Comprehensive benefits evaluation of low impact development using scenario analysis and fuzzy decision approach by Ting Ni, Xiaohong Zhang, Peng Leng, Mark Pelling, Jiuping Xu

“…The framework’s novelty lies in the integration of the hesitant fuzzy weighted average algorithm to handle subjective uncertainties in expert judgment and the incorporation of multi-return period scenarios to enhance the robustness of the evaluation. …”
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Research on power system transformation based on edge node technology under the background of carbon neutrality by LI Jin, GAO Hongliang, LIU Kemeng, XIE Hu

“…In each island, the improved particle swarm optimization algorithm is used to reasonably distribute the power tasks, forming a novel power system with the coordinated planning of source-network-load-storage as the core. …”
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An End-to-End Solution for Large-Scale Multi-UAV Mission Path Planning by Jiazhan Gao, Liruizhi Jia, Minchi Kuang, Heng Shi, Jihong Zhu

“…Additionally, we integrate a Multi-Start Greedy Rollout Baseline to evaluate diverse trajectories via parallelized greedy searches, thereby reducing policy gradient variance and improving training stability. Experiments demonstrated significant improvements in scalability, particularly in 100-node scenarios, where our method drastically reduced inference time compared to conventional methods, while maintaining a competitive path cost efficiency. …”
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Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position er... by Ruirui Liu, Ding Wang, Jiexin Yin, Ying Wu

“…Subsequently, a set of pseudo-linear equations are constructed, based on which the constrained total least squares optimization model has been formulated for target localization and the Newton iteration is applied to obtain the source position and clock bias simultaneously. …”
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Advanced Load Balancing Based on Network Flow Approach in LTE-A Heterogeneous Network by Shucong Jia, Wenyu Li, Xiang Zhang, Yu Liu, Xinyu Gu

“…Furthermore, a novel algorithm named optimal solution-based LB (OSLB) is proposed. …”
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Research on the Control Method of Force Servo System of Liquid Hydrostatic Guide Oil Film Thickness Test Bench for Machine Tools by Xu Fang, Youmin Wang, Bo Zhu

“…And based on the fast overshoot of the classical PID control, introducing the self-antidisturbance control algorithm, this study established a mathematical model of the test bench electro-hydraulic servo control system. …”
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A comprehensive review of ball detection techniques in sports by Cristiano Moreira, Lino Ferreira, Paulo Jorge Coelho

“…This is a highly debated and researched topic, but most works focus on one sport. Effective generalization of a single method or algorithm to different sports is much harder to achieve. …”
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Challenges of the Biopharmaceutical Industry in the Application of Prescriptive Maintenance in the Industry 4.0 Context: A Comprehensive Literature Review by Johnderson Nogueira de Carvalho, Felipe Rodrigues da Silva, Erick Giovani Sperandio Nascimento

“…The results obtained revealed that prescriptive maintenance offers opportunities for improvement in the production process, such as cost reduction and greater proximity to all actors in the areas of production, maintenance, quality, and management. …”
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A growth posture identification method of immature peaches in natural environments by Jidong Lv, Liangliang Niu, Ying Han, Xiaoqin Sun, Lingyun Wang, Hailong Rong, Ling Zou

“…The model was easily deployed with improved detection speed. …”
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Multi-Modal Federated Learning Over Cell-Free Massive MIMO Systems for Activity Recognition by Seyed Mohammad Sheikholeslami, Pai Chet Ng, Jamshid Abouei, Konstantinos N. Plataniotis

“…Additionally, we employ a modified Particle Swarm Optimization (PSO) algorithm for efficient resource allocation. …”
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Research on Unbalanced Electromagnetic Force Under Static Eccentricity of the Wheel Hub Motor Based on BP Neural Network by Xiangpeng Meng, Yunquan Zhang, Renkai Ding, Wei Liu, Ruochen Wang

“…A BP neural network optimization algorithm can reduce the time of electromagnetic force model simulation for 10 s from 1 h to about 50 s, which greatly improves the calculation efficiency of the electromagnetic force on the basis of ensuring the accuracy of the model, thus providing an unbalanced electromagnetic force model that is more suitable for the dynamic simulation of wheel hub direct-drive electric vehicles, which effectively solves the problem that the traditional electromagnetic force is difficult to couple with the vehicle dynamics model and lays a better foundation for subsequent research on the vertical vibration effect of wheel hub direct-drive electric vehicles.…”
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A New hybrid generalized CG- method for non-linear functions by Abbas Al-Bayati, Hamsa Chilmerane

“…In this paper a new extended generalized conjugate gradient algorithm is proposed for unconstrained optimization, which is considered as anew inverse hyperbolic model .In order to improve the rate of convergence of the new technique, a new hybrid technique between the standard F/R CG-method and Sloboda CG-method using quadratic and non-quadratic models is proposed by using exact and inexact line searches. …”
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Consumer-Centered Collaborative Governance of Regional Business Environment by Tingting Xiang, Hongzhi Lin

“…This paper proposes a bi-level programming model based on consumer welfare, with the upper-level model focusing on optimizing the government’s investment allocation strategy to maximize consumer welfare, and the lower-level model addressing the spatial price equilibrium problem after improving the business environment. …”
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A novel canopy water indicator for UAV imaging to monitor winter wheat water status by Meiyan Shu, Zhenghang Ge, Yang Li, Jibo Yue, Wei Guo, Yuanyuan Fu, Ping Dong, Hongbo Qiao, Xiaohe Gu

“…To develop robust estimation models, four machine learning algorithms were implemented across individual and combined growth stages, and their performance was validated using independent ground-measured datasets that were not used during the training process. …”
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The Application of Practical Clothing Design Method in the Teaching of Clothing Specialty by Miao Li, Rong Fu

“…To improve the teaching practice effect of clothing major, this study applies the practical clothing design method to the teaching of clothing major to analyze the digital clothing design and establishes a convex quadratic conic programming model for a class of force optimization problems. …”
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Lightweight UAV Detection Method Based on IASL-YOLO by Huaiyu Yang, Bo Liang, Song Feng, Ji Jiang, Ao Fang, Chunyun Li

“…To address this, we propose the IASL-YOLO algorithm, which optimizes the YOLOv8s model to enhance detection accuracy and lightweight efficiency. …”
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A Framework for Autonomous UAV Navigation Based on Monocular Depth Estimation by Jonas Gaigalas, Linas Perkauskas, Henrikas Gricius, Tomas Kanapickas, Andrius Kriščiūnas

“…The solution utilizes a depth image estimation model to create an occupancy grid map of the surrounding area and uses an A* path planning algorithm to find optimal paths to end goals while navigating around the obstacles. …”
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Hierarchical Vehicle Scheduling Research on Tide Bicycle-Sharing Traffic of Autonomous Transportation Systems by Mai Hao, Ming Cai, Minghui Fang, Shuxin Jin

“…It minimizes operating costs and maximizes user satisfaction to dynamically optimize scheduling routes and required vehicles within each layered zone. …”
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Data-Driven Customer Retention Strategies in E-Commerce: A Fuzzy Z-Number Approach by Siyin Hu, An Chen

“…For the purpose of evaluating customer churn, we use the Support Vector Machine (SVM) model. In order to improve the performance of the SVM, we tune its parameters using the Coyote Optimization Algorithm (COA). …”
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A deep contrastive learning-based image retrieval system for automatic detection of infectious cattle diseases by Veerayuth Kittichai, Morakot Kaewthamasorn, Apinya Arnuphaprasert, Rangsan Jomtarak, Kaung Myat Naing, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang

“…The model’s performance was also improved by a fine-tuned procedure between k-nearest neighbor and its normalized distance of each data point, including precision of 0.833 ± 0.134, specificity of 0.930 ± 0.054, recall of 0.838 ± 0.118, and accuracy of 0.915 ± 0.025, respectively. …”
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