Performance Predictions of Solar-Assisted Heat Pumps: Methodological Approach and Comparison Between Various Artificial Intelligence Methods by Minghui Ma, Oguzhan Pektezel, Vincenzo Ballerini, Paolo Valdiserri, Eugenia Rossi di Schio

Subjects: “…data-driven intelligent algorithms…”
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Investigating the Predictive Performance of Process Data and Result Data in Complex Problem Solving Using the Conditional Gradient Boosting Algorithm by Fatma Nur Aydin, Kubra Atalay Kabasakal, Ismail Dilek

“…This study aims to examine the predictive performance of process data and result data in complex problem-solving skills using the conditional gradient boosting algorithm. …”
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STOCK PRICE PREDICTION AND SIMULATION USING GEOMETRIC BROWNIAN MOTION-KALMAN FILTER: A COMPARISON BETWEEN KALMAN FILTER ALGORITHMS by Dimas Avian Maulana, A'yunin Sofro, Danang Ariyanto, Riska Wahyu Romadhonia, Affiati Oktaviarina, Mohammad Dian Purnama

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A comparative study of four deep learning algorithms for predicting tree stem radius measured by dendrometer: A case study by Guilherme Cassales, Serajis Salekin, Nick Lim, Dean Meason, Albert Bifet, Bernhard Pfahringer, Eibe Frank

“…High-resolution tree stem radius measurements and predictive simulation through machine learning algorithms offer powerful opportunities for understanding these dynamics. …”
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Efficient Channel Prediction Technique Using AMC and Deep Learning Algorithm for 5G (NR) mMTC Devices by Vipin Sharma, Rajeev Kumar Arya, Sandeep Kumar

“…In this paper, we have proposed a channel prediction scheme based on a deep learning (DL) algorithm possessed by parametric analysis. …”
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Forecasting: Analyze Online and Offline Learning Mode with Machine Learning Algorithms by Farida Ardiani, Rodhiyah Mardhiyyah, Izaaz Azaam Syahalam, Nasmah Nur Amiroh

“…This learning mode opens a new discourse regarding the impact on the learning mode and educational evaluation results. The author aims to compare the results of the educational evaluation of the online learning mode during the pandemic with offline learning mode, so that differences will be known, as well as can be used to predict student learning outcomes, in order to obtain an overview of the effectiveness and efficiency of a learning mode. …”
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Influencing factors and prediction algorithms to estimate public preference for painless medical procedures in China: a national cross-sectional study by Xiangyang Guo, Xiaoxiao Wang, Yanan Song, Chen Luo, Zhengqian Li, Wei You, Sichen Liu, Kaixi Liu

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Predictive model establishment for forward-head posture disorder in primary-school-aged children based on multiple machine learning algorithms by Hongjun Tao, Yang Wen, Rongfang Yu, Yining Xu, Fangliang Yu

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Adaptive drive-based integration technique for predicting rheological and mechanical properties of fresh gangue backfill slurry by Chaowei Dong, Jianfei Xu, Nan Zhou, Jixiong Zhang, Hao Yan, Zejun Li, Yuzhe Zhang

“…Analysis demonstrates that the particle swarm optimal (PSO) algorithm based on adaptive adjustment strategy can effectively optimize the hyperparameters of support vector regression (SVR), and the MC-PSO-SVR model exhibits better predictive capability (R2> 0.88) and lower error coefficients (MAE, RSE, and RMSE values approaching 0) and narrower widths of 95 % confidence intervals for yield stress, plastic viscosity, fluidity, and UCS. …”
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Multi-objective optimization of hybrid microgrid for energy trilemma goals using slime mould algorithm by Alok Kumar Shrivastav, Soham Dutta

“…Compared to conventional metaheuristic such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), the SMA achieves a power loss reduction of 12.3% and a levelized cost of energy (LCOE) improvement of 9.8%. …”
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Automated diabetes detection prediction system based on patients’ medical data by S.V. Pidopryhora, Yu.V. Bogoyavlenska

“…Given the continuous growth of medical data volumes, there is a clear need for modern information technologies capable of automating disease analysis and prediction processes. This paper examines the potential and benefits of implementing machine learning (ML) and artificial intelligence (AI) algorithms for medical data analysis aimed at diabetes detection. …”
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Post, Predict, and Rank: Exploring the Relationship Between Social Media Strategy and Higher Education Institution Rankings by Bruna Rocha, Álvaro Figueira

“…To better understand these strategies, we categorized the posts into five predefined topics—engagement, research, image, society, and education. This categorization, combined with Long Short-Term Memory (LSTM) and a Random Forest (RF) algorithm, was utilized to predict social media output in the last five days of each month, achieving successful results. …”
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Study the Relationship between the University Student and Teacher using the Principal Component Analysis and Genetic Algorithms by Sahar Mahmood

Subjects: “…university education…”
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Machine-learning algorithm to predict home delivery after antenatal care visit among reproductive age women in East Africa by Agmasie Damtew Walle, Shimels Derso Kebede, Jibril Bashir Adem, Daniel Niguse Mamo

“…The random forest (RF) model, selected as the best-performing algorithm, was used to predict home delivery after ANC visits. …”
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Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements by Pramod Kumar, Nagendra Kumar Swarnkar, Om Prakash Mahela, Baseem Khan, Divya Anand, Aman Singh, Juan Luis Vidal Mazon, Fahd S. Alharithi

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Enhanced zebra optimization algorithm for sustainable combined economic and emission dispatch in power systems by Ahmed Arkwazee, Rana Abttan

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Real-time freshness prediction for Apples and Lettuces using imaging recognition and advanced algorithms in a user-friendly mobile application by Chrysanthos Maraveas, George Kalitsios, Marianna I. Kotzabasaki, Dimitrios V. Giannopoulos, Kosmas Dimitropoulos, Anna Vatsanidou

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An interpretable deep learning framework using FCT-SMOTE and BO-TabNet algorithms for reservoir water sensitivity damage prediction by Yin-bo He, Ke-ming Sheng, Ming-liang Du, Guan-cheng Jiang, Teng-fei Dong, Lei Guo, Bo-tao Xu

“…The proposed framework offers a versatile and reliable solution for precise predictive modeling in complex drilling and completion scenarios reliant on tabular data, thereby providing a robust theoretical foundation and algorithmic support for accurate forecasting in the oil and gas industry.…”
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Early characterization and prediction of glioblastoma and brain metastasis treatment efficacy using medical imaging-based radiomics and artificial intelligence algorithms by Noémie N. Moreau, Noémie N. Moreau, Samuel Valable, Cyril Jaudet, Loïse Dessoude, Leleu Thomas, Romain Hérault, Romain Modzelewski, Romain Modzelewski, Dinu Stefan, Juliette Thariat, Juliette Thariat, Alexis Lechervy, Aurélien Corroyer-Dulmont, Aurélien Corroyer-Dulmont

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Prediction of performance and emission features of diesel engine using alumina nanoparticles with neem oil biodiesel based on advanced ML algorithms by M. S. Aswathanrayan, N. Santhosh, Srikanth Holalu Venkataramana, Kurugundla Sunil Kumar, Sarfaraz Kamangar, Amir Ibrahim Ali Arabi, Sameer Algburi, Osamah J. Al-sareji, A. Bhowmik

“…The random forest model demonstrated the highest predictive accuracy for performance (test R2 = 0.9620, Test MAPE = 3.6795%), making it the most reliable statistical approach for predicting BSFC compared to linear regression and decision Tree models. …”
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