Damage detection of civil structures based on hybrid optimization algorithm and combined correlation function of heterogeneous responses

Measurement, Journal Year: 2025, Volume and Issue: unknown, P. 116678 - 116678

Published: Jan. 1, 2025

Language: Английский

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

Computer Science Review, Journal Year: 2025, Volume and Issue: 57, P. 100740 - 100740

Published: March 3, 2025

Language: Английский

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Air quality and ventilation: exploring solutions for healthy and sustainable urban environments in times of climate change

Results in Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 103157 - 103157

Published: Oct. 1, 2024

Language: Английский

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A multi-objective optimization method for enclosed-space lighting design based on MOPSO

Building and Environment, Journal Year: 2024, Volume and Issue: 250, P. 111185 - 111185

Published: Jan. 10, 2024

Language: Английский

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Forecasting solar power generation using evolutionary mating algorithm-deep neural networks

Energy and AI, Journal Year: 2024, Volume and Issue: 16, P. 100371 - 100371

Published: April 17, 2024

This paper proposes an integration of recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) in optimizing the weights and biases deep neural networks (DNN) for forecasting solar power generation. The study employs a Feed Forward Neural Network (FFNN) to forecast AC output using real plant measurements spanning 34-day period, recorded at 15-minute intervals. intricate nonlinear relationship between irradiation, ambient temperature, module temperature is captured accurate prediction. Additionally, conducts comprehensive comparison with established algorithms, including Differential Evolution (DE-DNN), Barnacles Optimizer (BMO-DNN), Particle Swarm Optimization (PSO-DNN), Harmony Search (HSA-DNN), DNN Adaptive Moment Estimation optimizer (ADAM) Nonlinear AutoRegressive eXogenous inputs (NARX). experimental results distinctly highlight exceptional performance EMA-DNN by attaining lowest Root Mean Squared Error (RMSE) during testing. contribution not only advances methodologies but also underscores potential merging algorithms contemporary improved accuracy reliability.

Language: Английский

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Daily allocation of energy consumption forecasting of a power distribution company using optimized least squares support vector machine

Results in Control and Optimization, Journal Year: 2025, Volume and Issue: unknown, P. 100518 - 100518

Published: Jan. 1, 2025

Language: Английский

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A review of the influencing factors of building energy consumption and the prediction and optimization of energy consumption

AIMS energy, Journal Year: 2025, Volume and Issue: 13(1), P. 35 - 85

Published: Jan. 1, 2025

<p>Concomitant with the expeditious growth of construction industry, challenge building energy consumption has become increasingly pronounced. A multitude factors influence operations, thereby underscoring paramount importance monitoring and predicting such consumption. The advent big data engendered a diversification in methodologies employed to predict Against backdrop influencing operation consumption, we reviewed advancements research pertaining supervision prediction deliberated on more energy-efficient low-carbon strategies for buildings within dual-carbon context, synthesized relevant progress across four dimensions: contemporary state supervision, determinants optimization Building upon investigation three predictive were examined: (ⅰ) Physical methods, (ⅱ) data-driven (ⅲ) mixed methods. An analysis accuracy these revealed that methods exhibited superior precision actual Furthermore, predicated this foundation identified determinants, also explored prediction. Through an in-depth examination prediction, distilled pertinent accurate forecasting offering insights guidance pursuit conservation emission reduction.</p>

Language: Английский

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The application performance of individualized radiant cooling and heating systems, a review

Building and Environment, Journal Year: 2024, Volume and Issue: 256, P. 111488 - 111488

Published: April 5, 2024

Language: Английский

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Study on the degradation models based on the experiments considering the coupling effect of freeze-thaw and carbonation

Structures, Journal Year: 2024, Volume and Issue: 64, P. 106659 - 106659

Published: May 31, 2024

Language: Английский

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Enerji Sistemlerinde Metasezgisel Optimizasyon Teknikleri: Yenilikçi Algoritmalar ve Uygulama Alanları

Sürdürülebilir Mühendislik Uygulamaları ve Teknolojik Gelişmeler Dergisi, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 25, 2024

Optimizasyon, tüm olası alternatifler arasından bir problemin en optimal çözümünü belirleme sürecidir. Enerji sistemlerinde metasezgisel optimizasyon algoritmaları, karmaşık enerji problemlerini çözmede önemli rol oynamaktadır. Metasezgisel genetik algoritmalar, parçacık sürü optimizasyonu, simüle edilen tavlama, karınca kolonisi optimizasyonu gibi doğal süreçlerden esinlenerek geliştirilen ve genellikle bilgisayar tabanlı modellerle kullanılan özel yöntemleridir. büyük veri setleriyle çalışabilir farklı kısıtlamalar altında optimize edilmesi gereken çok sayıda değişkeni ele alabilirler. Bu nedenle sektöründe sürdürülebilirlik, verimlilik karlılık açısından öneme sahiptirler. verimliliğini artırmak, maliyetini azaltmak, üretimi, dağıtımı, tüketimi depolanması sistemlerinin bileşenlerini etmek için, yenilenebilir kaynaklarını entegre karbon ayak izini azaltmak çeşitli hedeflere ulaşmak için kullanılmaktadırlar. çalışmada, sistemleri uygulamalarında algoritmalarının kullanımı örnekler üzerinden incelenmiştir. algoritmaların ile problemlerin çözümlerinin daha kolaya indirgendiği görülmüştür.

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