Optimized AI and IoT-Driven Framework for Intelligent Water Resource Management by Mahmoud Badee Rokaya Mahmoud, Dalia Ismaeil Ibrahim Hemdan, Samah Hazzaa Alajmani, Raneem Yousif Alyami, Ghada Elmarhomy, Hassan Hashim, El-Sayed Atlam

“…This study presents an artificial intelligence-based optimization framework that improves forecasting accuracy, computational speed, and real-time adaptability. …”
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A Prescriptive Approach Based on Fuzzy Cognitive Maps and Genetic Algorithms for Disease Management in Beef Production by Rodrigo Garcia, Jose Aguilar, Angel Pinto, William Hoyos

“…The FCM captures expert knowledge through causal relationships between symptoms, treatments, and diagnoses, while the GA optimizes treatment actions to achieve desired health outcomes. …”
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Algorithm for Managing Patients Hospitalized in the Surgical Wards Due to COVID-19-Related Acute Abdominal Pathology by D. G. Buribayev, D. B. Tulyaganov, Kh. E. Anvarov

“…The application of the developed algorithm will optimize the management of patients with COVID-19-related acute surgical pathology, guarantee rapid decision-making while minimizing the risk of infection, reduce the risk of complications and adverse outcomes.…”
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Emerging technologies in airway management: a narrative review of intubation robotics and anatomical structure recognition algorithms by Weixiong Chen, Yu Tian, Yingjie Wang, Lili Feng, Mannan Abdul, Shuangshuang Li, Wenxian Li, Yuan Han

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A Fine-Grained Aircraft Target Recognition Algorithm for Remote Sensing Images Based on YOLOV8 by Xiao-Nan Jiang, Xiang-Qian Niu, Fan-Lu Wu, Yao Fu, He Bao, Yan-Chao Fan, Yu Zhang, Jun-Yan Pei

“…This article addresses the issues of missed and false detections in existing aircraft target fine-grained recognition algorithms for remote sensing images by proposing an improved algorithm based on YOLOv8, called FD-YOLOv8 (Focus Detail-YOLOv8). …”
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Operational response to contamination in water distribution systems: a multi-objective Bayesian optimization approach by Khalid Alnajim, Ahmed A. Abokifa

“…The optimization framework aims to balance the conflicting objectives of minimizing response time while maximizing water quality metrics after contamination events. …”
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Research on coal mine robot positioning algorithm based on integration of ORB-SLAM3 vision and inertial navigation by Wei CHEN, Shuaida WU, Zijian TIAN, Fan ZHANG, Yi LIU

“…In feature point matching, LK optical flow method based on image pyramid is introduced to reduce the number of optimization iterations. After the feature point matching is completed, the RANSAC algorithm is added to remove the mismatched feature points and improve the matching accuracy of the feature points. …”
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Gait and Trajectory Optimization by Self-Learning for Quadrupedal Robots with an Active Back Joint by Ariel Masuri, Oded Medina, Shlomi Hacohen, Nir Shvalb

“…The algorithm actively optimizes 12 of the robot’s dynamic walking parameters. …”
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Artificial Intelligence Dystocia Algorithm (AIDA) as a Decision Support System in Transverse Fetal Head Position by Antonio Malvasi, Lorenzo E. Malgieri, Tommaso Difonzo, Reuven Achiron, Andrea Tinelli, Giorgio Maria Baldini, Lorenzo Vasciaveo, Renata Beck, Ilenia Mappa, Giuseppe Rizzo

“…Additionally, the investigation analyzed the potential role of Artificial Intelligence Dystocia Algorithm (AIDA) as an innovative decision support system in standardizing diagnostic approaches and optimizing clinical decision-making in cases of fetal malposition. …”
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Machine-Learning-Algorithm-Assisted Portable Miniaturized NIR Spectrometer for Rapid Evaluation of Wheat Flour Processing Applicability by Yuling Wang, Chen Zhang, Xinhua Li, Longzhu Xing, Mengchao Lv, Hongju He, Leiqing Pan, Xingqi Ou

“…By employing an improved whale optimization algorithm (iWOA) coupled with a successive projections algorithm (SPA), we selected the 20 most informative wavelengths (MIWs) from the full range spectra, allowing the iWOA/SPA-SOA-SVR model to predict SV with correlation coefficient and root-mean-square errors in prediction (R_P and RMSE_P) of 0.9605 and 0.2681 mL. …”
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Research on Adaptive Planning of Three-Dimensional Trajectory for Uncrewed Aerial Vehicle Inspection Based on Nonlinear Weibull Algorithm by Zhuang Liu, Ning Yang, Jiaxing Fu, Huanqing Cai, Xuebei Wei

“…An S-shaped characteristic function-based nonlinear evolution factor is employed to balance global exploration and local exploitation of the optimal path, while a Weibull flight operator mutation strategy is designed to enable the algorithm to escape from locally optimal paths, enrich the search space, and improve convergence accuracy. …”
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Power Line Segmentation Algorithm Based on Lightweight Network and Residue-like Cross-Layer Feature Fusion by Wenqiang Zhu, Huarong Ding, Gujing Han, Wei Wang, Minlong Li, Liang Qin

“…Experimental results demonstrate that compared with classical UNet, the optimized network achieves 2.05% and 2.58% improvements in F1-Score and IoU, respectively, while reducing the parameter count to 57.25% of the original model. …”
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Fluid–Structure Interaction Study in Unconventional Energy Horizontal Wells Driven by Recursive Algorithm and MPS Method by Xikun Gao, Dajun Zhao, Yi Zhang, Yong Chen, Zhanzhao Gao, Xiaojiao Zhang, Shengda Wang

“…This research provides a framework for energy-efficient drilling in complex reservoirs, balancing efficiency with wellbore integrity and improving outcomes in the unconventional energy sector.…”
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Singular Value Decomposition (SVD) Method for LiDAR and Camera Sensor Fusion and Pattern Matching Algorithm by Kaiqiao Tian, Meiqi Song, Ka C. Cheok, Micho Radovnikovich, Kazuyuki Kobayashi, Changqing Cai

“…Unlike traditional calibration methods that require manual targets, our approach is targetless, extracting matched patterns from projected LiDAR point clouds and 2D image segments. The algorithm computes the optimal transformation matrix between sensors, correcting misalignments in rotation, translation, and scale. …”
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Synergetic simplified super-twisting algorithm control for stability enhancement of PV/BESS-based DC microgrid by Naamane Debdouche, Ali Chebabhi, Habib Benbouhenni, Fatma-Zohra Hadjaidji, Z. M. S. Elbarbary, Saad F. Al-Gahtani

“…The study shows that SSSTA improves the performance and stability of DC-MG systems incorporating solar PV and batteries. …”
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Optimizing the lifetime of wireless sensor networks via reinforcement-learning-based routing by Wenjing Guo, Cairong Yan, Ting Lu

“…Reinforcement-learning-based routing protocol takes advantage of the intelligent algorithm of reinforcement learning to search for the optimal routing path for data transmission. …”
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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

“…Therefore, it is reasonable to model the problem of improving network scalable degree as minimizing network coupling degree,and it is feasible to improve network scalable degree by reducing network coupling degree.2)The upper limit of computational complexity of the proposed algorithm is <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi mathvariant="script">O</mi><mo stretchy="false">(</mo><mi>K</mi><mi>N</mi><msub> <mi>log</mi> <mn>2</mn> </msub> <mi>N</mi><mo>+</mo><msup> <mi>k</mi> <mn>2</mn> </msup> <mo>+</mo><mi>N</mi><mi>N</mi><msub> <mover accent="true"> <mi>N</mi> <mo>¯</mo> </mover> <mtext>p</mtext> </msub> <mo stretchy="false">)</mo></math></inline-formula>,while that of directly solving the optimization problem is<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"><mi mathvariant="script">O</mi><mo stretchy="false">(</mo><msup> <mi>N</mi> <mrow> <msub> <mover accent="true"> <mi>N</mi> <mo>¯</mo> </mover> <mtext>u</mtext> </msub> <mi>K</mi></mrow> </msup> <mo stretchy="false">)</mo></math></inline-formula>.3)For theoretical analysis of the network scalable degree,take Fig.3 as an example.If AP2 changes,12 APs in Fig. 3(a)are affected and the network scalable degree is η₂=0.51,while 4 APs in Fig.3(c)are affected and the network scalable degree is η₂=0.79.4)Fig.5 shows the simulation results of network scalable degree.Compared with the traditional strategy,the network scalable degree is improved by 9.59% with 4.43% user rate loss.Compared with the strategy in[10],the network scalable degree is improved by 22.15% with 4.99% user rate loss. 5) The algorithm parameters, the threshold β₀of overlap rate and the upper limit number N₀of AP associated, effect the performance.As shown in Fig.6,with β₀or N₀decreases,η increases and the total user rate decreases. …”
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A comprehensive review of artificial intelligence approaches for smart grid integration and optimization by Malik Ali Judge, Vincenzo Franzitta, Domenico Curto, Andrea Guercio, Giansalvo Cirrincione, Hasan Ali Khattak

“…The advanced metaheuristic algorithms are a good addition to the literature, they are still in emerging stages and their performance can further be improved. …”
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Impact of Network Configuration on Hydraulic Constraints and Cost in the Optimization of Water Distribution Networks by Mojtaba Nedaei

“…The research focuses on designing and optimizing various WDN configurations while adhering to hydraulic constraints. …”
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Adaptive optimization of electromyographic channels for intelligent prosthetic hands based on individual differences by Jianzhuang Zhao, Ye Tian, Yuxuan Wang, Weiye Ji, Mingchi Zhu

“…Compared to a single optimization algorithm, the proposed algorithm can adaptively optimize the electrode configuration based on individual differences while ensuring recognition effectiveness, retaining electrode channel information that significantly contributes to gesture classification recognition, and meeting the stable recognition of their motion intentions by different subjects.…”
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