Deeppipe: Theory-guided prediction method based automatic machine learning for maximum pitting corrosion depth of oil and gas pipeline

Chemical Engineering Science, Journal Year: 2023, Volume and Issue: 278, P. 118927 - 118927

Published: May 29, 2023

Language: Английский

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Bond Graph-CNN based hybrid fault diagnosis with minimum labeled data

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 131, P. 107734 - 107734

Published: Jan. 5, 2024

Language: Английский

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Deeppipe: A two-stage physics-informed neural network for predicting mixed oil concentration distribution

Energy, Journal Year: 2023, Volume and Issue: 276, P. 127452 - 127452

Published: April 10, 2023

Language: Английский

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A Review of State-of-the-Art and Short-Term Forecasting Models for Solar PV Power Generation

Energies, Journal Year: 2023, Volume and Issue: 16(14), P. 5436 - 5436

Published: July 17, 2023

Accurately predicting the power produced during solar generation can greatly reduce impact of randomness and volatility on stability grid system, which is beneficial for its balanced operation optimized dispatch reduces operating costs. Solar PV depends weather conditions, such as temperature, relative humidity, rainfall (precipitation), global radiation, wind speed, etc., it prone to large fluctuations under different conditions. Its characterized by randomness, volatility, intermittency. Recently, demand further investigation into uncertainty short-term prediction effective use in many applications renewable energy sources has increased. In order improve predictive accuracy output develop a precise model, authors used algorithms system. Moreover, since forecasting an important aspect optimizing control systems electricity markets, this review focuses models generation, be verified daily planning smart addition, methods identified reviewed literature are classified according input data source, case studies examples proposed analyzed detail. The contributions, advantages, disadvantages probabilistic compared. Finally, future proposed.

Language: Английский

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Operational day-ahead photovoltaic power forecasting based on transformer variant

Applied Energy, Journal Year: 2024, Volume and Issue: 373, P. 123825 - 123825

Published: July 10, 2024

Language: Английский

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A Review of State-of-the-art and Short-Term Forecasting Models for Solar PV Power Generation

Published: May 23, 2023

Accurately predicting the power of solar generation can greatly reduce impact randomness and volatility on stability grid system, which is beneficial for balanced operation optimized dispatch reduces operating costs. Solar PV depends weather conditions, are prone to large fluctuations under different conditions. Its characterized by randomness, intermittency. Recently, demand further investigation effective use uncertainty short-term prediction has been getting increasing attention in many application renewable energy sources. In order improve predictive accuracy output develop a precise model, authors worked algorithms system. Moreover, since forecasting one important aspects optimizing control systems electricity markets, this review focuses models generation, be verified daily planning smart addition, methods reviewed literature classified according input data source used accurate models, case studies examples proposed analyzed detail. The contributions, advantages disadvantages probabilistic compared. Finally, future proposed.

Language: Английский

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Machine Learning Algorithms in Photovoltaics: Evaluating Accuracy and Computational Cost Across Datasets of Different Generations, Sizes, and Complexities

Journal of Electronic Materials, Journal Year: 2024, Volume and Issue: 53(3), P. 1530 - 1538

Published: Jan. 17, 2024

Language: Английский

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Adaptive masked network for ultra-short-term photovoltaic forecast

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 139, P. 109555 - 109555

Published: Nov. 7, 2024

Language: Английский

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Plantas de fresa regeneradas in vitro mediante organogénesis directa en diferentes concentraciones de auxinas y citocininas

Bioagro, Journal Year: 2025, Volume and Issue: 37(1), P. 123 - 134

Published: Jan. 1, 2025

La fresa (Fragaria x ananassa) es una especie vegetal de gran importancia económica y agroalimentaria, que se cultiva en regiones agroindustriales México, como el Bajío. El principal insumo la producción agrícola son las plantas, cuya primera etapa multiplicación empieza con formación clones por cultivo in vitro a partir plantas madre seleccionadas. Sin embargo, diversas características regeneradas pueden presentar variaciones reducen su valor agronómico comercial. Dicha variabilidad debida múltiples factores, aunque destaca efecto tienen combinaciones auxinas citocininas, así sus concentraciones. objetivo del presente estudio fue evaluar mediante organogénesis directa ante diferentes concentraciones citocininas. Los explantes obtuvieron meristemos apicales los estolones variedad Camino Real. Se utilizaron 21 tratamientos (AIB 2,4-D) citocininas (BAP cinetina) para organogénesis. mayor número vitroplantas obtuvo combinación AIB BAP 0,4 mg·L-1, tasa regeneración promedio 68,3 %. En dicho tratamiento presentaron mejor desarrollo alta respuesta antioxidante. concentración prolina 1,7 µg mL-1, control sin ni

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New Energy Power Generation Prediction Based on CNN-LSTM-Attention Model and Risk Detection Analysis of Isolation Forest Algorithm

Journal of Image and Signal Processing, Journal Year: 2025, Volume and Issue: 14(01), P. 45 - 61

Published: Jan. 1, 2025

Language: Английский

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