhibits strong adaptability robustness supplementary advantages but also balances local exploitation promote precision determine best solution. CEC 2022 test suite six real-world designs are utilized evaluate effectiveness feasibility CGJO. compared with three categories existing algorithms: (1) WO, HO, NRBO BKA recently published algorithms; (2) SCSO, GJO, RGJO SGJO highly cited (3) L-SHADE, LSHADE-EpsSin CMA-ES performing algorithms. experimental results reveal that superior those other superiority reliability quicker greater computation precision, stability robustness.

Language: Английский

Citations

2
PMSOMA: optical microscope algorithm based on piecewise linear chaotic mapping and sparse adaptive exploration DOI Creative Commons

Linyi Guo,

Wei Gu

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Sept. 6, 2024

Language: Английский

Citations

2