Results 61 to 70 of about 6,660,147 (290)

Hybrid Simulation–Machine Learning Surrogates for Coordinate‐Based Solar and Wind Energy Yield Assessment in Iraq: A Streamlit Decision‐Support Tool

Energy Science &Engineering, EarlyView.
This study integrates climatic simulations with machine learning to predict solar and wind energy across Iraq. Results show Random Forest excels for solar (R2 = 0.98) and neural networks for wind (R2 = 0.97), enabling a practical web tool for renewable energy planning. ABSTRACT Driven by the global shift away from fossil fuels, solar and wind resources
Bassam Musheer Kareem, Abdolsalam Ebrahimpour, Jafar Ghafouri, Roghayyeh Motallebzadeh   +3 more
wiley   +1 more source

MODEL PERAMALAN NILAI TUKAR RUPIAH TERHADAP DOLLAR SINGAPURA MENGGUNAKAN METODE HYBRID ARIMA-ANN

Jurnal Lebesgue
This research aims to predict the Rupiah exchange rate against the Singapore Dollar using the hybrid ARIMA-ANN method. The hybrid model is used to increase prediction accuracy by utilizing the ARIMA model to capture linear patterns and the ANN model to ...
Sarah Fadhlia, Eko Primadi Hendri, Deasy Dwi Cahyaningtyas A   +2 more
doaj   +1 more source

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source

Which univariate time series model predicts quicker a crisis? The Iberia case [PDF]

, 1996
In this paper four univariate models are fitted to monthly observations of the number of passengers in the Spanish airline IBERIA from January 1985 to October 1994. During the first part of the sample, the series shows an upward trend which has a rupture
Ruiz Ortega, Esther, Ruiz, Esther, Lorenzo, Fernando   +2 more
core   +1 more source

High Precision Prediction Model of Wind Speed for Underground Mine Tunnel by Using ASTF Net

Energy Science &Engineering, EarlyView.
This paper proposes an Adaptive Spectral‐Temporal Fusion Net (ASTF‐Net), which features a novel decomposition‐ensemble framework with adaptive feature fusion. This design deliberately balances spectral and temporal features and effectively boosts prediction accuracy in complex ventilation environments. ABSTRACT An Adaptive Spectral‐Temporal Fusion Net (
Ruo‐Qi Li, Yong‐Qiang Chai, Lian Shi, Fu‐Gang Wang, Mi Liu   +4 more
wiley   +1 more source

Environmental Control for Edible Fungi Cultivation Based on Temporal Information and Deep Learning

Food Bioengineering, EarlyView.
ABSTRACT Currently, there are still prevalent issues in greenhouse environmental regulation, such as response lag, low control accuracy, and difficulty in coping with sudden environmental disturbances. To achieve high‐precision and dynamic control of the edible fungi cultivation environment, this study proposes an edible fungi environmental control ...
Xiangyan Wang, Shuangcheng Huang, Qingbo Lu, Xinyi Guo   +3 more
wiley   +1 more source

The study of gastronomic tourism in Cordoba and the association of the cuisine. An econometric analysis

Tourism and Hospitality Management, 2016
Purpose – As the city aspires to declare itself as a quality dinning destination, this paper aims to provide some guidelines to achieve that goal. Design – The paper aims to appraise as to what extent the gastronomic product supply of Córdoba can be ...
Genoveva Millán Vázquez de la Torre, Ricardo Hernández Rojas, Virginia Navajas Romero   +2 more
doaj   +1 more source

A projeção dos lucros trimestrais para as companhias brasileiras através de modelos ARIMA [PDF]

, 2009
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Sócio-Econômico, Programa de Pós-Graduação em Economia, Florianópolis, 2009.O estudo trata da aplicação da metodologia Box e Jenkins (1970) para a previsão das séries dos lucros em ...
Fabris, Thiago Rocha
core  

Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia

, 2018
Accurate and reliable forecasting models for electricity demand (G) are critical in engineering applications. They assist renewable and conventional energy engineers, electricity providers, end-users, and government entities in addressing energy ...
Deo, Ravinesh C., Jan F. Adamowski, Adamowski, Jan F., Mohanad S. Al-Musaylh, Ravinesh C. Deo, Al-Musaylh, Mohanad S., Li, Yan, Yan Li   +7 more
core   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source