Capuchin search algorithm based task scheduling in cloud computing environment by Sivakumar Ramu, Rameshkumar Ranganathan, Ramakrishnan Ramamoorthy

“…Then, we develop a modified capuchin search (MCS) algorithm for priority based optimal task scheduling which minimize makespan and improve resource utilization. …”
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Qualitative Simulation Algorithm for Resource Scheduling in Enterprise Management Cloud Mode by Jiaohui Yu

“…Aiming at the problem of resource scheduling optimization in enterprise management cloud mode, a customizable fuzzy clustering cloud resource scheduling algorithm based on trust sensitivity is proposed. …”
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Retracted: Research on GNSS-Assisted Low-Cost INS Combined Navigation Moving Base Initial Alignment Technique by Mengbo Sun, Jian Huang, Pengcheng Hu, Xiaohui Song, Zhu Li

“…The measured results show that the proposed method has better alignment accuracy and algorithm robustness than the existing Optimization-based alignment and their improvement algorithms for the moving base of low-cost INS/GNSS combined navigation.…”
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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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Speech emotion recognition algorithm of intelligent robot based on ACO-SVM by Xueliang Kang

“…The experimental results showed that the average recognition rate of the multilevel SVM model optimized by genetic algorithm was as high as 81.26 %, which was 8.78 percentage points higher than that before optimization. …”
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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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Estimating forest aboveground carbon sink based on landsat time series and its response to climate change by Kun Yang, Kai Luo, Jialong Zhang, Bo Qiu, Feiping Wang, Qinglin Xiao, Jun Cao, Yunrun He, Jian Yang

“…In this study, a genetic algorithm (GA) was used to optimize the parameters of random forest (RF) to establish dynamic models to estimate the carbon sink intensity (CSI) of Pinus densata in Shangri-La and analyze the combined effects of multi-climatic factors on CSI. …”
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An improved hybrid approach involving deep learning for urban greening tree species classification with Pléiades Neo 4 imagery—A case study from Nanjing, Eastern China by Min Sun, Stephane G.P. Debulois, Zhengnan Zhang, Xiaolei Cui, Zhili Chen, Mingshi Li

“…Future work will integrate multi-source data, multi-seasonal observations, and adaptive algorithms to further enhance classification performance and improve model robustness across diverse urban environments.…”
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The Hydrodynamic Performance of a Vertical-Axis Hydro Turbine with an Airfoil Designed Based on the Outline of a Sailfish by Aiping Wu, Shiming Wang, Chenglin Ding

“…Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. …”
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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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Object Detection Algorithm Based on Feature Enhancement and Anchor-object Matching by LI Cheng-yan, ZHAO Shuai, CHE Zi-xuan

“…In order to improve the detection accuracy of SSD (Single Shot MultiBox Detector), an A-SSD (Anchor-object SSD) object detection algorithm based on Anchor-object matching is proposed. …”
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A Projection Strategy for Improving the Preconditioner in the LOBPCG by Ma Tailai, Sun Shuli, Zheng Fangyi, Chen Pu

“…This oblique projection technique can find a more accurate approximate solution which minimizes the 2-norm residuals in the search subspace without significantly increasing computational cost, thereby improving the quality of the preconditioner, thus accelerating convergence of the LOBPCG.Numerical experiments show that the projection strategy can improve the LOBPCG algorithm significantly in terms of efficiency and stability.…”
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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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Estimating stomatal conductance of citrus orchard based on UAV multi-modal information in Southwest China by Quanshan Liu, Zongjun Wu, Ningbo Cui, Shunsheng Zheng, Shouzheng Jiang, Zhihui Wang, Daozhi Gong, Yaosheng Wang, Lu Zhao, Renjuan Wei

“…The BKA optimization algorithm effectively enhanced the predictive performance of the KELM and ELM models. …”
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Two-sided Energy Storage Cooperative Scheduling Method for Transmission and Distribution Network Based on Multi-agent Attention-deep Reinforcement Learning by CHEN Shi, ZHU Yujie, LIU Yihong, XU Liuchao, TANG Guodeng

“…The attention mechanism is introduced into the evaluation network to capture interdependencies among agents, enabling potential intent recognition and cooperative behavior perception, thereby improving algorithm convergence. Additionally, noise is added to expand the exploration space, enhancing training stability.Results and Discussions　Using a modified IEEE transmission-distribution joint system as an example, the modeling and solution demonstrate that the multi-agent attention mechanism can strengthen the focus among collaborators, thereby balancing the interests of both parties. …”
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Smart Management of Energy Losses in Distribution Networks Using Deep Neural Networks by Ihor Blinov, Virginijus Radziukynas, Pavlo Shymaniuk, Artur Dyczko, Kinga Stecuła, Viktoriia Sychova, Volodymyr Miroshnyk, Roman Dychkovskyi

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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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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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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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Research on floating object classification algorithm based on convolutional neural network by Jikai Yang, Zihan Li, Ziyan Gu, Wei Li

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