Optimal allocation of renewable energy resources in a smart grid under neutrosophic credibility-based uncertainty by Muhammad Zafar Abbas, Rukhshanda Anjum, Muhammad Umar Mirza, Abdulrahman A. Almehizia, Amir Hussain

“…Based on NCNs, we introduce a novel aggregation operator termed as generalized neutrosophic fuzzy credibility numbers weighted averaging (GNFCNWA) operator which enhances aggregation of uncertain information and improves the credibility of decisions. Furthermore, we also provide an algorithm that extends the utilization of NCNs with the GNFCNWA operator in a complete approach to decision-making. …”
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Performance analysis and testing of personal influence algorithm in online social networks by Yong QUAN, Yan JIA, Liang ZHANG, Zheng ZHU, Bin ZHOU, Binxing FANG

“…Social influence is the key factor to drive information propagation in online social networks and can be modeled and analyzed with social networking data.As a kind of classical personal influence algorithm,two parallel implementation versions of a PageRank based method were introduced.Furthermore,extensive experiments were conducted on a large-scale real dataset to test the performance of these parallel methods in a distributed environment.The results demonstrate that the computational efficiency of the personal influence algorithm can be improved significantly in massive data sets by virtue of existing big data processing framework,and provide an empirical reference for the future research and optimization of the algorithm as well.…”
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Robust Optimal Sizing of a Stand-Alone Hybrid Renewable Energy System Using Machine Learning-Based Uncertainty Sets by Ali Keyvandarian, Ahmed Saif, Ronald Pelot

“…Simulation reveals a 10.7% increase in capital cost on average but a 36.2% decrease in operational cost, resulting in a 16.4% total cost reduction and an 8.1% improvement in system reliability compared to the nominal model employing point estimates. …”
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Algorithm of underdetermined convolutive blind source separation for high reverberation environment by Yuan XIE, Tao1 ZOU, Weijun SUN, Shengli XIE

“…To separate the underdetermined convolutive mixture signals in the high reverberation environment, a novel algorithm of underdetermined convolutive blind source separation was proposed.Aiming at the influence of high reverberation environment, a global impulse response network was designed to weaken reverberation echo, improving signal quality.A new mathematical model of time-frequency mixing signals was established based on the global impulse response network.The global impulse response matrix which shortened the length of the traditional impulse response, reduced the approximation error of model transformation caused by high reverberation.The real-time update learning rules of model parameters were designed based on the theory of nonnegative matrix factorization, and the source signal separation problem was converted into the model parameter optimization problem, achieving blind source separation of mixing signals.Experimental results show that the proposed algorithm can effectively realize the blind source separation of Chinese and English speech and music signals, and the comparision with existing popular algorithms verified the superiority of the proposed algorithm.…”
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Low error floor LT coding algorithm for unequal error protection by Xin SONG, Shuyan NI, Zhe ZHANG, Yurong LIAO, Tuofeng LEI

“…Conclusions: In this paper, a systematic unequal error protection LT coding scheme is designed, and a check degree distribution design model suitable for this scheme is constructed to solve the problem of high error floor existing in the conventional UEP-LT algorithm in the AWGN channel.The main idea of this scheme is to design fixed coding segments,rateless coding segments and systematic node segments and transmit them in sequence.The advantage of this scheme is that it can provide non-zero LLR information as early as possible for information nodes, and make the MIB and the LIB obtain different and flexibly adjustable average degrees.In addition,based on the extrinsic information transfer(EXIT)chart,the check degree distribution is designed for the fixed segment and the rateless segment,so that the MIB can obtain the optimal protection performance,and the convergence performance of the LIB can be improved as much as possible. …”
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A Deep Learning-Based Algorithm for Ceramic Product Defect Detection by Junxiang Diao, Hua Wei, Yawei Zhou, Zhihua Diao

“…Additionally, an adaptive threshold method is proposed to improve the traditional Canny edge detection algorithm, significantly enhancing its accuracy in defect edge detection. …”
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A Linear Fitting Algorithm Based on Modified Random Sample Consensus by Yujin Min, Yun Tang, Hao Chen, Faquan Zhang

“…This algorithm significantly reduces the influence of outliers on the dataset, resulting in improved fitting accuracy and enhanced robustness. …”
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Prediction Model of Water Demand for Scouring Siltation in Coastal River Networks Based on APSO and SVM: A Case Study of Doulong Port by MA Zhutong, XIANG Long, YAN Ke

“…By analyzing the in-situ monitoring data for the downstream channel of Doulong Port from 2001 to 2018, the paper extracted key variables such as initial riverbed volume, siltation amount, time duration, rainfall volume, and the frequency of sluice openings. A predictive model of water demand for scouring siltation was constructed, which combined adaptive particle swarm optimization (APSO) algorithm with support vector machine (SVM) and optimized the model parameters of the SVM through the APSO algorithm, enhancing the prediction accuracy of the APSO-SVM model. …”
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Prediction Model of Water Demand for Scouring Siltation in Coastal River Networks Based on APSO and SVM: A Case Study of Doulong Port by MA Zhutong, XIANG Long, YAN Ke

“…By analyzing the in-situ monitoring data for the downstream channel of Doulong Port from 2001 to 2018, the paper extracted key variables such as initial riverbed volume, siltation amount, time duration, rainfall volume, and the frequency of sluice openings. A predictive model of water demand for scouring siltation was constructed, which combined adaptive particle swarm optimization (APSO) algorithm with support vector machine (SVM) and optimized the model parameters of the SVM through the APSO algorithm, enhancing the prediction accuracy of the APSO-SVM model. …”
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An Extended Firefly Algorithm for Enhanced Information Diffusion with Multi-Factor Considerations by Amjad Alloush, Ghaida Rebdawi:, Mohammad Saeed Abou Trab

“…The proposed model is evaluated using multiple real-world datasets, including Twitter and Reddit, and compared against state-of-the-art optimization-based diffusion models such as PSO, ACO, and GWO. …”
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Enhancing Kidney Disease Diagnosis Using ACO-Based Feature Selection and Explainable AI Techniques by Abbas Jafar, Myungho Lee

“…This paper aims to address these limitations by creating an effective machine-learning-based approach that integrates ant colony metaheuristic optimization algorithms for feature selection and explainable artificial intelligence techniques such as SHAP and LIME for model interpretation. …”
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Study on Lightweight Bridge Crack Detection Algorithm Based on YOLO11 by Xuwei Dong, Jiashuo Yuan, Jinpeng Dai

“…Additionally, the algorithm improves detection accuracy without increasing the model size. …”
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Pulmonary Nodules Detection Algorithm Combining Multi-view and Attention Mechanism by LIU Yu-bo, LIU Guo-zhu, SHI Cao, XU Can-hui

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Barefoot Footprint Detection Algorithm Based on YOLOv8-StarNet by Yujie Shen, Xuemei Jiang, Yabin Zhao, Wenxin Xie

“…This study proposes an optimized footprint recognition model based on an enhanced StarNet architecture for biometric identification in the security, medical, and criminal investigation fields. …”
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Research on Semantic Segmentation Algorithm for Infrared Moving Targets in Complex Backgrounds by Ji Haoyu, Meng Weihua, Zhang Xinchao, Duan Jingfei, Zhang Meng

“…Based on the publicly available target detection and tracking dataset, an infrared image semantic segmentation dataset is annotated and constructed. The STDC-Seg model is used to optimize the characteristics of infrared images, and an infrared target semantic segmentation algorithm STDC-Infrared is proposed. …”
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Computer-economical optimization method for solving inverse problems of determining electrophysical properties of objects in eddy current structroscopy by V. Ya. Halchenko, R. V. Trembovetska, V. V. Tychkov

“…Integration of multiple capabilities in the surrogate model that combine the advantages of high-performance computing and optimization algorithms in the factor space reduced by the Kernel PCA (Principal Component Analysis) method. …”
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Risk assessment and prevention in airport security assurance by integrating LSTM algorithm. by Yao Hu, Liguang Qiao, Feng Gu

“…It can be summarized that the algorithmic model has good accuracy and robustness. …”
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Elastic Optimization for Stragglers in Edge Federated Learning by Khadija Sultana, Khandakar Ahmed, Bruce Gu, Hua Wang

“…The results confirm the improved performance of our approach over benchmark algorithms.…”
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Optimized Luenberger Observer-Based PMSM Sensorless Control by PSO by Rongfu Luo, Zenghui Wang, Yanxia Sun

“…Therefore, this paper is to use the particle swarm optimization (PSO) algorithm to optimize the PI parameters of PLL and speed-loop of Luenberger observer of the system. …”
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Research on PBS buffer scheduling strategy problems based on genetic algorithms by Zhang Yaodan, Shi Yuanbo, Xu Jianjun, Wei Zhiye

“…A genetic algorithm optimized vehicle selection from the PBS, adhering to constraints.Analysis showed this method improved efficiency by nearly 40% compared to traditional linear scheduling. …”
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