Optimizing Fairness and Spectral Efficiency With Shapley-Based User Prioritization in Semantic Communication by Moirangthem Tiken Singh, Adnan Arif, Rabinder Kumar Prasad, Bikramjit Choudhury, Chandan Kalita, Sikdar Md. S. Askari

“…The Shapley-based approach outperforms established methods, including the Hungarian algorithm, reinforcement learning algorithms like Deep Q-Network (DQN) and Proximal Policy Optimization (PPO), as well as conventional 4G and 5G resource allocation strategies. …”
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Star Recognition Based on Path Optimization in Star Sensor with Multiple Fields of View by Di Jiang, Ke Zhang, Olivier Debeir

“…Star sensors make use of astronomical information in stars to determine attitude for spacecrafts by star image recognition. For low-cost star sensors with small field of view, fusion of observed images from multiple fields of view is performed and a novel recognition algorithm based on path optimization by randomly distributed ant colony is proposed. …”
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Improved Correlation of Oil Recovery Factor for Water Driven Reservoirs in the Niger Delta by Ayodele Daniel, Faisal Olasubomi Olanipekun, Sunday Oloruntoba Isehunwa

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UAV-Based Pseudolite Navigation System Architecture Design and the Flight Path Optimization by Ruocheng Guo, Hong Yuan, Yang Zhang, Xiao Chen, Guanbing Zhang

“…The research results show that the flight path strongly guarantees navigation service performance with constraints on the operating cost. The ARMNSGA-III proposed in this paper can provide a 44.01% algorithm timeliness improvement compared to the NSGA-III in the flight path optimization, supporting rapid establishment and continuous service of the UAV-PNS in emergency scenarios.…”
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Integrating Machine Learning and Multi-Objective Optimization in Biofuel Systems: A Review by Ivan P. Malashin, Dmitry A. Martysyuk, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…The optimization of biofuel production involves balancing multiple conflicting objectives such as yield maximization, cost minimization, and environmental impact reduction. …”
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A Comparative Study of EAG and PBIL on Large-Scale Global Optimization Problems by Imtiaz Hussain Khan

“…Evolutionary Algorithm with Guided Mutation (EAG) combines global statistical information and location information to sample offspring, aiming that this hybridization improves the search and optimization process. …”
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APG mergence and topological potential optimization based heuristic user association strategy by Zhirui HU, Meihua BI, Fangmin XU, Meilin HE, Changliang ZHENG

“…Methods:The network scalable degree was designed as a measure of scalability,and then a user association strategy to improve network scalable degree was studied by using optimization theory. 1) For modelling the optimization problem, firstly, the network coupling degree, representing the degree of association among nodes, was constructed to establish the mathematical relationship between the network scalable degree and AP group (APG).Thus,the problem of improving the network scalable degree was modeled as the problem of minimizing the network coupling degree.Then,a multi-objective optimization problem of minimum network coupling degree and maximum user rate was established to find the balance between network scalable degree and network service quality. 2) For solving the optimization problem,to avoid the high computational complexity,a heuristic user association strategy based on APG mergence and topological potential optimization was proposed.With the proposed algorithm,the number of APG could be reduced by APG mergence,and the number of APG that AP belongs to could be reduced by AP exiting APG. …”
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Logistics Distribution Path Optimization Considering Carbon Emissions and Multifuel-Type Vehicles by Chuanxiang Ren, Li Lu, Juan Teng, Changchang Yin, Juntao Li, Haowei Ji, Xiaoqi Wang, Fangfang Fu

“…An improved genetic algorithm (IGA) is designed to solve the VRP-CEMF. …”
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Multiobjective Collaborative Optimization Method for the Urban Rail Multirouting Train Operation Plan by Lianbo Deng, Qi Peng, Li Cai, Junhao Zeng, Nava Raj Bhatt

“…A multiobjective genetic-based algorithm is designed to simultaneously optimize the TOP and the two-way train stopping time in each period. …”
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Optimizing Robotic Arm Learning: Curiosity-Driven Deep Deterministic Policy Gradient by Liu Jiarun

“…However, collecting the large- scale real-world data is costly and impractical, making simulation environments essential for optimization. …”
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Optimization of Resonant Arrays for Dynamic Wireless Power Transfer Using Adaptive Termination by Joao Dinis, Jose Alberto, Antonio J. Marques Cardoso

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Predicting compressive strength of concrete at elevated temperatures and optimizing its mixture proportions by Jinjun Xu, Han Wang, Wenjun Wu, Lang Lin, Yong Yu

“…The Cuckoo search algorithm was then employed to optimize mix designs, balancing high-temperature strength, cost and sustainability. …”
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Application of inertial navigation high precision positioning system based on SVM optimization by Ruiqun Han

“…Experiments indicated that the sum of squared errors for traditional algorithms estimating pedestrian trajectories was 0.92, whereas the optimized algorithms produced an improved sum of squared errors of 0.26. …”
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Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approaches by Cvetkovski Goga, Petkovska Lidija

“…In this case, optimising the efficiency of the motor, reducing cogging torque, and minimising the total weight of active materials are defined as possible objective functions. Genetic algorithms are nature based algorithms that are commonly used in engineering to find optimal solutions to complex problems, including those with multiple objectives. …”
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Decentralized Multi-Robot Navigation Based on Deep Reinforcement Learning and Trajectory Optimization by Yifei Bi, Jianing Luo, Jiwei Zhu, Junxiu Liu, Wei Li

“…Additionally, it introduces safety constraints through an artificial potential field (APF) to optimize these trajectories. Additionally, a constrained nonlinear optimization method further refines the APF-adjusted paths, resulting in the development of the GNN-RL-APF-Lagrangian algorithm. …”
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Mining Spatiotemporal Mobility Patterns Using Improved Deep Time Series Clustering by Ziyi Zhang, Diya Li, Zhe Zhang, Nick Duffield

“…Mining spatiotemporal mobility patterns is crucial for optimizing urban planning, enhancing transportation systems, and improving public safety by providing useful insights into human movement and behavior over space and time. …”
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Improving Efficiency of Rolling Mill Stand Electric Drives Through Load Alignment by Stanislav S. Voronin, Andrey A. Radionov, Alexander S. Karandaev, Roman A. Lisovsky, Boris M. Loginov, Mark A. Zinchenko, Vadim R. Khramshin, Ivan N. Erdakov

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Bayesian optimization of hybrid quantum LSTM in a mixed model for precipitation forecasting by Yumin Dong, Huanxin Ding

“…The hyperparameters of the model are optimized using the Bayesian optimization algorithm to obtain the best performance. …”
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Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration by Gudi V. Chandra Sekhar, Chekol Alemu

“…XGBoost achieved optimal performance with highest $$\text {AUC}$$ (0.956, 95% $$\text {CI}$$ : 0.952–0.961) and competitive clinical cost (5,496), representing 2.8% improvement over Random Forest. …”
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Capacity planning for wind, solar, thermal and energy storage in power generation systems considering coupled electricity‐carbon markets by Jiajia Huan, Yuling He, Kai Sun, Hongchang Lu, Haipeng Wang, Xuewei Wu

“…The model employs a bi‐level optimization method based on the Improved Coati Optimization Algorithm (ICOA) to optimize the system's capacity planning. …”
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