Efficient multiplayer battle game optimizer for numerical optimization and adversarial robust neural architecture search DOI Creative Commons
Rui Zhong, Yuefeng Xu, Chao Zhang

и другие.

Alexandria Engineering Journal, Год журнала: 2024, Номер 113, С. 150 - 168

Опубликована: Ноя. 18, 2024

Язык: Английский

The Study of Convex Quadratic Optimization Problems with Indicator Variables DOI

宗丹 刘

Operations Research and Fuzziology, Год журнала: 2025, Номер 15(02), С. 302 - 312

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Progressive DNN-metaheuristics for programmable broadband mechanical metamaterial absorbers design DOI
Tae Sun Park,

Dowon Noh,

Jeongwoo Lee

и другие.

International Journal of Mechanical Sciences, Год журнала: 2025, Номер unknown, С. 110297 - 110297

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Machine tool FEM model correction assisted by dynamic evolution sequence DOI Creative Commons
Weihao Lin, Peng Zhong,

Xindi Wei

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Май 29, 2025

In the simulation analysis of large-scale industrial instruments such as machine tools, in order to ensure accuracy, model parameter correction is necessary. This research presents a tool method assisted by dynamic evolution sequence (DES). The first introduces generate uniformly distributed sequence, replacing traditional used Kriging surrogate models, and constructing more accurate for tools. Moreover, random with enhances search space coverage heterogeneous comprehensive learning particle swarm optimization (HCLPSO) algorithm. results numerical examples demonstrate that finite element model, corrected using proposed method, accurately predicts true displacement responses tool. offers new solution addressing static problems.

Язык: Английский

Процитировано

0

A review on shape optimization of hulls and airfoils leveraging Computational Fluid Dynamics Data-Driven Surrogate models DOI Creative Commons
Jake M. Walker, Andrea Coraddu, Luca Oneto

и другие.

Ocean Engineering, Год журнала: 2024, Номер 312, С. 119263 - 119263

Опубликована: Сен. 19, 2024

Язык: Английский

Процитировано

2

RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review DOI Creative Commons

Wang Yejiao,

Hazalila Kamaludin, Nayef Abdulwahab Mohammed Alduais

и другие.

IEEE Access, Год журнала: 2024, Номер 12, С. 64980 - 64996

Опубликована: Янв. 1, 2024

With the development of intelligent manufacturing in China, Radio Frequency Identification (RFID), a key technology for smart factories, has received widespread attention. As RFID applications expand, so does size their networks. It makes it more difficult to ensure signal coverage, leads communication problems, and increases equipment energy consumption costs, thereby posing challenges realm network planning (RNP). The RNP problem needs consider multiple objectives constraints such as conflicts, economic benefit, load balance which have been proven be optimized by swarm optimization algorithms. Therefore, this study reviews technology, intelligence algorithms planning. improvement direction factors affecting performance are also explored. In addition, analyzes problems discusses innovations drawbacks these approaches. Finally, some research limitations directions identified.

Язык: Английский

Процитировано

1

Optimizing Warehouse Building Design for Simultaneous Revenue Generation and Carbon Reduction in Taiwan: A Fuzzy Nonlinear Multi-Objective Approach DOI Creative Commons
Kanglin Chiang

Buildings, Год журнала: 2024, Номер 14(8), С. 2441 - 2441

Опубликована: Авг. 7, 2024

Taiwan’s encouragement of installing solar photovoltaic power plants (SPPPs) on warehouse rooftops is a step towards sustainability and profitable investment. This study, analyzing the installations STY Company, found that rooftop SPPPs significantly boost revenue, with rates increasing from 2.0088% to 6.8681% over 20 years. The break-even point in 7th year, return rate ranging 2.0088 2.1748%. shows SPPP investments are benefit for investors, shortening construction times allowing warehouses sell energy at an earlier date. research utilized fuzzy nonlinear multi-objective programming model examine trade-offs between time, cost, quality, revenue (TCQR) optimize construction. findings suggest reducing time effective strategy lower carbon emissions despite potential cost increases. However, quality costs inversely proportional, highlighting importance efficient project management minimizing impacts this trade-off. Adjusting funding can maintain while speeding up Completing projects early also heightens green sales, offsetting higher initial investments. TCQR focuses investment managing efficiently, making data-driven decisions expedite development. improves profitability promotes sustainable growth by optimizing financial strategies. study’s contribution includes: 1. Optimizing installation process SPPPs, which provide significant long-term environmental benefits. 2. Combining different methods scholars into solve complex systems high uncertainty. put forth study closer actual situation handle balancing problems programming. 3. Improving efficiency make it feasible reduce emissions. 4. Concocting comprehensive approach integrating financial, environmental, operational factors successful addresses academic gap. Previously, conducted independently, focusing solely or (TCQ) issues without considering two together. By combining TCQ, fills gap research. According better returns could improve promotion energy. Unlike previous research, integrates analysis TCQ assessing revenues allows decision-makers derive judgments quickly.

Язык: Английский

Процитировано

1

FOX-TSA: Navigating Complex Search Spaces and Superior Performance in Benchmark and Real-World Optimization Problems DOI Creative Commons

Sirwan A. Aula,

Tarik A. Rashid

Ain Shams Engineering Journal, Год журнала: 2024, Номер unknown, С. 103185 - 103185

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

1

Inchworm Search Algorithm: A Memory-Saving Nature-Inspired Metaheuristic Algorithm for Real-World Online Optimization Problems DOI
Zhihao Yu, Jialu Du, Guangqiang Li

и другие.

Опубликована: Янв. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Язык: Английский

Процитировано

0

A novel similarity algorithm for triangular cloud models based on exponential closeness and cloud drop variance DOI Creative Commons
Jianjun Yang, Jiahao Han,

Qilin Wan

и другие.

Complex & Intelligent Systems, Год журнала: 2024, Номер 10(4), С. 5171 - 5194

Опубликована: Апрель 20, 2024

Abstract Cloud model similarity algorithm is an important part of cloud modelling theory. Most the existing algorithms suffer from poor discriminability, classification, unstable results, and low time efficiency. In this paper, a new proposed that considers triangular distance shape. First, according to $${{D}}_{\text{T}}$$ D T formula, exponential closeness measure defined, with which models characterized. Then, shape calculated variance drops. Finally, two similarities are synthesized define for determining formula based on (DD T STCM). stability, efficiency theoretical interpretability taken as evaluation indices. Equipment security system capability experiment, differentiation simulation experiment series classification accuracy set up verify effectiveness in terms four above aspects. The experimental results show DD STCM has good excellent effects. series, average reaches 91.78%, at least 2.78% higher than those other seven commonly used algorithms. CPU running also extremely high, group training always order milliseconds, effectively reduces cost. case study conducted analyse risk assessment problem China’s island microgrid industry, line human cognition have value engineering applications. Graphical abstract

Язык: Английский

Процитировано

0

Intelligent device recognition of internet of things based on machine learning DOI Creative Commons
Sheng Huang

Intelligent Systems with Applications, Год журнала: 2024, Номер 22, С. 200368 - 200368

Опубликована: Апрель 12, 2024

With the rapid popularization and application of Internet Things technology, smart devices have become an indispensable part people's daily lives. Therefore, it is crucial to accurately identify these as their numbers continue grow. The research aimed introduce a lightweight method for identifying based on network flow characteristics scheduling algorithms. This can improve device identification accuracy while maintaining high efficiency. constructed comprehensive optimization algorithm selection framework achieve performance in different scenarios. took into account many factors, including traffic characteristics, requirements, system efficiency, ensure flexible adaptation scenarios optimize overall performance. Research results showed that proposed had 96.8 % at 1-minute intervals, which increased 99.7 10-minute reached 99.9 both 30-minute 60-minute intervals. In 100 experiments, improved by average 1.5 compared with baseline. fingerprint recognition, long short-term memory exceeded 90 %, area under curve 0.99. Most over 95 recall rate remained around effectiveness study was further verified. not only efficiency but also provided powerful solutions field security. provides useful guidance practical applications related fields.

Язык: Английский

Процитировано

0