Improved YOLO for long range detection of small drones by Sicheng Zhou, Lei Yang, Huiting Liu, Chongqin Zhou, Jiacheng Liu, Yang Wang, Shuai Zhao, Keyi Wang

“…Inspired by ARM CPU efficiency optimizations, the model uses depthwise separable convolutions and efficient activation functions to reduce parameter size. …”
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EGNAS: Efficient Graph Neural Architecture Search Through Evolutionary Algorithm by Younkyung Jwa, Chang Wook Ahn, Man-Je Kim

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A deep learning-based algorithm for the detection of personal protective equipment. by Bo Tong, Guan Li, Xiangli Bu, Yang Wang, Xingchen Yu

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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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The Application of Kalman Filter Algorithm in Rail Transit Signal Safety Detection by Zhinong Miao, Qilong Liao

“…Firstly, the improved Kalman filter algorithm is used to denoise the signal to ensure the accuracy of signal transmission. …”
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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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Illustration visual communication based on computer vision image retrieval algorithm by H.Z. Zhang

“…Therefore, this paper optimizes the feature extraction module of convolutional neural network and fuses hash algorithm to improve the efficiency and speed of image retrieval. …”
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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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Task distribution offloading algorithm of vehicle edge network based on DQN by Haitao ZHAO, Tangwei ZHANG, Yue CHEN, Houlin ZHAO, Hongbo ZHU

“…In order to achieve the best balance between latency,computational rate and energy consumption,for a edge access network of IoV,a distribution offloading algorithm based on deep Q network (DQN) was considered.Firstly,these tasks of different vehicles were prioritized according to the analytic hierarchy process (AHP),so as to give different weights to the task processing rate to establish a relationship model.Secondly,by introducing edge computing based on DQN,the task offloading model was established by making weighted sum of task processing rate as optimization goal,which realized the long-term utility of strategies for offloading decisions.The performance evaluation results show that,compared with the Q-learning algorithm,the average task processing delay of the proposed method can effectively improve the task offload efficiency.…”
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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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A Linear Fitting Algorithm Based on Modified Random Sample Consensus by Yujin Min, Yun Tang, Hao Chen, Faquan Zhang

“…RANSAC is then used to fit the model parameters of the processed dataset. The optimal parameters for the linear model are obtained after multiple iterative processes. …”
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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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Optimum problem of piezoelectric laminated composite plate using genetic algorithm by Le Kim Ngoc, Tran Ich Thinh

“…A nine-node isoparametric rectangular element with 5 degrees of freedom for the generalized displacements and 2 electrical degrees of freedom at each node is used. Optimization techniques based on genetic algorithm (GAs) are applied in order to maximize the piezoelectric actuator efficiency, improve the structural performance. …”
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Reversible Data Hiding of Digital Image Based on Pixel Combination Algorithm by Jingmin Zhang

“…In order to improve the security effect of image information, this paper studies the reversible information hiding of the digital images combined with the pixel combination algorithm and proposes an improved simulated annealing algorithm using the incremental calculation method of statistical functions. …”
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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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Medium and Long Term Wind Power Prediction Based on Graph Convolutional Network and Wind Velocity Differential Fitting by Zihan CHEN, Wei TENG, Xuefeng XU, Xian DING, Yibing LIU

“…In order to make full use of the prior relationships among data features and improve the prediction accuracy of medium and long term wind power at wind farms, a medium and long term wind power prediction model based on graph convolution neural network (GCN), wind velocity differential fitting (DF), and particle swarm optimization (PSO) is proposed. …”
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Application of evolutionary deep learning algorithm in construction engineering management system by Zhe Yang

“…By comparing with other classic deep learning models, we found that the optimized evolutionary deep learning algorithm model significantly improved the accuracy of classification training and testing. …”
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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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