Kun Li¹, Tianfu Li^2,*, Xiuwei Wang¹, Qingchun Meng¹, Zhenjie Wang¹, Jinyang Luo^1,2, Zhaohui Wang¹, Yuedong Yao²

Energy Engineering, Vol.122, No.6, pp. 2215-2238, 2025, DOI:10.32604/ee.2025.062876 - 29 May 2025

Abstract CO₂ flooding for enhanced oil recovery (EOR) not only enables underground carbon storage but also plays a critical role in tertiary oil recovery. However, its displacement efficiency is constrained by whether CO₂ and crude oil achieve miscibility, necessitating precise prediction of the minimum miscibility pressure (MMP) for CO₂-oil systems. Traditional methods, such as experimental measurements and empirical correlations, face challenges including time-consuming procedures and limited applicability. In contrast, artificial intelligence (AI) algorithms have emerged as superior alternatives due to their efficiency, broad applicability, and high prediction accuracy. This study employs four AI algorithms—Random Forest Regression (RFR), Genetic… More >

Kumail Javaid¹, Ayesha Siddiqa², Syed Abbas Zilqurnain Naqvi², Allah Ditta³, Muhammad Ahsan², M. A. Khan⁴, Tariq Mahmood⁵, Muhammad Adnan Khan^6,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4425-4442, 2022, DOI:10.32604/cmc.2022.022984 - 14 January 2022

Abstract Artificial intelligence (AI) and machine learning (ML) help in making predictions and businesses to make key decisions that are beneficial for them. In the case of the online shopping business, it’s very important to find trends in the data and get knowledge of features that helps drive the success of the business. In this research, a dataset of 12,330 records of customers has been analyzed who visited an online shopping website over a period of one year. The main objective of this research is to find features that are relevant in terms of correctly predicting… More >

R. Saravana Ram^1,*, M. Vinoth Kumar², N. Krishnamoorthy³, A. Baseera⁴, D. Mansoor Hussain⁵, N. Susila⁶

Computer Systems Science and Engineering, Vol.42, No.2, pp. 545-460, 2022, DOI:10.32604/csse.2022.021681 - 04 January 2022

Abstract Major fields such as military applications, medical fields, weather forecasting, and environmental applications use wireless sensor networks for major computing processes. Sensors play a vital role in emerging technologies of the 20th century. Localization of sensors in needed locations is a very serious problem. The environment is home to every living being in the world. The growth of industries after the industrial revolution increased pollution across the environment. Owing to recent uncontrolled growth and development, sensors to measure pollution levels across industries and surroundings are needed. An interesting and challenging task is choosing the place… More >

Ayesha Siddiqa¹, Syed Abbas Zilqurnain Naqvi¹, Muhammad Ahsan¹, Allah Ditta², Hani Alquhayz³, M. A. Khan⁴, Muhammad Adnan Khan^5,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5519-5536, 2022, DOI:10.32604/cmc.2022.021666 - 11 October 2021

Abstract Due to unforeseen climate change, complicated chronic diseases, and mutation of viruses’ hospital administration’s top challenge is to know about the Length of stay (LOS) of different diseased patients in the hospitals. Hospital management does not exactly know when the existing patient leaves the hospital; this information could be crucial for hospital management. It could allow them to take more patients for admission. As a result, hospitals face many problems managing available resources and new patients in getting entries for their prompt treatment. Therefore, a robust model needs to be designed to help hospital administration… More >

Fuyun Zhu, Guoqing Wu^*

Energy Engineering, Vol.118, No.6, pp. 1703-1712, 2021, DOI:10.32604/EE.2021.015602 - 10 September 2021

Abstract Accurate power load forecasting plays an important role in the power dispatching and security of grid. In this paper, a mathematical model for power load forecasting based on the random forest regression (RFR) was established. The input parameters of RFR model were determined by means of the grid search algorithm. The prediction results for this model were compared with those for several other common machine learning methods. It was found that the coefficient of determination (R²) of test set based on the RFR model was the highest, reaching 0.514 while the corresponding mean absolute error (MAE) More >