Enhancing Residential Electricity Consumption Forecasting with Meta-Heuristic Algorithms by Milad Mohebbi, Behnam Sobhani

“…This study explores optimizing Artificial Neural Network (ANN) parameters using meta-heuristic algorithms instead of traditional gradient-based methods to predict residential electricity consumption across different seasons. …”
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Supercontinuum Generation in Suspended Core Fibers Based on Intelligent Algorithms by Meiqian Jing, Tigang Ning

“…A high-nonlinearity SCF structure (γ ≈ 6–7 W⁻¹·m⁻¹) was first designed, and a neural network model was developed to accurately predict effective modal refractive indices and mode-field areas (RMSE < 1%). …”
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Financial engineering and the digital economy: The implementations of machine learning algorithms by Pingping Fu, Honghao Yang, Wenhao Qian, ELsiddig Idriss Mohamed, Wafa Ali J. Almohri, Huda M. Alshanbari

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Weed detection on embedded systems using computer vision algorithms by D. Shadrin, S. Illarionova, R. Kasatov, M. Akimenkova, G. Rudensky, E. Erhan

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Machine learning approach for revealing the nickel grade and recovery optimization in reduction process of laterite ores by Vuri Ayu Setyowati, Fakhreza Abdul

“…Data sets were collected from published studies that feature nickel ore grade (Ni and Fe content) and reduction process (temperature, additives, reductant, etc.), while prediction models for Ni grade and recovery were formed from four types of regression algorithms. …”
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Predictive analytics in customer behavior: Anticipating trends and preferences by Hamed GhorbanTanhaei, Payam Boozary, Sogand Sheykhan, Maryam Rabiee, Farzam Rahmani, Iman Hosseini

“…In the current work, various machine learning algorithms such as Decision Tree (DT), Random Forest (RT), Logistic Regression (LR), Support Vector Machines (SVM), and gradient boosting are used to predict customer behavior. …”
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Microservice Deployment Based on Multiple Controllers for User Response Time Reduction in Edge-Native Computing by Zhaoyang Wang, Jinqi Zhu, Jia Guo, Yang Liu

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Low-carbon economic dispatch based on improved ISODATA scenario reduction for wind power in IES by Yuangen HUANG, Xingyu LIU, Tianran LI, Zhenya JI, Wei XU

“…A low-carbon, economic dispatch method for IES using an enhanced wind power scenario reduction algorithm is introduced in this paper. It employs an improved iterative self-organizing data analysis technique algorithm (ISODATA) for clustering historical wind power scenarios, addressing the limitations of traditional clustering algorithms in determining cluster centers and analyzing inherent data features. …”
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Optimizing circular antenna arrays with artificial rabbits optimization for beam control and side lobe reduction by Sunil Kumar, Harbinder Singh, Avtar Singh

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Merging Multiple System Perspectives: The Key to Effective Inland Shipping Emission-Reduction Policy Design by Solange van der Werff, Fedor Baart, Mark van Koningsveld

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A Model Predictive Control to Improve Grid Resilience by Joseph Young, David G. Wilson, Wayne Weaver, Rush D. Robinett

“…The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. …”
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Predictive modeling for rework detection in sustainable building projects by AbdulLateef Olanrewaju, Kafayat Shobowale

“…The systemic solution to prevent rework in sustainable buildings is to predict the occurrence of rework. This research pursues two key objectives: first, to prioritise the primary predictors of rework in sustainable buildings; second, to evaluate the most suitable machine learning algorithms for accurately modelling rework occurrences by classifying the extent of rework in the sustainable buildings. …”
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Prediction Analysis of Pre-Camber for Continuous Girder Bridge Cantilever Casting Construction Based on DBO-CNN-BiLSTM-Attention Neural Network by Jinyang Zhang, Haiqing Liu, Xiangen Gong, Ming Lei, Zimu Chen

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Model Predictive Control Used in Passenger Vehicles: An Overview by Meaghan Charest-Finn, Shabnam Pejhan

“…The following article presents a high-level overview of how Model Predictive Control (MPC) is leveraged in passenger vehicles and their subsystems for improved performance. …”
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Informing Disaster Recovery Through Predictive Relocation Modeling by Chao He, Da Hu

“…This study explores the use of machine learning algorithms to improve the prediction of household relocation in the aftermath of disasters. …”
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Machine learning-driven condition monitoring for predictive maintenance by Mahliyo Aliyeva

“…ML algorithms, including Artificial Neural Networks and Random Forest Regression, enable the proactive forecasting of impending failures by constructing data-centric thermal models tailored for power electronics modules, thus averting catastrophic malfunctions such as air outlet blockages. …”
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Evaluating the Predictive Power of Software Metrics for Fault Localization by Issar Arab, Kenneth Magel, Mohammed Akour

“…We fitted thousands of models and benchmarked different algorithms—including deep learning, Random Forest, XGBoost, and LightGBM—to choose the best-performing model. …”
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Predictive analysis of doubly Type-Ⅱ censored models by Young Eun Jeon, Yongku Kim, Jung-In Seo

“…Second, it addresses prediction problems in a closed-form manner, ensuring computational efficiency. …”
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Data-driven predictive models for sustainable smart buildings by Prabhu Rajaram, Gnana Swathika O․V․

“…It highlights the critical role of energy efficiency and the importance of lowering carbon footprints through the implementation of advanced algorithms, including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Random Forest, XGBOOST, AdaBoost, and Naive Bayes classifiers. …”
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Algorithm for optimization of cold‑rolled pipe rolling routes by S. V. Pilipenko

“…Among the latter, the maximum possible reduction in the cross‑sectional area, the required reduction in the cross‑sectional area in the last pass, the requirement for the nature of the distribution of the reduction value in the cross‑sectional area, in the wall thickness and in the pipe diameter from pass to pass and other parameters are highlighted. …”
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