Technology for risk assessment at product lifecycle stages using fuzzy logic by A. N. Chesalin, S. Ya. Grodzenskiy, Pham Van Tu, M. Yu. Nilov, A. N. Agafonov

“…It is suggested that if there is a priori information about previously occurred events that can be used for risk analysis and fore casting, the fuzzy conclusion should be refined using widely known methods of mathematical statistics, optimization algorithms, for example, gradient descent, simplex method or genetic algorithms. …”
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Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network by Liping Yan, Yue Tang, Chan Peng, Yu Cai, Wenbo Zhang, Jing Wang

“…Compared with three non-negotiated optimization algorithms based on swarm technology, EMR2SM is verified by experiments that it improves the efficiency and accuracy of the optimal route selection for multiple vehicles and reduces vehicle emissions, which can effectively reduce traffic congestion and environmental pollution.…”
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Facial emotion based smartphone addiction detection and prevention using deep learning and video based learning by C. Joseph, P. Uma Maheswari

“…Experimental results demonstrate significant improvements in students’ behavior and reductions in smartphone usage post-intervention. …”
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Nondestructive freshness recognition of chicken breast meat based on deep learning by Rui Jian, Guangbo Li, Xie Jun, Guolong Shi

“…Experimental results show that in the improved algorithm, YOLOv8n_CA_DSC3 achieves suboptimal recall rate but optimal precision, average precision at IoU = 0.5, and average precision at IoU = 0.5:0.95. …”
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Degradation and reliability assessment of accuracy life of RV reducers by XU Hang, NIE Yixuan, WEN Dongjie, REN Jihua, HONG Zhihui

“…A Gaussian process regression model optimized by genetic algorithm was established using vibration characteristic data to optimize the prediction of transmission accuracy.ResultsThe results show that the prediction accuracy based on Gaussian process regression model is significantly better than that of traditional regression model. …”
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Sonar-Based Simultaneous Localization and Mapping Using the Semi-Direct Method by Xu Han, Jinghao Sun, Shu Zhang, Junyu Dong, Hui Yu

“…To obtain better feature extraction results in specific directions, we propose a method that accelerates the computation of the two-dimensional SO-CFAR algorithm, with the time cost being only a very slight increase compared to the one-dimensional SO-CFAR. …”
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Frequency Regulation Provided by Doubly Fed Induction Generator Based Variable-Speed Wind Turbines Using Inertial Emulation and Droop Control in Hybrid Wind–Diesel Power Systems by Muhammad Asad, José Ángel Sánchez-Fernández

“…Wind energy (WE) is the most adopted renewable energy source due to its technical readiness, competitive cost, and environmentally friendly characteristics. …”
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Research on collaborative scheduling strategies of multi-agent agricultural machinery groups by Ziyi Wang, Fan Zhang, Shiji Ma, Hailong Wang, Shunyao Zhang, Xiaozhong Gao

“…Finally, the solution is optimized through a local search strategy. In this study, three dispatch centers were selected within the maize growing area of Hebei Province, and comparative analyses were conducted for 20, 40, 50, 100 and 120 farmlands, respectively.The results indicate that the MCMPP-DRL algorithm achieves a reduction in total scheduling costs of at least 9.66%, 14.34% and 24.41% compared to Ant Colony Optimization (ACO), Simulated Annealing (SA) and Genetic Algorithms(GA), respectively.The significant optimization in scheduling costs demonstrates that the MCMPP-DRL algorithm establishes a robust theoretical foundation and offers technical support for addressing complex scheduling problems involving multiple dispatch centers and multiple.…”
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Machine Learning-Augmented Triage for Sepsis: Real-Time ICU Mortality Prediction Using SHAP-Explained Meta-Ensemble Models by Hülya Yilmaz Başer, Turan Evran, Mehmet Akif Cifci

“…<b>Background/Objectives:</b> Optimization algorithms are acknowledged to be critical in various fields and dynamical systems since they provide facilitation in identifying and retrieving the most possible solutions concerning complex problems besides improving efficiency, cutting down on costs, and boosting performance. …”
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IMAGE SEGMENTATION AND OBJECT SELECTION BASED ON MULTI-THRESHOLD PROCESSING by Vladimir Yu. Volkov, Oleg A. Markelov, Mikhail I. Bogachev

“…Although this is achieved at the cost of the resource-consuming multi-threshold analysis procedure for each processed image, this can be also partially compensated by the simplicity of the algorithm and its possible parallel implementation.…”
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Enhancing prediction of wildfire occurrence and behavior in Alaska using spatio-temporal clustering and ensemble machine learning by A. Ahajjam, M. Allgaier, R. Chance, E. Chukwuemeka, J. Putkonen, T. Pasch

“…A sequential Genetic Algorithm (GA) is employed for cost-effective feature selection from 49 geospatial features, including remote sensing and reanalysis data. …”
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An Adaptive Unscented Kalman Ilter Integrated Navigation Method Based on the Maximum Versoria Criterion for INS/GNSS Systems by Jiahao Zhang, Kaiqiang Feng, Jie Li, Chunxing Zhang, Xiaokai Wei

“…On this basis, fully considering the high-order moments of estimation errors, the maximum versoria criterion is introduced as the optimization criterion to construct a novel cost function, further effectively suppressing deviations caused by non-Gaussian disturbances and improving system navigation accuracy. …”
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Enhancing Crowd Safety at Hajj: Real-Time Detection of Abnormal Behavior Using YOLOv9 by Amani A. Alsabei, Tahani M. Alsubait, Hosam H. Alhakami

“…Leveraging deep learning, this research accurately identifies features of abnormal behavior from the HAJJv2 dataset, specifically curated and annotated for the Hajj context. Optimization of the YOLOv9 algorithm for this scenario demonstrated superior performance metrics (mean Average Precision (mAP@0.5), Recall, and Precision) when compared with its predecessors (YOLOv4, YOLOv5, YOLOv7, and YOLOv8), highlighting significant improvements in detection accuracy and real-time applicability. …”
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Optimising the Selection of Input Variables to Increase the Predicting Accuracy of Shear Strength for Deep Beams by Mohammed Majeed Hameed, Faidhalrahman Khaleel, Mohamed Khalid AlOmar, Siti Fatin Mohd Razali, Mohammed Abdulhakim AlSaadi

“…The feature-section algorithm based on the combination of genetic algorithm and information theory (GAITH) was used to select the most important input combinations and introduce them into the prediction models. …”
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Hybrid Damping Mode MR Damper: Development and Experimental Validation with Semi-Active Control by Jeongwoo Lee, Kwangseok Oh

“…This configuration supports four damping modes—Soft/Soft, Hard/Soft, Soft/Hard, and Hard/Hard—allowing adaptability to varying driving conditions. Magnetic circuit optimization ensures rapid damping force adjustments (≈10 ms), while a semi-active control algorithm incorporating skyhook logic, roll, dive, and squat control strategies was implemented. …”
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Hardware-in-loop implementation of an adaptive MPPT controlled PV-assisted EV charging system with vehicle-to-grid integration by Surabhi Singh, Hari Om Bansal

“…In addition, the designed bidirectional charging system maximizes solar energy collection, minimizes the charging cost, and improves grid stability through demand balancing. …”
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Online Attentive Kernel-Based Off-Policy Temporal Difference Learning by Shangdong Yang, Shuaiqiang Zhang, Xingguo Chen

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Enhancing Lifetime and Reliability in WSNs: Complementary of Dual-Battery Systems Energy Management Strategy by Mehrshad Eskandarpour, Hossein Soleimani

“…Unlike previous approaches, this system enables simultaneous charging and load powering and is specifically optimized for energy-harvesting WSN environments. Simulation results in MATLAB/Simulink demonstrate that the system improves battery lifespan by up to 25% compared to conventional single-battery configurations, while ensuring stable voltage regulation and improved reliability under variable loads. …”
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Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…Initially, the SIMDP-EDLIoT approach uses linear scaling normalization (LSN) to ensure that the input data is scaled appropriately. Besides, the Improved Osprey Optimization Algorithm (IOOA)-based feature selection is employed to classify the most relevant features, enhancing the efficiency of the system by reducing dimensionality. …”
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A 5G network based conceptual framework for real-time malaria parasite detection from thick and thin blood smear slides using modified YOLOv5 model by Swati Lipsa, Ranjan Kumar Dash, Korhan Cengiz, Nikola Ivković, Adnan Akhunzada

“…Conclusion Our model exemplifies how a generic one-stage object detection algorithm, such as YOLOv5x, can be repurposed to detect objects as small as malaria parasites from microscopic visuals in a cost-effective manner over the 5G network. …”
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