Real-Time Data-Driven Estimation of Production for Point Bottom Sealing and Cutting Machines Using Machine Learning

Systems and Soft Computing, Год журнала: 2025, Номер unknown, С. 200194 - 200194

Опубликована: Фев. 1, 2025

Язык: Английский

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Fishing cat optimizer: a novel metaheuristic technique

Engineering Computations, Год журнала: 2025, Номер unknown

Опубликована: Фев. 10, 2025

Purpose The fishing cat's unique hunting strategies, including ambush, detection, diving and trapping, inspired the development of a novel metaheuristic optimization algorithm named Fishing Cat Optimizer (FCO). purpose this paper is to introduce FCO, offering fresh perspective on demonstrating its potential for solving complex problems. Design/methodology/approach FCO structures process into four distinct phases. Each phase incorporates tailored search strategy enrich diversity population attain an optimal balance between extensive global exploration focused local exploitation. Findings To assess efficacy algorithm, we conducted comparative analysis with state-of-the-art algorithms, COA, WOA, HHO, SMA, DO ARO, using test suite comprising 75 benchmark functions. findings indicate that achieved results 88% functions, whereas SMA which ranked second, excelled only 21% Furthermore, secured average ranking 1.2 across sets CEC2005, CEC2017, CEC2019 CEC2022, superior convergence capability robustness compared other comparable algorithms. Research limitations/implications Although performs excellently in single-objective problems constrained problems, it also has some shortcomings defects. First, structure relatively there are many parameters. value parameters certain impact Second, computational complexity high. When high-dimensional takes more time than algorithms such as GWO WOA. Third, although multimodal rarely obtains theoretical solution when combinatorial Practical implications applied five common engineering design Originality/value This innovatively proposes mimics mechanisms cats, strategies lurking, perceiving, rapid precise trapping. These abstracted closely connected iterative stages, corresponding in-depth exploration, multi-dimensional fine developmental localized refinement contraction search. enables efficient fine-tuning environments, significantly enhancing algorithm's adaptability efficiency.

Язык: Английский

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Research and Application of Optimization of Physical Education Training Model Based on Multi-Objective Differential Evolutionary Algorithm

Systems and Soft Computing, Год журнала: 2025, Номер unknown, С. 200200 - 200200

Опубликована: Фев. 1, 2025

Язык: Английский

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Frequency Regulation of Two-Area Thermal and Photovoltaic Power System via Flood Algorithm

Results in Control and Optimization, Год журнала: 2025, Номер 18, С. 100539 - 100539

Опубликована: Фев. 21, 2025

Язык: Английский

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Efficient Optimization of Engineering Problems With A Particular Focus on High‐Order IIR Modeling for System Identification Using Modified Dandelion Optimizer

Optimal Control Applications and Methods, Год журнала: 2025, Номер unknown

Опубликована: Фев. 24, 2025

ABSTRACT This paper introduces the modified dandelion optimizer (mDO), a novel adaptive metaheuristic algorithm designed to address complex engineering optimization challenges, with focus on infinite impulse response (IIR) system identification. The proposed mDO incorporates three key advancements: an enhanced descending phase improve global exploration, exploration‐exploitation that balances search intensity and breadth, self‐adaptive crossover operator refines solutions dynamically. These innovations specifically target challenges associated high‐order IIR modeling, enabling deliver more precise efficient To validate its performance, was rigorously evaluated across diverse testing environments, including CEC2017 CEC2022 benchmark functions, various model identification scenarios, real‐world design problems such as multi‐product batch plant design, multiple disk clutch brake speed reducer design. Comparative analyses reveal consistently outperforms leading algorithms in terms of accuracy, robustness, computational efficiency, particularly complex, high‐dimensional landscapes. Statistical assessments further confirm mDO's superior capability accurately identifying parameters even under noise varying orders. study positions competitive versatile tool for applications, offering significant improvements accuracy adaptability advanced modeling problem‐solving.

Язык: Английский

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A Method for Predicting the Morphology of Multi-track Laser Cladding Coatings Based on WOA-RF

International Journal of Precision Engineering and Manufacturing-Green Technology, Год журнала: 2025, Номер unknown

Опубликована: Март 13, 2025

Язык: Английский

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Optimization Model of Steel‐Prestressed Concrete Hybrid Wind Turbine Tower: Using a Combined Differential Whale Optimization Algorithm

The Structural Design of Tall and Special Buildings, Год журнала: 2025, Номер 34(5)

Опубликована: Март 14, 2025

ABSTRACT This study proposes a combined differential whale optimization algorithm (CDWOA) to evaluate the cost model of steel‐prestressed concrete hybrid wind turbine tower (WTT) structures: (1) For WTTs, chosen optimal scale factors F 1 = 0.005 and 2 0.03 lead fast stable WTT structures; (2) establishing relatively complete set design constraints for concrete. also effectually helps overcome key problems large amounts calculation time caused by repeated structural analysis. The results demonstrate that CDWOA offers significant advantages in optimizing WTTs compared traditional algorithms. Particularly ultrahigh exhibits superior applicability. Furthermore, savings achieved increase with height. Finite element analysis indicates primary constraint governing convergence is fatigue strength, aligning well model's calculated results.

Язык: Английский

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Optimization of CO2 emissions of composite alveolar beams considering manufacturing constraints

REM - International Engineering Journal, Год журнала: 2025, Номер 78(2)

Опубликована: Янв. 1, 2025

Abstract The increasing concern over the scarcity of natural resources has driven search for more sustainable structural designs. Among various alternatives, steel-concrete composite cellular structures have emerged as a good solution large spans, combining strength properties concrete and steel without significantly structure's mass. This article presents formulation optimization beams aimed at minimizing carbon dioxide (CO2) emissions. In addition to materials used, emissions from manufacturing processes, specifically cutting welding profiles, are also considered. problem was addressed using Particle Swarm Optimization (PSO) Grey Wolf Optimizer (GWO), numerical examples provided investigate advantages proposed compared welded beams. results, it observed that similar solutions were obtained with both methods. addition, varying span in range 5 17.5 m, possible identify profiles configurations efficient regarding weight environmental impact. best results almost all spans Litzka beam, except m span, which Peiner beam had lowest CO2 emission.

Язык: Английский

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A new neural network–assisted hybrid chaotic hiking optimization algorithm for optimal design of engineering components

Materials Testing, Год журнала: 2025, Номер unknown

Опубликована: Апрель 11, 2025

Abstract In the era of artificial intelligence (AI), optimization and parametric studies engineering structural systems have become feasible tasks. AI ML (machine learning) offer advantages over classical techniques, which often face challenges such as slower convergence, difficulty handling multiobjective functions, high computational time. Modern techniques may not effectively address all critical design problems despite these advancements. Nature-inspired algorithms based on physical phenomena in nature, human behavior, swarm intelligence, evolutionary principles present a viable alternative for multidisciplinary challenges. This article explores various using newly developed modified hiking algorithm (HOA). The is inspired by hill climbing hiker speed. HOA are compared with those several famous from literature, demonstrating superior results terms statistical measures.

Язык: Английский

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A Modified Black-winged Kite Optimizer Based on Chaotic Maps for Global Optimization of Real-World Applications

Knowledge-Based Systems, Год журнала: 2025, Номер unknown, С. 113558 - 113558

Опубликована: Апрель 1, 2025

Язык: Английский

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