Quantum resonant dimensionality reduction by Fan Yang, Furong Wang, Xusheng Xu, Pan Gao, Tao Xin, ShiJie Wei, Guilu Long

“…Here, we propose a quantum resonant dimensionality reduction (QRDR) algorithm based on the quantum resonant transition to reduce the dimension of input data and accelerate the quantum machine learning algorithms. …”
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Ensemble design for seasonal climate predictions: studying extreme Arctic sea ice lows with a rare event algorithm by J. Sauer, F. Massonnet, G. Zappa, F. Ragone

“…Here, we apply a rare event algorithm to ensemble simulations with the intermediate-complexity coupled climate model PlaSim-LSG to study extremes of pan-Arctic sea ice area reduction under pre-industrial greenhouse gas conditions. …”
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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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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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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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Optimizing knee osteoarthritis severity prediction on MRI images using deep stacking ensemble technique by Punita Panwar, Sandeep Chaurasia, Jayesh Gangrade, Ashwani Bilandi, Dayananda Pruthviraja

“…In order to address the limitation of time and expedite the diagnostic process, deep learning algorithms have been implemented in the medical field. …”
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Reference frame list optimization algorithm in video coding by quality enhancement of the nearest picture by Junyan HUO, Ruipeng QIU, Yanzhuo MA, Fuzheng YANG

“…Interframe prediction is a key module in video coding, which uses the samples in the reference frames to predict those in the current picture, thus helps to represent the complex video by transmitting a small amount of the prediction residual.In lossy video coding, the qualities of reference frames are affected by the quantization distortion, which lead to poor prediction accuracy and performance degradation.Targeted at the low latency video services, a reference frame list optimization algorithm was proposed, which enhanced the quality of the nearest reference frame by a deep learning-based convolutional neural network, and integrated the enhanced reference frame into the reference frame list to improve the accuracy of interframe prediction.Compared with H.265/HEVC reference software HM16.22, the proposed algorithm provides BD-rate savings of 9.06%, 14.92% and 13.19% for Y, Cb and Cr components, respectively.…”
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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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Prediction and management of physical injuries caused by gym equipment and facilities using a Support Vector Machine (SVM) algorithm by Javad Shahlaei Bagheri

“…Purpose: This study aimed to predict and manage physical injuries caused by gym equipment and facilities using the SVM algorithm.Method: This study was of a developmental-applied type. …”
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Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms by Yuki Hanawa, Tomohiro Harada, Yukiya Miura

Subjects: “…Surrogate-assisted evolutionary algorithms…”
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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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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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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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