Optimization of external container delivery and pickup scheduling based on appointment mechanism. by Pengfei Huang, Hao Wang, Fangjiao Tan, Yuyue Jiang, Jinfen Cai

“…Through case studies, we have demonstrated the superior performance of this algorithm in addressing relevant problems. The results show that, in terms of truck operational costs, the improved algorithm reduces costs by 10.96% and 3.02% compared to traditional Ant Colony Optimization and Variable Neighborhood Search algorithms, respectively, and by 4.89% compared to manual scheduling. …”
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Adaptive Q-Learning Grey Wolf Optimizer for UAV Path Planning by Golam Moktader Nayeem, Mingyu Fan, Golam Moktader Daiyan

“…In path planning simulation, QGWO lowers the path cost by 27.4%, improves the convergence speed by 19.06%, and reduces the area under the curve (AUC) by 23.8% over standard GWO, achieving optimal trajectory. …”
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A Novel Two-Stage Learning-Based Phase Unwrapping Algorithm via Multimodel Fusion by Chao Yan, Tao Li, Yandong Gao, Shijin Li, Xiang Zhang, Xuefei Zhang, Di Zhang, Huiqin Liu

“…To solve this problem, this paper combines a deep neural network model with the traditional PhU model and proposes a novel two-stage learning-based phase unwrapping (TLPU) algorithm via multimodel fusion. The major advantages of TLPU are as follows: 1) A high-resolution U-Net (HRU-Net) model trained on a dataset constructed according to InSAR interferometric geometry is utilized for the PhU for the first time, which effectively improves the performance of the DLPU. 2) TLPU utilizes the traditional PhU method to optimize the results of DLPU, addressing the issue of weak generalization ability of a single DLPU, while improving accuracy in areas with large-gradient changes. …”
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Development and Comparison of Interrupt-Based and Analog-to-Digital Converter Algorithms for Seed Counting in Precision Planters by A. Ghaffarnezhad, H. Navid, H. Karimi

“…Both developed circuits featured the deployment of the STM32F103C8T6 microcontroller, renowned for its robust capabilities and cost efficiency.In the interrupt-based algorithm's development, the microcontroller's external interrupt was used, selecting its sensitivity to detect both rising and falling edges. …”
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Multi-objective Optimization Design of Component Cooling System in HPR1000 by ZHAO Weiguang1, 2, YU Pei1, 3, ZENG Xiaobo1, 2, FAN Guangming1, 2, YAN Changqi1, 2

“…To manage this complexity, a novel optimization algorithm was implemented to perform multi-objective optimization. …”
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Assessment of Urban Water Supply System Based on Query Optimization Strategy by Shibao Lu, Yizi Shang, Wei Li, Zhimin Wang

“…As a complicated water treatment system project, an urban water supply plays a significant role in enhancing ecological civilization construction, promoting social-economic sustainable development, and improving the living environment of humans. This paper has the goal of improving water treatment efficiency and reducing water treatment cost based on comparative studies by applying two types of distributed database query optimization methods, including the system for a distributed database (SDD-1) and all reduction algorithms. …”
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Reliability Optimization Model of Stop-Skipping Bus Operation with Capacity Constraints by Zhenhua Mou, Hu Zhang, Shidong Liang

“…Finally, a numerical example based on a bus route in Changchun city is carried out to test the reliability optimization model. Results showed that the reliability optimization strategy can improve the stability of stop service and then save cost of passengers’ travel time.…”
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Detection of capsaicin content by near-infrared spectroscopy combined with optimal wavelengths by LÜ Xiaohan, JIANG Jinlin, YANG Jing, CHEN Jianying, CEN Haiyan, FU Hongfei, ZHOU Yifei

“…In addition, compared with the full spectra of 200 wavelengths, the number of the optimal wavelengths selected by CARS was reduced by 96%, which indicated that optimal wavelengths can be used to simplify the models and improve the operation efficiency. …”
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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…To enable efficient detection, this study proposes a rockfall detection system based on embedded technology and an improved Yolov8 algorithm, termed Yolov8-GCB. The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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Investigating the Performance of Open-Vocabulary Classification Algorithms for Pathway and Surface Material Detection in Urban Environments by Kauê de Moraes Vestena, Silvana Phillipi Camboim, Maria Antonia Brovelli, Daniel Rodrigues dos Santos

“…The second experiment evaluates standardized pavement classification using the Deep Pavements dataset and a fine-tuned CLIP algorithm optimized for detecting OSM-compliant pavement categories. …”
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Cost-effectiveness of FIT and a FIT-based model to optimise symptomatic diagnosis of colorectal cancer: health economic modelling for the COLOFIT project by Linda Sharp, Sarah Bailey, Colin Rees, Willie Hamilton, Dawn Craig, Joe West, David Humes, Gary Abel, James Turvill, Brian Nicholson, Chloe Thomas, Jim Chilcott, Colin Crooks, Olena Mandrik, John Whelpton

“…Cost-effectiveness improves as risk thresholds rise. …”
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Reliability-Based Optimization of Impeller Structure Using Exponential Function Approximation by Haiwei Lin, Yiqun Ren, Hong Bao, Feng Zhang, Feifei Zhao, Xiya Bao

“…Then, the obtained explicit exponential function approximation is used to decouple the reliability-based optimization problem and transform it into an equivalent deterministic optimization problem, where a general optimization algorithm can be adopted to solve steadily with a neglectable computational cost. …”
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Optimizing concrete strength: How nanomaterials and AI redefine mix design by Dan Huang, Guangshuai Han, Ziyang Tang

“…XGB was identified as the most effective ML algorithm for predicting compressive strength among others in this study (R2=0.974). …”
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Sensor placement optimization for critical-grid coverage problem of indoor positioning by Hui Wu, Zhe Liu, Jin Hu, Weifeng Yin

“…Then, NSGA-II algorithm was used to solve the optimizing model of sensor placement. …”
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Resource allocation strategy based on optimal matching auction in the enterprise network by Xin CONG, Lingling ZI, Xueli SHEN

“…To address the issue that the owners of computer are selfish in the enterprise networks,which caused the low available number of resource nodes and low efficiency of resource allocation,an optimized matching resource allocation strategy OMRA was proposed and its core was the auction mechanism.Selfishness was restrained and the number of available resources was increased by OMRA,so as the operating efficiency of the whole auction market was improved.First,the initial prices were determined by normalizing the costs of different type of resources on the beginning of auction.Secondly,an optimal matching auction algorithm was designed to maximize the interests of the auction markets.Then,service perfecting algorithm was performed such that the sellers could get more services at the current transaction value,thus ensuring the benefits of resource providers.At last,a request price updating algorithm was adopted to assurance that both sellers and buyers could get priorities in the next auction processing.Compared with the cloud resource allocating algorithm via fitness-enabled auction (CRAA/FA),the experiment results indicate that the efficiency of resource allocation improves by 10% and the benefits of market increase by 11.4%.…”
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Optimal PMU Placement Considering with HVDC Links and Their Voltage Stability Requirements by Milad Dalali, Hosein Kazemi Karegar

“…However, it is not practical in real networks due to the relatively expensive cost of PMUs and other technical limitations. Optimal PMU Placement (OPP) is an optimization problem providing full observability of the power network with minimum number of PMUs. …”
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Forecasting Wind Farm Production in the Short, Medium, and Long Terms Using Various Machine Learning Algorithms by Gökhan Ekinci, Harun Kemal Ozturk

“…These findings provide practical insights for optimizing wind energy forecasting models, which can improve energy trading strategies, enhance grid stability, and support informed decision making in renewable energy investments. …”
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Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach by Tomás de Jesús Mateo Sanguino, Jhon Carlos Mendoza Betancourt

“…The developed algorithm allows automating the design process, traditionally handmade by network technicians, in order to save time and cost by improving the WLAN arrangement. …”
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Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis by XinPei Liu, SanXi Ai, RuiMing Yu, ChaoJi Zhang, Qi Miao

“…Machine learning models enable early prediction of post-surgical AKI, facilitating targeted perioperative optimization and risk stratification in this distinct patient group.…”
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Daily runoff forecasting using novel optimized machine learning methods by Peiman Parisouj, Changhyun Jun, Sayed M. Bateni, Essam Heggy, Shahab S. Band

“…In the Carson River, the GB model achieves the highest forecasting accuracy, which is significantly improved by ARO, resulting in a 24.8 % reduction in root mean square error (RMSE). …”
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