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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Pre-university students’ perception on algorithmic biases of artificial intelligence by Elba Gutiérrez-Santiuste, Lourdes López-Pérez, Fátima Poza-Vilches, Daniel Molina-Cabrera, Rosana Montes-Soldado and Luis Alcalá

“…This research focuses on pre-university students’ perceptions of algorithmic biases in artificial intelligence. Six types of biases (generational, gender, functional diversity, ethnicity, geographical origin and economic reasons) are examined on the basis of four variables (age, sex, educational level and academic year) of young people. …”
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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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Development of the predictive model for I stage breast cancer by A. Kh. Ismagilov, A. S. Vanesyan, D. R. Khuzina

“…Using a forward stepwise selection (binary regression), the most important prognostic factors were selected, on the basis of which the predictive model “Risk Assessment Algorithm for Recurrence of Breast Carcinoma” was constructed.Results. …”
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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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Feature engineering through two-level genetic algorithm by Aditi Gulati, Armin Felahatpisheh, Camilo E. Valderrama

“…Deep learning models are widely used for their high predictive performance, but often lack interpretability. …”
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Provident garbage collection algorithm for SSD storage system by Xuezhen TU, Zhenjiang Huang, Zhengguang CHEN

“…A predictive based proactive garbage collection algorithm was proposed.Firstly,the data was separated according to different heat factors,then the upper and lower predictions were performed on the number of different types of page allocation requests (PAR) that would be reached in the future.While satisfying the page allocation request lower prediction,the PAR upper prediction requirement was maximally satisfied,the WA problem was optimized,and invalid effective data migration was reduced,thereby maximizing the garbage collection utility.A mathematical model was defined for this problem,and an algorithm for obtaining the approximate optimal solution was given.The applicable scenario of the model was analyzed.The practical results show that the algorithm can obtain the maximum benefit and can significantly improve the performance of SSD and reduce the cost.…”
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Application of a deep learning algorithm for the diagnosis of HCC by Philip Leung Ho Yu, Keith Wan-Hang Chiu, Jianliang Lu, Gilbert C.S. Lui, Jian Zhou, Ho-Ming Cheng, Xianhua Mao, Juan Wu, Xin-Ping Shen, King Ming Kwok, Wai Kuen Kan, Y.C. Ho, Hung Tat Chan, Peng Xiao, Lung-Yi Mak, Vivien W.M. Tsui, Cynthia Hui, Pui Mei Lam, Zijie Deng, Jiaqi Guo, Li Ni, Jinhua Huang, Sarah Yu, Chengzhi Peng, Wai Keung Li, Man-Fung Yuen, Wai-Kay Seto

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A Novel Long Short-Term Memory Seq2Seq Model with Chaos-Based Optimization and Attention Mechanism for Enhanced Dam Deformation Prediction by Lei Wang, Jiajun Wang, Dawei Tong, Xiaoling Wang

Subjects: “…dam deformation prediction…”
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