Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…Finally, the integrated prediction combining fluctuation and random terms under condition 5 yielded R2 of 0.87 and 0.93 for the overall prediction at Ankang and Baihe stations, respectively, demonstrating excellent model performance. [Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework by Mengji Yang, Haiqing Zhang, Xi Yu, Aicha Sekhari Seklouli, Abdelaziz Bouras, Yacine Ouzrout

“…Firstly, to reduce the redundancy of the input for the prediction model and the computational time complexity, while enhancing the robustness and stability of the prediction model, nonlinear correlation search algorithm based on time window extending and time window shrinking strategies have been proposed. …”
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Engine Optimization Model for Accurate Prediction of Friction Model in Marine Dual-Fuel Engine by Mina Tadros

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STRUCTURAL DEIGN OF KEY COMPONENTS OF FEEDER BASED ON TOPOLOGY OPTIMIZATION AND MULTI-OBJECTIVE OPTIMIZATION by TANG HuaPing, LI HongXing, JIANG YongZheng, LIU Jie

“…At last,genetic algorithm is used to carry out the multiple object optimization to the response surface model,and the optimal solution set of Pareto is obtained. …”
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Mechanism-learning prediction model for pitting depth of buried pipeline based on HMOGWO-RF by Fulin SONG, Hong ZHAO, Xingyuan MIAO

“…Methods This paper presents a prediction model for the pitting depth of buried pipelines, guided by the corrosion mechanism and combining a Random Forest (RF) algorithm with a Multi-Objective Optimization process. …”
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Reliability Analysis of High-Pressure Tunnel System Under Multiple Failure Modes Based on Improved Sparrow Search Algorithm–Kriging–Monte Carlo Simulation Method by Yingdong Wang, Chen Xing, Leihua Yao

“…Then, the improved sparrow search algorithm (ISSA) is used to optimize the hyper-parameters of the Kriging surrogate model, in order to improve the computational efficiency and accuracy of the reliability analysis model. …”
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Efficiency multi-agent model assisted Moea/D algorithm for optimization design for building taking into account annual energy consumption and annual user discomfort hours by Hua Deng, Kai Zhou

“…Then it introduces a multi-agent model auxiliary mechanism to improve the decomposition based multi-objective evolutionary optimization algorithm, and then solves the multi-objective optimization model for building energy efficiency. …”
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Research on Indoor Object Detection and Scene Recognition Algorithm Based on Apriori Algorithm and Mobile-EFSSD Model by Wenda Zheng, Yibo Ai, Weidong Zhang

“…The specific research contents are as follows: (1) To address complex indoor scenes and occlusion, this paper proposes an improved Mobile-EFSSD object detection algorithm. An optimized MobileNetV3 with ECA attention is used as the backbone. …”
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Autonomous Decision-Making for Air Gaming Based on Position Weight-Based Particle Swarm Optimization Algorithm by Anqi Xu, Hui Li, Yun Hong, Guoji Liu

“…As the complexity of air gaming scenarios continues to escalate, the demands for heightened decision-making efficiency and precision are becoming increasingly stringent. To further improve decision-making efficiency, a particle swarm optimization algorithm based on positional weights (PW-PSO) is proposed. …”
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Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Netwo... by Han Qiu, Rong Hu, Jiaqing Chen, Zihao Yuan

“…Accurate power load forecasting plays an important role in smart grid analysis. To improve the accuracy of forecasting through the three-level “decomposition–optimization–prediction” innovation, this study proposes a prediction model that integrates complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the improved sparrow search algorithm (ISSA), a convolutional neural network (CNN), and bidirectional long short-term memory (BiLSTM). …”
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Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization by Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim

“…A convolutional neural network (CNN) based on the VGG16 architecture is utilized for spatial feature extraction, followed by a bidirectional long short-term memory (BiLSTM) network to capture the temporal dependencies of the scalograms. The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. …”
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Directed energy deposition (DED) of Inconel 718-SS316 L bimetallic structures: Experimental investigations and optimization through artificial humming bird algorithm for improved h... by D. Rajamani, A.R. Vinod, K. Niranjan Reddy, M. Siva Kumar

“…This study reveals the insights into the development of bimetallic structures through DED process with their microstructures, process-property relationship and multi-response optimization through metaheuristic algorithms concerning the improved high strain rate and mechanical characteristics.…”
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Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization by Muhammad Suhail Shaikh, Chang Wang, Senlin Xie, Gengzhong Zheng, Xiaoqing Dong, Shuwei Qiu, Mohd Ashraf Ahmad, Saurav Raj

“…The Grey Wolf Optimizer (GWO) is enhanced using a chaotic map, improving its ability to find the best solutions and achieve faster convergence, resulting in the ICGWO algorithm. …”
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Study on the optimization of duration for repetitive projects considering spatial interference effects in operations by Chunli Zhang, Fan Zhang, Shuwen Yin, Yan Fu, Jun Liu, Peng Duan

“…Furthermore, we propose a model for solving optimal duration based on simulation results, using a genetic algorithm, and analyze the calculation results, speed, and complexity of the genetic algorithm with a heuristic approach. …”
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Improved MobileVit deep learning algorithm based on thermal images to identify the water state in cotton by Kaijun Jin, Jihong Zhang, Ningning Liu, Miao Li, Zhanli Ma, Zhenhua Wang, Jinzhu Zhang, Feihu Yin

“…This study introduces a method for identifying the moisture state of cotton using an enhanced MobileVit deep learning algorithm. This approach incorporates the Efficient Channel Attention (ECA) mechanism into the Fusion component of the MobileVit model, optimizes the first convolution in the Fusion component by replacing it with Depthwise Separable Convolution (DsConv), and substitutes the Local representation with the MobileOne block. …”
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An Environmentally Adaptive CRO-SL Algorithm Based on Dynamic Agents for the Channel Assignment Problem in Wireless Networks by Antonio J. Romero-Barrera, Luis Cruz-Piris, Marino Tejedor-Romero, Jose Manuel Gimenez-Guzman, Ivan Marsa-Maestre

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Comparative Study of Algorithms for the Conversion From Surface Mesh Models to Volume Mesh Models by Youxi Wang, Qi Pang, Meng Li, Yang Liu

“…In addition, the randomness of the HXT algorithm in mesh generation led to variations in results, which requires further optimization to improve the consistency and robustness of the algorithm. …”
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Design of a Novel Fractional Whale Optimization-Enhanced Support Vector Regression (FWOA-SVR) Model for Accurate Solar Energy Forecasting by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Hafeez Anwar, Tariq Ali

“…This study presents a novel Fractional Whale Optimization Algorithm-Enhanced Support Vector Regression (FWOA-SVR) framework for solar energy forecasting, addressing the limitations of traditional SVR in modeling complex relationships within data. …”
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Short-Term Photovoltaic Power Forecasting Based on the VMD-IDBO-DHKELM Model by Shengli Wang, Xiaolong Guo, Tianle Sun, Lihui Xu, Jinfeng Zhu, Zhicai Li, Jinjiang Zhang

“…The model’s hyperparameters are optimized using the IDBO. …”
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Fault diagnosis of HVCB via the subtraction average based optimizer algorithm optimized multi channel CNN-SABO-SVM network by Qingjun Song, Jiuxin Wang, Qinghui Song, Kai Li, Wenchao Hao, Haiyan Jiang

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