Inverse Kinematics Solution for Manipulators Based on the Artificial Evolved Hummingbird Algorithm by Wang Junru, Qin Pengfei, Sun Guangbin

“…Aiming at the current stage of inverse kinematics solving methods for multi-degree-of-freedom manipulators, most of which have the problems of low solving accuracy and poor generalization, an artificial evolved hummingbird algorithm (AEHA) was proposed for inverse kinematics solving of manipulators. …”
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GravCPA: Controller Placement Algorithm Based on Traffic Gravitation in SDN by Chenhui Wang, Hong Ni, Lei Liu

“…In this article, we take both the average latency and the worst latency between switch and controller into consideration and make a multi-objective optimization model. An improved label propagation algorithm based on traffic gravitation is proposed to solve the subdomain division problem, and a heuristic method is for subdomain controller placement. …”
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Research on floating object classification algorithm based on convolutional neural network by Jikai Yang, Zihan Li, Ziyan Gu, Wei Li

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3D animation design image detail enhancement based on intelligent fuzzy algorithm by Pu Haitao, Pu Yuang

“…The image was divided into superpixel regions using SLIC (Simple Linear Iterative Clustering) algorithm, and local features such as texture, contrast, and edge intensity were extracted; in the SRGAN model, the generator improved image resolution through deep residual blocks and Convolutional Neural Network (CNN), while the discriminator optimized the generated image quality through adversarial training; at the same time, a Fuzzy Logic System (FLS) was constructed to dynamically adjust the image fuzzy degree; channel and spatial attention modules in the generator were integrated to enhance key area details. …”
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A systematic review of deep learning applications in database query execution by Bogdan Milicevic, Zoran Babovic

“…We categorize these approaches into three groups based on how such models are applied: improving performance of index structures and consequently data manipulation algorithms, query optimization tasks, and externally controlling query optimizers through parameter tuning. …”
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A sensor node scheduling algorithm for heterogeneous wireless sensor networks by Zhangquan Wang, Yourong Chen, Banteng Liu, Haibo Yang, Ziyi Su, Yunkai Zhu

“…Regional coverage increment optimization model, arc coverage increment optimization model, and residual energy optimization model are proposed. …”
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Improved RT-DETR Framework for Railway Obstacle Detection by Peng Li, Yanhui Peng, Su-Mei Wang, Cheng Zhong

“…Obstacle intrusion detection in railway systems is a critical technology for ensuring the operational safety of trains. However, existing algorithms face challenges related to insufficient multiscale object detection, high model redundancy, and poor real-time performance. …”
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PV Power Short-Term Forecasting Method Based on VMD-GWO-ELMAN by Na ZHANG, Qiang REN, Guangchen LIU, Liping GUO, Jingyu LI

“…Considering the blindness and randomness of weights and thresholds of traditional Elman neural networks and the fluctuation and nonstationarity of PV output power signal, the paper proposes a short-term prediction model of PV output power based on variational mode decomposition (VMD) and an Elman neural network optimized by grey wolf optimization (GWO) algorithm. …”
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Distributionally Robust Operation for Flexible Distribution Networks Considering Multi-correlation of Renewable Power Generation by Zhiwei LIU, Yue MA, Zhicheng SHA, Yunshu SHAO, Yuanfang NIU, Xiaoming DONG, Chengfu WANG

“…Finally, the column and constraint generation algorithm is adopted to solve the model, and a simulation analysis is conducted using an improved IEEE 33-bus test system as an example, verifying the effectiveness and practicality of the proposed method.…”
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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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An Approach to Trustworthy Article Ranking by NLP and Multi-Layered Analysis and Optimization by Chenhao Li, Jiyin Zhang, Weilin Chen, Xiaogang Ma

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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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A Clustering Approach Using Cooperative Artificial Bee Colony Algorithm by Wenping Zou, Yunlong Zhu, Hanning Chen, Xin Sui

“…This paper presents an extended ABC algorithm, namely, the Cooperative Article Bee Colony (CABC), which significantly improves the original ABC in solving complex optimization problems. …”
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