Performance Analysis of Diabetes Detection Using Machine Learning Classifiers by Hung Huynh, Liu Hui, Ngoc Han Nguyen, Ruixuan Qiao

“…Despite performing well in almost all of the metrics, SGD’s low recall score shows that it is not the most optimal algorithm. Given that recall score is prioritized in the context of clinical diagnostics, Random Forest emerges as a strong candidate due to its balanced performance across key metrics.…”
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A Mixed Integer Linear Formulation and a Grouping League Championship Algorithm for a Multiperiod-Multitrip Order Picking System with Product Replenishment to Minimize Total Tardin... by Morteza Farhadi Sartangi, Ali Husseinzadeh Kashan, Hassan Haleh, Abolfazl Kazemi

“…A mixed integer linear programming formulation is proposed for this new problem. The model is optimally solved for small-size problems. For larger instances, grouping metaheuristic algorithms are proposed based on particle swarm optimization and the league championship algorithm that use group-based operators to generate reasonable batches of orders. …”
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Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks by Omar S. Aba Hussen, Shaiful J. Hashim, Nasri Sulaiman Member, S.A.R. Alhaddad, Bassam Y. Ribbfors, Masanobu Umeda, Keiichi Katamine

“…The main objectives are to reduce the number of unserved demands and operational costs. A simulation model was developed in MATLAB, utilizing the Non-dominated Sorting Genetic Algorithm (NSGA-II), a powerful multi-objective optimization technique that balances conflicting objectives to achieve the best trade-offs for operational efficiency. …”
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Enhancing Last-Mile Logistics: AI-Driven Fleet Optimization, Mixed Reality, and Large Language Model Assistants for Warehouse Operations by Saverio Ieva, Ivano Bilenchi, Filippo Gramegna, Agnese Pinto, Floriano Scioscia, Michele Ruta, Giuseppe Loseto

“…Due to the rapid expansion of e-commerce and urbanization, Last-Mile Delivery (LMD) faces increasing challenges related to cost, timeliness, and sustainability. Artificial intelligence (AI) techniques are widely used to optimize fleet management, while augmented and mixed reality (AR/MR) technologies are being adopted to enhance warehouse operations. …”
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RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

“…The graphs are processed using a graph neural network with DiffPool. To optimize feature integration, we incorporate an improved dung beetle optimization algorithm, which adaptively assigns fusion weights during inference. …”
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Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes by Kelly Joel Gurubel Tun, Elizabeth León-Becerril, Octavio García-Depraect

“…Predictive control uses the Newton-Raphson as the optimization algorithm and a multi-layer feedforward neural network for the state prediction. …”
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Forecast-Aided Converter-Based Control for Optimal Microgrid Operation in Industrial Energy Management System (EMS): A Case Study in Vietnam by Yeong-Nam Jeon, Jae-ha Ko

“…The forecasted load data is then used to optimize charge/discharge schedules for energy storage systems (ESS) using a Particle Swarm Optimization (PSO) algorithm. …”
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Targeted Interventional Therapies for the Management of Postamputation Pain: A Comprehensive Review by Dunja Savicevic, Jovana Grupkovic, Uros Dabetic, Dejan Aleksandric, Nikola Bogosavljevic, Uros Novakovic, Ljubica Spasic, Slavisa Zagorac

“…Nevertheless, further research is required to standardize clinical algorithms, optimize therapeutic decision-making and improve long-term outcomes and quality of life for individuals with PAP.…”
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Micro hole drilling and multi criteria optimization of soda lime glass via ultrasonic assisted rotary electrochemical discharge drilling by Sahil Grover, Viveksheel Rajput, Sanjay Kumar Mangal, Sarbjit Singh, Sandeep Singh, Shubham Sharma, Ehab El Sayed Massoud, Dražan Kozak, Jasmina Lozanovic

“…Machine learning-based algorithms are also used to predict the responses using Random Forest and Gradient Boost approaches. …”
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Improving total bone marrow and lymphoid irradiation: feasibility of intensity-modulated proton therapy (IMPT) and dosimetric comparison with helical tomotherapy (HT) by Dayananda Shamurailatpam Sharma, Arjunan Manikandan, Gaganpreet Singh, Sanjib Gayen, Sham Sundar, Aishwarya G, Rangasamy S, Mahammood Suhail, Rajesh S, Ganapathy Krishnan, Revathi Raj, Srinivas Chilukuri, Jose Easow, Rakesh Jalali

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Management of the business system of the enterprise by O. Grosheleva, M. Ivanova, O. Usatenko

“…An algorithm for determining the optimal share of sales costs in revenue is proposed. …”
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Multi-Robot exploration for coal mine rescue based on the extension of undirected graph by Linna ZHOU, Tihao WU, Xinli HUANG, Chunyu YANG, Xin ZHANG

“…Therefore, in response to the complex post-disaster downhole environment, a multi-robot autonomous exploration method based on the extended undirected graph is proposed, aiming at studying the collaborative search and rescue of a multi-robot autonomous exploration system to further improve rescue efficiency. …”
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Improvement of the technique applied to preserve species and varieties of <i>Fragaria</i> L. in the field genebank at Krymsk Experiment Breeding Station of VIR by V. N. Podorozhniy, N. A. Piyanina

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LGN-YOLO: A Leaf-Oriented Region-of-Interest Generation Method for Cotton Top Buds in Fields by Yufei Xie, Liping Chen

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Estimation of elbow flexion torque using equilibrium optimizer on feature selection of NMES MMG signals and hyperparameter tuning of random forest regression by Raphael Uwamahoro, Raphael Uwamahoro, Kenneth Sundaraj, Farah Shahnaz Feroz

“…The performance of the GLEO-coupled with the RFR model was compared with the standard Equilibrium Optimizer (EO) and other state-of-the-art algorithms in physical and physiological function estimation using biological signals.ResultsExperimental results showed that selected features and tuned hyperparameters demonstrated a significant improvement in root mean square error (RMSE), coefficient of determination (R2) and slope with values improving from 0.1330 to 0.1174, 0.7228 to 0.7853 and 0.6946 to 0.7414, respectively for the test dataset. …”
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Enhancing resilience of distribution system under extreme weather: Two-stage energy storage system configuration strategy based on robust optimization by Ye He, Hongyun Fu, Andrew Y. Wu, Hongbin Wu, Ming Ding

“…Finally, a two-stage robust optimization model for the ESS is established to improve DN resilience with the objective of minimizing the comprehensive economic cost of the ESS and the annual comprehensive weighted load loss, which is solved using the column-and-constraint generation algorithm (C&CG). …”
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Combining miRNA concentrations and optimized machine-learning techniques: An effort for the tomato storage quality assessment in the agriculture 4.0 framework by Seyed Mohammad Samadi, Keyvan Asefpour Vakilian, Seyed Mohamad Javidan

“…However, the RF, with hyperparameters optimized by the genetic algorithm, was able to improve the R2 values of the prediction of storage temperature and period to 0.96 and 0.89. …”
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Enhanced recurrent attention-deep Q learning with optimal node constrains and effective penalty based model for data transmission scheduling on wireless sensor networks by D.R. Anita Sofia Liz, Yesubai Rubavathi C

“…Additionally, the algorithm’s efficiency contributes to cost savings and resource conservation, making it a socially responsible choice for managing wireless sensor networks.…”
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A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…Traditional energy management methods, based on static models or heuristic algorithms, often fail to handle real-time grid dynamics, leading to suboptimal energy distribution, high operational costs, and significant energy wastage. …”
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A lithium-ion batteries SOH estimation method based on extracting new features during the constant voltage charging stage and improving BPNN. by Yanhua Xian, Mingyang Li, Jiayin Huang

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