Solving 0-1 Knapsack and Bin Packing Problem Using Logical Social Group Optimization by Rhiddhi Prasad Das, Junali Jasmine Jena, Suresh Chandra Satapathy, Naeem M. S. Hannoon

“…This prominent research gap has been addressed in this paper by introducing Logical Social Group Optimization (LSGO), a logic-based binarized variant of Social Group Optimization (SGO) that leverages Boolean logic for improved efficiency. …”
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Privacy-preserving detection and classification of diabetic retinopathy using federated learning with FedDEO optimization by Dasari Bhulakshmi, Dharmendra Singh Rajput

“…The experiments show that FedDEO works effectively for the MESSIDOR dataset to achieve a high classification accuracy, specificity, recall, and F1-Measure of 96.98%, 98.12%, 97.12%, and 98.00% while preserving privacy. The results demonstrate that implementing these algorithms in an FL environment significantly improves privacy and performance compared to other approaches. …”
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DGCA3QM: DESIGN OF A DUAL GENETIC ALGORITHM BASED AUTOREGRESSION MODEL FOR CORRELATIVE PREDICTION OF AIR QUALITY METRICS by Harna M. Bodele, G. M. Asutkar, Kiran G. Asutkar

“…Due to incorporation of dual bioinspired optimizers with autoregressive correlation, the model is able to improve prediction accuracy by 8.5%, precision by 4.9%, recall by 1.5%, while reducing computational delay by 3.4% when compared with standard air quality analysis models. …”
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Flexibility Resource Planning and Stability Optimization Methods for Power Systems with High Penetration of Renewable Energy by Haiteng Han, Xiangchen Jiang, Yang Cao, Xuanyao Luo, Sheng Liu, Bei Yang

“…Finally, a hybrid SA-PSO algorithm combined with conic programming is employed to enhance computational efficiency while ensuring high solution quality for practical system scales. …”
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Optimal Autonomous Control for Distribution Transformer Area With High Photovoltaic Penetration Based on CSBO-LSTM by Yukai Wei, Chun He, Zhuo Chen, Yinyuan Guo, Zongyuan Li

“…Firstly, the improved CSBO is used to solve the multi-objective optimization problem, accurately formulate the PV reactive power regulation and ESS charging/discharging strategies, and generate the optimal operation dataset of the transformer area through multi-scenario simulation. …”
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Semantic aware intelligent optimization for IRS/UAV-enabled MEC in wideband cognitive radio networks by Wei Zheng, Pengshan Ren, Qing Li

“…Particularly, the proposed optimization framework jointly optimizes UAV trajectories, subcarrier allocation, IRS reflection coefficients, task offloading ratios, task priorities and contextual relevance to maximize semantic utility and system energy efficiency while dynamically ensuring task demands. …”
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Fine-Grained Classification of Pressure Ulcers and Incontinence-Associated Dermatitis Using Multimodal Deep Learning: Algorithm Development and Validation Study by Alexander Brehmer, Constantin Seibold, Jan Egger, Khalid Majjouti, Michaela Tapp-Herrenbrück, Hannah Pinnekamp, Vanessa Priester, Michael Aleithe, Uli Fischer, Bernadette Hosters, Jens Kleesiek

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Synergizing NOMA and energy harvesting in full duplex mobile edge computing for optimized energy efficiency by Mirza Baber Baig, Taoshen Li, Muhammad Zain Yousaf, Mohit Bajaj, Arvind R. Singh, Milkias Berhanu Tuka

“…Full-duplex base stations simultaneously manage task offloading and energy transmission, improving resource utilization. A Block Coordinate Descent (BCD)-based algorithm addresses the non-convex optimization challenge, offering an optimal solution. …”
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Scheduling Optimization of Electric Rubber-Tired Vehicles in Underground Coal Mines Based on Constraint Programming by Maoquan Wan, Hao Li, Hao Wang, Jie Hou

“…This study presents a Constraint Programming (CP)-based optimization framework that integrates Virtual Charging Station Mapping (VCSM) and sensor fusion positioning to decouple spatiotemporal charging conflicts and applies a dynamic topology adjustment algorithm to enhance computational efficiency. …”
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Optimal Scheduling of Biomass-Hybrid Microgrids with Energy Storage: An LSTM-PMOEVO Framework for Uncertain Environments by Zichong Wang, Yingying Zheng

“…Finally, a public dataset was utilized for the experiments to verify the performance of the proposed algorithm. Comparisons and discussions show that the proposed optimization strategies significantly improve the performance of PMOEVO, demonstrating marked advantages over six classical algorithms. …”
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Electromagnetic Analysis and Multi-Objective Design Optimization of a WFSM with Hybrid GOES-NOES Core by Kyeong-Tae Yu, Hwi-Rang Ban, Seong-Won Kim, Jun-Beom Park, Jang-Young Choi, Kyung-Hun Shin

“…Subsequently, a multi-objective optimization was conducted using Latin Hypercube Sampling, meta-modeling, and a genetic algorithm to maximize power density and efficiency while minimizing torque ripple. …”
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Comprehensive Evaluation Method of Teaching Effect Based on Particle Swarm Optimization Neural Network Model by Heng Cao, Qianhui Gao

“…This paper studies the optimization algorithm and optimization system, it not only makes the algorithm involve basic mathematical operations, and the computer support required for the data processing process is not high, but it also improves the evaluation of the degree of optimization. …”
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Optimized Software Implementation of Keccak, Kyber, and Dilithium on RV{32,64}IM{B}{V} by Jipeng Zhang, Yuxing Yan, Junhao Huang, Çetin Kaya Koç

“…Additionally, we improve the signed Plantard multiplication algorithm proposed by Akoi et al. …”
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A Novel NSGA-III-GKM++ Framework for Multi-Objective Cloud Resource Brokerage Optimization by Ahmed Yosreddin Samti, Ines Ben Jaafar, Issam Nouaouri, Patrick Hirsch

“…This paper presents NSGA-III-GKM++, an advanced multi-objective optimization model that integrates the NSGA-III evolutionary algorithm with an enhanced K-means++ clustering technique to improve the convergence speed, solution diversity, and computational efficiency. …”
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Research on Prediction and Optimization of Airport Express Passenger Flow Based on Fusion Intelligence Network Model by Jin He, Yinzhen Li, Yuhong Chao

“…The purpose of this paper is to optimize the accuracy of airport express passenger flow prediction so as to meet the need for the optimal allocation of traffic resources against the background of accelerated urbanization and the rapid development of airport express services. …”
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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…This paper presents an enhanced hybrid particle swarm optimization (EHPSO) algorithm that incorporates a spatial position encoding (SPE) strategy to optimize coverage while dynamically adjusting the number of sensors deployed in WSNs. …”
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A cluster-optimized regulation method for distribution networks considering distributed photovoltaic heterogeneous characteristics by Junhao Li, Xin Wang, Qi Guo, Chunzhi Yang, Yizhe Chen, Ruifeng Zhao, Ming Li

“…To address these challenges, a cluster-optimized regulation method is proposed, leveraging DPV heterogeneity to enable coordinated regulation while reducing directly-managed devices through DN clustering. …”
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Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment by Jing Zhang, Jingjing Liu, Zhong Wan

“…For this complicated polymorphic uncertain optimization model, a unified compromising approach is proposed to hedge the uncertainty of this model such that some powerful optimization algorithms can be applied to make an optimal recycling plan. …”
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Optimized dual NURBS curve interpolation for high-accuracy five-axis CNC path planning by Yi Xu, Mohd Hairi Mohd Zaman, Feng Zhou

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Intelligent algorithm-based model for predicting mass transfer performance in CO2 absorption within a rotating packed bed by Wei Zhang, Hao Chen, Ke Huang, Xing Shu, Cheng Fu, Bin Huang

“…Using dimensional analysis, key factors are transformed into dimensionless numbers, which are then input into models integrating least squares support vector machine (LSSVM) with genetic algorithm (GA), particle swarm optimization (PSO), and a hybrid GA-PSO (HGAPSO). …”
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