COD Optimization Prediction Model Based on CAWOA-ELM in Water Ecological Environment by Lili Jiang, Liu Yang, Yang Huang, Yi Wu, Huixian Li, XiYan Shen, Meng Bi, Lin Hong, Yiting Yang, Zuping Ding, Wenjie Chen

“…In order to detect high error rate and poor convergence of the water ecological chemical oxygen demand (COD) prediction model, combining the limit learning machine (ELM) model and whale optimization algorithm, CAWOA is improved by the sin chaos search strategy, while the ELM optimizes the parameters of the algorithm to improve convergence speed, thus improving the generalization performance of the ELM. …”
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Better care for children with appendicitis: implementation of antibiotic stewardship optimizes postoperative therapy by Beltz, Sebastian, Fischer, Stephanie, Huenger, Frank, Vahdad, Reza, Kalhoff, Hermann, Leutner, Andreas

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Networked Sensor-Based Adaptive Traffic Signal Control for Dynamic Flow Optimization by Xinhai Wang, Wenhua Shao

“…This method integrates the Webster algorithm with a proportional–integral–derivative (PID) controller, whose parameters are optimized using a genetic algorithm, thereby facilitating scientifically informed traffic signal timing strategies for enhanced traffic regulation. …”
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Optimizing Masks and Random Screening Test Usage within K-12 Schools by Yiwei Zhang, Maria E. Mayorga, Julie S. Ivy, Julie L. Swann

“…Many studies discussed the effectiveness of various interventions, while few focused on optimizing such interventions. …”
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Evolutionary Search with Multiple Utopian Reference Points in Decomposition-Based Multiobjective Optimization by Wu Lin, Qiuzhen Lin, Zexuan Zhu, Jianqiang Li, Jianyong Chen, Zhong Ming

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K-Means Based Bee Colony Optimization for Clustering in Heterogeneous Sensor Network by Prince Modey, Gaddafi Abdul-Salaam, Emmanuel Freeman, Patrick Acheampong, William Leslie Brown-Acquaye, Israel Edem Agbehadji, Richard C. Millham

“…While the traditional bee colony optimization technique has been widely used as a clustering technique in WSN, it mostly suffers from energy efficiency and network performance. …”
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LEVELS OF PATIENTS EXPOSURE AND A POTENTIAL FOR OPTIMIZATION OF THE PET DIAGNOSTICS IN THE RUSSIAN FEDERATION by L. A. Chipiga, I. A. Zvonova, D. V. Ryzhkova, M. A. Menkov, М. B. Dolgushin

“…Low dose computed tomography protocols, justification of diagnostic and multiphase computed tomography protocols, application of tube current modulation system and modern reconstruction algorithms, education and training of the staff in the field of radiation protection should be used for optimization of radiation protection of patient.…”
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Hybrid Model for 6G Network Traffic Prediction and Wireless Resource Optimization by Mohammed Anis Oukebdane, A. F. M. Shahen Shah, Md Baharul Islam, John Ekoru, Milka Madahana

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Beamforming and resource optimization in UAV integrated sensing and communication network with edge computing by Bin LI, Sicong PENG, Zesong FEI

“…To address the dependence of traditional integrated sensing and communication network mode on ground infrastructure, the unmanned aerial vehicle (UAV) with edge computing server and radar transceiver was proposed to solve the problems of high-power consumption, signal blocking, and coverage blind spots in complex scenarios.Firstly, under the conditions of satisfying the user’s transmission power, radar estimation information rate and task offloading proportion limit, the system energy consumption was minimized by jointly optimizing UAV radar beamforming, computing resource allocation, task offloading, user transmission power, and UAV flight trajectory.Secondly, the non-convex optimization problem was reformulated as a Markov decision process, and the proximal policy optimization method based deep reinforcement learning was used to achieve the optimal solution.Simulation results show that the proposed algorithm has a faster training speed and can reduce the system energy consumption effectively while satisfying the sensing and computing delay requirements.…”
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Self-adaptive dragonfly based optimal thresholding for multilevel segmentation of digital images by Rakoth Kandan Sambandam, Sasikala Jayaraman

“…Dragonfly optimization (DFO) is a population based meta-heuristic optimization algorithm that simulates the static and dynamic swarming behaviors of dragonflies. …”
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Design approach for optimization of a piston ring profile considering mixed lubrication by Zhinan Zhang, Jun Liu, Youbai Xie

“…Abstract To reduce the friction of a piston ring while maintaining a large oil film load-carrying capacity, an approach comprising of the inverse method and the sequential quadratic programming algorithm was proposed. …”
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An optimization approach for blood supply chain management integrating drone delivery method by Mayuri K. N, Gowsalya M.

“…This paper aims to minimize the delivery lead time and make the fastest delivery of lifesaving blood products within a specified delivery range. We proposed an optimization model that uses mixed integer non-linear programming (MINLP) with Dijkstra’s algorithm. …”
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Large language models design sequence-defined macromolecules via evolutionary optimization by Wesley F. Reinhart, Antonia Statt

“…Abstract We demonstrate the ability of a large language model to perform evolutionary optimization for materials discovery. Anthropic’s Claude 3.5 model outperforms an active learning scheme with handcrafted surrogate models and an evolutionary algorithm in selecting monomer sequences to produce targeted morphologies in macromolecular self-assembly. …”
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Differential Evolution for Optimizing Model Parameters in Simulation of Direct Dimethyl Carbonate Synthesis by Outi Ruusunen, Riitta Keiski, Mika Ruusunen

“…The Differential Evolution (DE) algorithm was applied to optimize parameters of the model. …”
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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

“…Notably, as the number of channels increases, S-SE stabilizes while fairness continues to improve, approaching optimal levels in diverse system configurations. …”
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Multi-Objective Optimization of Gas Storage Compressor Units Based on NSGA-II by Lianbin Zhao, Lilin Fan, Jun Lu, Mingmin He, Su Qian, Qingsong Wei, Guijiu Wang, Haoze Bai, Hu Zhou, Yongshuai Liu, Cheng Chang

“…A multi-objective optimization model based on the NSGA-II algorithm is proposed to maximize gas injection volume while minimizing energy consumption. …”
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Optimizing Energy Forecasting Using ANN and RF Models for HVAC and Heating Predictions by Khaled M. Salem, Javier M. Rey-Hernández, A. O. Elgharib, Francisco J. Rey-Martínez

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Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

“…Specifically, we propose an optimization algorithm based on Differential Evolution (DE) that adjusts anchor scales and ratios while determining the most appropriate number of these parameters for each dataset based on the annotated data. …”
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Optimizing Variable Admittance Control for Remote Ultrasound Scanning Under Uncertain Environment by Songjie Xiao, Tengyue Wang, Yun Long, Liangjing Yang

“…Precise force control in remote robotic ultrasound systems is critical for optimizing image quality and ensuring patient safety. …”
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Optimal Design and Dynamic Performance Analysis of Vehicle Suspension Employing an Eccentric Inerter by Chengqun Qiu, Ang Chen, Yuqiu Xu, Yujie Shen

“…Then, by considering the overall performance such as the vehicle body acceleration, the suspension working space, and the dynamic tire load, the key parameters of the two suspensions are optimized by using the genetic algorithm. Simulation analysis results indicate that the series-connected vehicle ISD suspension is superior to the parallel-connected one, and all of the RMS values of the body acceleration, the suspension working space, and the dynamic tire load are decreased significantly by comparing to the conventional suspension, while the improvement of the parallel-connected vehicle ISD suspension is relatively poor. …”
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