Leveraging retinanet based object detection model for assisting visually impaired individuals with metaheuristic optimization algorithm by Alaa O. Khadidos, Ayman Yafoz

“…This paper proposes a novel Object Detection Model for Visually Impaired Individuals with a Metaheuristic Optimization Algorithm (ODMVII-MOA) technique. …”
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Behavioral Modeling of SiC MOSFET Static and Dynamic Characteristics Based on Particle Swarm Optimization Algorithm by Zhibo Zhu, Yang Zhao, Wei Yan

“…The PSO algorithm is used to extract the parameters of the improved Enz-Krummnacher-Vittoz model and a static characteristic behavioral model of the SiC MOSFET is established, avoiding a large amount of simulation or calculation time for circuit and datasheet-drive models, the efficiency is increased by 60%, and the model accuracy is 98% compared to the datasheet. …”
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Animation Pose Generation Model Based on Kinect Depth Image and Occlusion-Robust Pose-Maps Algorithm by Zhenxi Yu, Ting Wang, Peng Tian, Xuejie Li

“…Aiming at the problem of low efficiency and difficulty in adapting to complex interactive scenes in traditional animation pose generation methods, a dynamic pose generation model based on Kinect depth image and an occlusion robust pose map algorithm is proposed. …”
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Distributed data trading algorithm based on multi-objective utility optimization by Xiaohong HUANG, Yong ZHANG, Desheng SHAN, Yekui QIAN, Lu HAN, Dandan LI, Qun CONG

“…The traditional centralized data trading models are not well applicable to the current intelligent era where everything is interconnected and real-time data is generated, and in order to maximize the use of collected data, it is essential to design an effective data trading framework.Therefore, a distributed data trading framework based on consortium blockchain was proposed, which realized P2P data trading without relying on a third party.Aiming at the problem that existing data trading models only consider the factors of the data itself and ignore the factors related to user tasks, a bi-level multi-objective optimization model was constructed based on multi-dimensional factors, such as data quality, data attributes, attribute relevance and consumer competition, to optimize the utilities of data provider (DP) and data consumer (DC).To solve the above model, an improved multi-objective genetic algorithm-collaborative NSGAII was proposed, calculated by the cooperation of DP, DC and data aggregator (AG).The simulation results show that the collaborative NSGAII achieves better performance in terms of the utilities of DP and DC, thus realizing more effective data trading.…”
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Improving inverter efficiency for electric vehicles: Experimental validation of the neural network-based SHE technique using RT-LAB by Seyf Eddine Bechekir, Mokhtaria Jbilou, Mostefa Brahami, Fatima Zohra Boudjella, Imen Souhila Bousmaha, Mimouna Oukli, Said Nemmich

“…This approach improves inverter performance and offers new optimization possibilities for various applications, including electric vehicles. …”
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A Comprehensive Review and Benchmarking of Fairness-Aware Variants of Machine Learning Models by George Raftopoulos, Nikos Fazakis, Gregory Davrazos, Sotiris Kotsiantis

“…This paper presents a comprehensive survey of classical machine learning models that have been modified or enhanced to improve fairness concerning sensitive attributes (e.g., gender, race). …”
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A Novel High-Precision Workpiece Self-Positioning Method for Improving the Convergence Ratio of Optical Components in Magnetorheological Finishing by Yiang Zhang, Pengxiang Wang, Chaoliang Guan, Meng Liu, Xiaoqiang Peng, Hao Hu

“…A composite data acquisition method using both a camera and probe is designed, and a stepwise global optimization model is constructed by integrating a synchronous iterative localization algorithm with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). …”
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Optimization of integrated energy system considering P2G oxygen-enriched improvement and hybrid solar energy utilization by Xiaohui YANG, Zhao WAN, Riying XIAO, Zeyu YANG, Zecheng HU, Chilyu WU

“…Secondly, because the boiler efficiency is affected by the oxygen concentration, the optimal oxygen supply state for each period of the oxygen-consuming equipment is determined by a combined algorithm of genetic algorithm and Gurobi solver. Finally, the solar energy efficiency is improved by using mixed solar energy to reduce the use of fossil energy. …”
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Advances in Surveying Topographically Complex Ecosystems with UAVs: Manta Ray Foraging Algorithms by Shijie Yang, Jiateng Yuan, Zhibo Chen, Hanchao Zhang, Xiaohui Cui

“…The α-hop clustering algorithm used in this paper has a huge advantage in space and time complexity compared with existing clustering algorithms, and the accuracy of data extraction is relatively improved by 7.57% and 6.95%. …”
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Research of Models of Topological Relations of Spatial Objects by Vladislav G. Gorshkov, Dmitriy M. Murin, Olga P. Yakimova

“…We have proposed an improved model of nine intersections, which takes into account the topological conflict that occurs when a point object is located next to a simplified line. …”
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The Impact of Assimilating Ionosphere and Thermosphere Observations on Neutral Temperature Improvement: Observing System Simulation Experiments Using EnKF by Jianhui He, Xinan Yue, Zhipeng Ren

“…In this work, the impact of different ionosphere and thermosphere observing systems on the improvement of neutral temperature of the data assimilation model has been investigated by a series of observing system simulation experiments. …”
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A personalized recommendation algorithm for English exercises incorporating fuzzy cognitive models and multiple attention mechanisms by Yixuan Zhang, Yanyi Wang

“…In response to the above problems in the recommendation of English reading, writing and translation exercises in higher education, this paper proposes an algorithm that combines improved fuzzy cognitive diagnosis model and multi-head attention mechanism to predict students’ performance on future recommended exercises. …”
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Load Estimation Algorithm Based on Extended Kalman Filter for Freight Train by DENG Hao

“…In the simulation experiment of 2,000-ton load, the estimation error ranged from 3.5% to 4%, demonstrating the proposed algorithm could effectively improve the accuracy of the ATO system, with lower requirements on multi-particle motion models.…”
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Improving the quality of SAR radar image detection and identification using neural network to increase the security factor of military tactics by ali alizade, Jalil Mazloum, behrang hadian, ahmad dolatkhah, behnam dorostkar

“…The main goal is to provide a powerful algorithm based on artificial intelligence to improve the detection of SAR radar ground targets with object detection algorithms that are obtained through airplanes or satellites in order to monitor ground targets.Analysis: In the pre-processing stage, after reducing the effect of speckle noise on SAR radar images, the proposed model is investigated to improve the detection of SAR radar ground targets with the help of Lee filter.Analysis of the results: by using YOLO and RCNN algorithms, the RCNN algorithm has a better performance in detecting denoised MSTAR images with an average accuracy of 99.84% compared to YOLO with an average accuracy of 90.424%, but in detecting noisy MSTAR images, the YOLO method With an average accuracy of 80.875%, compared to the RCNN method with an average accuracy of 61.49%, it has a better performance for identifying and improving images and increasing the reliability of the system.…”
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Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

“…Seven different experimental data sets are used to improve the performance of the proposed differential evolution with an integrated mutation per iteration algorithm (DEIMA). …”
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Complex Working Condition Bearing Fault Diagnosis Based on Multi-Feature Fusion and Improved Weighted Balance Distribution Adaptive Approach by Jing Yang, Yanping Bai, Ting Xu, Rong Cheng, Wendong Zhang, Guojun Zhang

“…In order to improve the accuracy and generalization ability of fault diagnosis for rotating machinery bearings under complex working conditions, a new model based on multi-feature fusion and improved weighted balance distribution adaptation is proposed. …”
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Synergizing advanced algorithm of explainable artificial intelligence with hybrid model for enhanced brain tumor detection in healthcare by Kamini Lamba, Shalli Rani, Mohammad Shabaz

“…As understanding reasoning behind their predictions is still a great challenge for the healthcare professionals and raised a great concern about their trustworthiness, interpretability and transparency in clinical settings. Thus, an advanced algorithm of explainable artificial intelligence (XAI) has been synergized with hybrid model comprising of DenseNet201 network for extracting the most important features based on the input Magnetic resonance imaging (MRI) data following supervised algorithm, support vector machine (SVM) to distinguish distinct types of brain scans. …”
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Application of machine learning algorithm incorporating dietary intake in prediction of gestational diabetes mellitus by Tianze Ding, Peijie Liu, Jie Jia, Hui Wu, Jie Zhu, Kefeng Yang

“…We applied random forest mean decrease impurity for feature selection and the models are built using logistic regression, XGBoost, and LightGBM algorithms. …”
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GCB‐YOLO: A Lightweight Algorithm for Wind Turbine Blade Defect Detection by Zhiming Zhang, Chaoyi Dong, Ze Wei, Xiaoyan Chen, Weidong Zan, Yao Xue

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An improved long-term high-resolution surface pCO2 data product for the Indian Ocean using machine learning by Prasanna Kanti Ghoshal, A.P. Joshi, Kunal Chakraborty

“…In this study, we employ a machine learning algorithm to correct the deviations in high-resolution (1/12°) model simulations of surface pCO2 from the INCOIS-BIO-ROMS model (pCO2 model) for the period 1980–2019, using available observations (pCO2 obs). …”
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