Tackling the Optimal Phasor Measurement Unit Placement and Attack Detection Problems in Smart Grids by Incorporating Machine Learning by Ramzi Al-Sharawi, Abdelfatah Ali, Mostafa Shaaban, Nasser Qaddoumi, Mohamed S. Abdalzaher

“…Thus, this paper proposes a novel approach by formulating this issue as a tri-objective functions optimization problem. The proposed approach optimizes PMU allocation to maximize topological observability and minimize system cost while improving the FDIA detection performance using machine learning. …”
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Applications of Machine Learning Algorithms in Geriatrics by Adrian Stancu, Cosmina-Mihaela Rosca, Emilian Marian Iovanovici

“…The increase in the elderly population globally reflects a change in the population’s mindset regarding preventive health measures and necessitates a rethinking of healthcare strategies. The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, and treatment. …”
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A Comparative Analysis of Different Machine Learning Algorithms Developed with Hyperparameter Optimization in the Prediction of Student Academic Success by Bahar Demirtürk, Tuba Harunoğlu

“…In addition, the performances of all machine learning models were compared, using seventeen metric results for three cases, including results without hyperparameter optimization and determinations after hyperparameter optimization. …”
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Aero Engine Component Fault Diagnosis Using Multi-Hidden-Layer Extreme Learning Machine with Optimized Structure by Shan Pang, Xinyi Yang, Xiaofeng Zhang

“…A new aero gas turbine engine gas path component fault diagnosis method based on multi-hidden-layer extreme learning machine with optimized structure (OM-ELM) was proposed. …”
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Leveraging machine learning for prediction and optimization of texture properties of sustainable activated carbon derived from waste materials by Ahmed Farid Ibrahim, Mohamed Abdrabou Hussein

“…However, the traditional assessment methods are expensive and complex. This study employed machine learning (ML) models to predict AC’s properties and optimize its production process. …”
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Initialization of cutting tools and milling paths for 5-axis CNC flank milling of freeform surfaces by Pengbo Bo, Siyu Xue, Xiwen Xu, Caiming Zhang

Subjects: “…CNC machining…”
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Renewable Electricity Management Cloud System for Smart Communities Using Advanced Machine Learning by Yukta Mehta, Vincent Lo, Vijen Mehta, Kunal Agrawal, Charan Teja Madabathula, Eugene Chang, Jerry Gao

“…This paper proposes and develops a community-based model that manages and analyzes multiple buildings’ energy usage, allowing the model to perform both distributed and aggregated decision-making, achieving an accuracy of 98.2% using stacking results of models with reinforcement learning. …”
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Exploring statistical and machine learning methods for modeling probability distribution parameters in downtime length analysis: a paper manufacturing machine case study by Vladimir Koković, Kosta Pavlović, Andjela Mijanović, Slavko Kovačević, Ivan Mačužić, Vladimir Božović

“…This paper explores statistical and machine learning techniques for modeling downtime length probability distributions and correlation with machine vibration measurements. …”
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Optimizing machine learning methods for groundwater quality prediction: Case study in District Bagh, Azad Kashmir, Pakistan by Usman Basharat, Wenjing Zhang, Cuihong Han, Shoukat Husain Khan, Arshad Abbasi, Sehrish Mahroof, Shuxin Li

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Network-, Cost-, and Renewable-Aware Ant Colony Optimization for Energy-Efficient Virtual Machine Placement in Cloud Datacenters by Ali Mohammad Baydoun, Ahmed Sherif Zekri

“…This paper proposes NCRA-DP-ACO (Network-, Cost-, and Renewable-Aware Ant Colony Optimization with Dynamic Power Usage Effectiveness (PUE)), a bio-inspired metaheuristic that optimizes VM placement across geographically distributed datacenters. …”
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A Real-World Energy Management Dataset from a Smart Company Building for Optimization and Machine Learning by Jens Engel, Andrea Castellani, Patricia Wollstadt, Felix Lanfermann, Thomas Schmitt, Sebastian Schmitt, Lydia Fischer, Steffen Limmer, David Luttropp, Florian Jomrich, René Unger, Tobias Rodemann

“…The dataset enables the application of a wide range of methods in the domain of energy management, including optimization, modeling, and machine learning to optimize building operations and reduce costs and carbon emissions.…”
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Improvement strategies for heuristic algorithms based on machine learning and information concepts: a review of the seahorse optimization algorithm by Shixing Zheng

“…To overcome the mechanical limitations of traditional inertia weight optimization methods, this study draws inspiration from machine learning models and proposes an inertia weight optimization strategy based on the K-nearest neighbors (KNN) principle with dynamic adjustment properties. …”
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Multi-Objective Optimization of a Spoke Type Synchronous Machine With Ferrite Magnets Considering Torque Ripple and Demagnetization by Marcelo D. Silva, Sandra Eriksson

“…The study is developed using experimentally validated FEM models. Furthermore, the study shows that, for Spoke Type PMSM with ferrite PMs, the inclusion of demagnetization in the optimization process alters the optimal design by skewing the Pareto front toward low-performing solutions. …”
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Machinability Assessment and Multi-Objective Optimization of Graphene Nanoplatelets-Reinforced Aluminum Matrix Composite in Dry CNC Turning by Nikolaos A. Fountas, Dimitrios E. Manolakos, Nikolaos M. Vaxevanidis

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AquaFlowNet a machine learning based framework for real time wastewater flow management and optimization by P. Prabu, Ala Saleh Alluhaidan, Romana Aziz, Shakila Basheer

“…These limitations often lead to inefficiencies such as energy wastage, treatment delays, and overflow incidents, negatively impacting system performance and sustainability.AquaFlowNet leverages state-of-the-art machine learning algorithms to analyze real-time data from sensors, forecast flow variations, and optimize wastewater treatment processes. …”
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Prediction and optimization of WEDM parameters for machining of NiTi-shape memory alloy using ANFIS-PSO approach by Lokesh Kumar, Ashish Goyal, Vimal Kumar Pathak

“…Comparative analysis demonstrated that ANFIS modeling provided better results, with excellent significant improvements in surface morphology and chemical composition, as investigated via FESEM and EDS testing at the optimal settings of machined and unmachined Zn coated brass wire. …”
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Street View-Enabled Explainable Machine Learning for Spatial Optimization of Non-Motorized Transportation-Oriented Urban Design by Yichen Ruan, Xiaoyi Zhang, Shaohua Wang, Xiuxiu Chen, Qiuxiao Chen

“…These features are fused with multi-source geospatial data encompassing 23 built environment variables into an interpretable machine learning pipeline using SHAP-optimized random forest models. …”
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Electrical Equivalent Circuit Parameter Estimation of Commercial Induction Machines Using an Enhanced Grey Wolf Optimization Algorithm by Premkumar Manoharan, Sowmya Ravichandran, Jagarapu S. V. Siva Kumar, Mustafa Abdullah, Tan Ching Sin, Tengku Juhana Tengku Hashim

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Analysis of Vibration Characteristics of the Grading Belt in Wolfberry Sorting Machines by Yang Yu, Zhiwei Su, Junhao Zhang, Jinglong Li, Wu Qin

“…The vibration of the belt drive system in fresh wolfberry sorting machines significantly impacts the sorting efficiency of wolfberries. …”
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Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data by Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya, R. Manjunatha, Debasish Shit, M. Nirmala, Ajay Sharma, Sarbeswara Hota, Shirin Shomurotova, Fadhil Faez Sead, Hojjat Abbasi, Mohammad Mahtab Alam

Subjects: “…Choke flow modeling…”
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