CKRT coagulation risk prediction and nursing feedback model based on intelligent algorithms by Xianrong Xu, Mou Chen, Lvjing Chen, Kaixing Huang, Shiqi Cao, Wenwen Gao, Kang Liu, Buyun Wu, Huijuan Mao

“…A hybrid machine learning algorithm was applied to predict the timing of Continuous Kidney Replacement Therapy initiation for patients with acute kidney injury. …”
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Research progress in globular fruit picking recognition algorithm based on deep learning by LI Hui, ZHANG Jun, YU Shuochen, LI Zhixin

“…With the continuous research by domestic scholars, YOLO algorithm is also continuously iteratively optimized, and its ability to detect the objects of different sizes and shapes is significantly improved, which can adapt to the maturity degree, size and occlusion of fruits, and improve the detection performance in complex environments.…”
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A multi-objective optimized OLSR routing protocol. by Wenhong Wei, Huijia Wu, Ying He, Qingxia Li

“…Simulation results show that the proposed algorithm can effectively reduce packet loss and end-to-end delay while obtaining better results in HV and Spacing, two multi-objective optimization result evaluation metrics.…”
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Optimization of Vehicle Routing with Pickup Based on Multibatch Production by Hongtao Hu, Jiao Mo, Chengle Ma

“…In the second stage, the Particle Swarm Optimization (PSO) algorithm was used to allocate vehicles to each production batch. …”
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Artificial intelligence-driven modeling of biodiesel production from fats, oils, and grease (FOG) with process optimization via particle swarm optimization by Badril Azhar, Muhammad Ikhsan Taipabu, Cries Avian, Karthickeyan Viswanathan, Wei Wu, Raymond Lau

“…The findings demonstrate the effectiveness of combining ML and optimization techniques to enhance biodiesel production efficiency while reducing costs and energy consumption.…”
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Universality in game-driven random walks with strategies generated by a genetic algorithm by Kouki Tsuji, Kenta Takashima, Yuzuru Sato, Takuma Akimoto

“…Each player follows a strategy categorized as either a mixed strategy or an adaptive strategy optimized via a genetic algorithm (GA) that analyzes the opponent’s past hands. …”
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A Multiobjective Cooperative Driving Framework Based on Evolutionary Algorithm and Multitask Learning by Xia Jiang, Jian Zhang, Qing-yang Li, Tian-yi Chen

“…Based on a multi-objective evolutionary algorithm, CAVs are denoted as a sequence to be searched in solution space, while a multitask learning neural network with adaptive loss function is implemented for optimization target feedback to surrogate the simulation test procedure. …”
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A Detailed Comparison of Two New Heuristic Algorithms Based on Gazelles Behavior by Emine Baş

“…In this study, Mountain Gazelle Optimization (MGO) and Gazelle Optimization Algorithm (GOA) algorithms, which have been newly proposed in recent years, were examined. …”
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RESEARCH ON DYNAMIC PERFORMANCE OF GEAR SYSTEM BASED ON ORTHOGONAL DESIGN AND GENETIC ALGORITHM by WU ZhengWei, WU XunCheng, ZHANG JueCheng

“…Dynamic performance of gear system especially vibration was a typical nonlinear problem,while the vibration was closely related to the gear profile modification,the solving gear profile modification parameters was a nonlinear optimization problem. …”
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Minimum number oriented relay node deployment algorithm in two-tiered WSN by Chun-yu MIAO, Li-na CHEN, Guo-yong DAI, Fan YANG, Qing-zhang CHEN

“…Aiming at minimizing the number of relay nodes distributed in the sensing area while keeping the feasible communication with at least one relay node for every sensor node, two algorithms (i.e. the integral linear programming optimal algorithm and the heuristic algorithm) were proposed. …”
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Service chain deployment algorithms for deterministic end-to-end delay upper bound by Ze’nan WANG, Jiao ZHANG, Shuo WANG, Tao HUANG, F.Richard Yu

“…To solve the problem that the current service chain deployment algorithms cannot guarantee the delay of each packet passing through the service chain (SC), a SC deployment algorithm for deterministic end-to-end delay upper bound was proposed.First, the end-to-end delay bound of the SC was derived based on network calculus.Then, the deterministic end-to-end delay bound of the SC was achieved by collaboratively optimizing the routing of SC and the resource allocation of the virtual network function nodes in the SC.The experimental results show that the proposed algorithm can effectively improve the volume of accepted SC while guaranteeing that the end-to-end delay of each packet satisfies the delay requirements.…”
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Use of Diagnostic Algorithms for *NTRK* Fusion-Positive Tumors in Pathology Institutes in Switzerland by Holger Moch, Gieri Cathomas, Milo Frattini, Wolfram Jochum, Erik Vassella, Laurence de Leval, Joachim Diebold, Christian Britschgi, Thomas McKee, Lukas Bubendorf

“…As the detection of *NTRK* gene fusion opens up new treatment options for patients, it is vital to ensure that the detection methods and diagnostic algorithms in pathology institutes are optimized and of high quality. …”
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Optimal Design of Low Sidelobe Sparse Linear Arrays by Li Wang, Fenggan Zhang, Banghuan Hou

“…The initial value of the algorithm is generated through the chaotic Piecewise map, while the scaling factor is adjusted dynamically in line with the iterations and fitness values. …”
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Comparative Study of Sphere Decoding Algorithm and FCS-MPC for PMSMs in Aircraft Application by Joseph O. Akinwumi, Yuan Gao, Xin Yuan, Sergio Vazquez, Harold S. Ruiz

“…These findings underscore the importance of norm selection, sampling interval optimization, and weighting factor adjustments in balancing THD reduction and switching frequency. …”
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Hybrid genetic algorithm and deep learning techniques for advanced side-channel attacks by Faisal Hameed, Hoda Alkhzaimi

“…These findings validate genetic algorithms as a robust alternative for optimizing side-channel attack models, offering both scalability and consistent performance across diverse attack scenarios while advancing the state of cryptographic security assessment.…”
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Performance of machine learning algorithms to evaluate the physico-mechanical properties of nanoparticle panels by Derrick Mirindi, James Hunter, David Sinkhonde, Tajebe Bezabih, Frederic Mirindi

“…The Pearson correlation analysis reveals a strong relationship between board properties (R = 0.94 for WA–TS; R = 0.93 for MOR–MOE), confirming that nanoparticle treatments enhance performance while maintaining inherent material behavior. Hierarchical clustering grouped nanoparticles by performance: zinc oxide and chitosan+UF+epoxy formed a cluster with the lowest WA and TS, indicating optimal dimensional stability, while GO, rGO, and chitosan-based composites clustered with moderate values. …”
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Leveraging AI to Drive Timely Improvements in Patient Experience Feedback: Algorithm Validation by Mustafa Khanbhai, Catalina Carenzo, Sarindi Aryasinghe, David Manton, Erik Mayer

“…Technical infrastructure, including coding environments and packages for algorithm testing and deployment, was optimized. The algorithm was iteratively trained using bag of words from anonymized data, tailored to accommodate contextual variations, and tested for change in algorithm performance while simultaneously rectifying issues identified. …”
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Unmanned aerial vehicle path planning with hybrid motion algorithm for obstacle avoidance by Venkatasivarambabu Pamarthi, Richa Agrawal

“…To enhance trajectory optimization, the optimized motion planner enhances the Rapidly-exploring Random Tree (RRTX) method with a Covariant Hamiltonian Optimization for Motion Planning (CHOMP) algorithm-based optimizer. …”
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A Heuristic Motion Planning Algorithm for a Mobile Robot With Nonholonomic Constraints by Duc Thien Tran, Duc Huy Pham, Quang Chien Nguyen

“…This paper proposes a heuristic motion planning algorithm to enhance optimal path determination and tracking for a differential drive mobile robot within a global environment. …”
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Adaptive Exploration Artificial Bee Colony for Mathematical Optimization by Shaymaa Alsamia, Edina Koch, Hazim Albedran, Richard Ray

“…By addressing the shortcomings of the traditional ABC algorithm, AEABC significantly advances mathematical optimization, especially in engineering applications. …”
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