EMPLOYING GENETIC ALGORITHM INSPIRED HYPERPARAMETER OPTIMIZATION IN MOBILE NET V2 ARCHITECTURE by Baljinder Kaur, Manik Rakhra, Nonita Sharma, Monika Mangla

Subjects: “…predictive modeling…”
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Fault Risk Assessment of Transmission Lines Under Extreme Weather Conditions Based on Genetic Algorithm Back-Propagation Neural Network by Jialu Li, Ruilin Lei, Yongqiang Gao, Aoyu Lei, Junqiu Fan, Yong Mei, Wenwei Tao, Haohuai Wang, Linzi Wang, Taiji Li, Qiansheng Zhao

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Three-dimensional Underwater Dynamic Target Tracking Based on Adaptive Interactive Multi-model Algorithm by QIN Hongmao, YE Hongwei, CUI Qingjia, XU Biao, HU Manjiang

“…In response to this, the paper introduces an adaptive parallel IMM (APIMM) based on current adaptive IMM algorithms. This method adaptively adjusts transition probabilities and pairs with the unscented Kalman filter (UKF) algorithm for state prediction of maneuvering targets in a 3D underwater environment. …”
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From Tension to Triumph: Design and Implementation of an Innovative Algorithmic Metric for Quantifying Individual Performance in Women Volleyball’s Critical Moments by Carlos López-Serrano, María Zakynthinaki, Daniel Mon-López, Juan José Molina Martín

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AI-Driven Predictive Maintenance in Mining: A Systematic Literature Review on Fault Detection, Digital Twins, and Intelligent Asset Management by Luis Rojas, Álvaro Peña, José Garcia

Subjects: “…predictive maintenance…”
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Innovative Study on Volatility Prediction Model for New Energy Stock Indices by Yanguo Li, Chao Long

Subjects: “…Volatility prediction…”
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Intelligent Damage Prediction During Vehicle Collisions Based on Simulation Datasets by Sheng Liu, Conghao Liu, Xunan An, Xin Liu, Liang Hao

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Empirical research on the diffusion effect of ICT innovation diffusion and prediction in China by Wenyu HU, Wenju WANG

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Prediction and Monitoring Model of Concrete Dam Deformation Based on WOA-RFR by FENG Yu, WU Yunxing, GU Wenjing, PANG Qiong, GU Yanchang, CHEN Siyu

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Support of individual educational trajectories based on the concept of explainable artificial intelligence by I. G. Zakharova, M. S. Vorobeva, Yu. V. Boganyuk

“…The authors proposed a methodology for digital support of IET, corresponding to the principles of explainable artificial intelligence, i.e. machine learning models predict educational outcomes, and a special algorithm automatically generates personalised recommendations based on the results of the analysis of data on the educational process. …”
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Comparative Analysis of Machine Learning and Deep Learning Models for Lung Cancer Prediction Based on Symptomatic and Lifestyle Features by Bireswar Dutta

Subjects: “…lung cancer prediction…”
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Two-Stage Energy Storage Allocation Considering Voltage Management and Loss Reduction Requirements in Unbalanced Distribution Networks by Hu Cao, Lingling Ma, Guoying Liu, Zhijian Liu, Hang Dong

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Mechanism-learning prediction model for pitting depth of buried pipeline based on HMOGWO-RF by Fulin SONG, Hong ZHAO, Xingyuan MIAO

“…To ensure the safe operation of buried pipelines, accurately predicting the degree of corrosion is crucial. Methods This paper presents a prediction model for the pitting depth of buried pipelines, guided by the corrosion mechanism and combining a Random Forest (RF) algorithm with a Multi-Objective Optimization process. …”
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Sparse Array Mutual Coupling Reduction by C. Larmour, N. Buchanan, V. Fusco, M. Ali Babar Abbasi

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Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithms by Bruna Carbas, Pedro Sampaio, Sílvia Cruz Barros, Andreia Freitas, Ana Sanches Silva, Carla Brites

“…This study evaluates the potential of near-infrared (NIR) spectroscopy combined with chemometric algorithms to detect fumonisins in maize. For fumonisin B1 (FB1) and B2 (FB2) levels were developed predictive NIR models using partial least squares (PLS) and artificial neural networks (ANN). …”
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Optimized Application of CGA-SVM in Tight Reservoir Horizontal Well Production Prediction by Chao Wang, Ruogu Wang, Yuhan Lin, Jiafei Zhang, Xiaofei Xie, Zidan Zhao, Yunlin Xu

“…Limited by the number of parameters, the traditional linear fitting method has low computational efficiency and a large error, which brings difficulties to horizontal well production prediction. In this paper, chaotic genetic algorithm is used to optimize the traditional support vector machine, and the problems of slow convergence and local convergence are solved by chaotic genetic algorithm, and an improved support vector machine horizontal well production prediction method is established. …”
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Predictive Technology Assessment by Means of a Structure-Based Method of Machine Learning by Manja Mai-Ly PFAFF, Uwe FRIEß, Andreas OTTO, Matthias PUTZ

“…The starting point is an adaptive algorithm that performs a dynamic tolerance band formation based on different criteria, emphasizing on adaptive characteristic segmentation. …”
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Automatic Distribution of PRVs for Leakage Reduction by Ramon Pérez, Guillem Roca, Sergi Grau

“…The manual introduction of a PRV shows its effectiveness regarding leakage reduction. An algorithm for finding the high-pressure areas and their boundary pipes is presented. …”
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Predicting coastal variations in non-storm conditions with machine learning by Jabari Amir, Adjami Mehdi, Gharechelou Saeid

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Predicting social welfare in Madrid neighbourhoods using machine learning by Carlos Alberto Lastras Rodríguez

“…A comprehensive dataset representing various socioeconomic metrics of Madrid’s neighbourhoods is analysed utilising different linear regression models and the XGBoost machine learning algorithm. The findings indicate that demographic variables play a crucial role in shaping social welfare and inequality in Madrid's neighbourhoods, with the percentage of women, and the percentage of children under 14 years old and adults over 65 years old being the most important variables for predicting social welfare and inequality in the studied neighbourhoods. …”
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