PID Control of Multisources Complex Excitations Active Vibration Isolation System: An Improved Particle Swarm Optimization Algorithm by Song Chunsheng, Jiang Youliang, Zhang Jinguang

“…Furthermore, this paper also sets up the acceleration feedback-based PID control model for multisources complex excitations active vibration isolation system, proposes an improved particle swarm optimization (PSO) algorithm of dynamic inertia weight factors used to optimize parameters of the built PID control model, and conducts simulation analysis. …”
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An integrated vehicle routing model to optimize agricultural products distribution in retail chains by W. Madushan Fernando, Amila Thibbotuwawa, H. Niles Perera, Peter Nielsen, Deniz Kenan Kilic

“…Numerical experiments showcase the efficiency of the proposed algorithm in solving real-world VRP problems. Moreover, the proposed VRP model achieves a 19% reduction in daily distribution costs, including a 24% saving in fuel costs. …”
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Energy Management of Electric–Hydrogen Coupled Integrated Energy System Based on Improved Proximal Policy Optimization Algorithm by Jingbo Zhao, Zhengping Gao, Zhe Chen

“…However, the inherent uncertainties of renewable energy sources present significant challenges to optimal energy management in the EHCS. To address these challenges, this paper proposes an energy management method for the EHCS based on an improved proximal policy optimization (IPPO) algorithm. …”
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Modeling of 3 SAT discrete Hopfield neural network optimization using genetic algorithm optimized K-modes clustering by Xiaojun Xie, Saratha Sathasivam, Hong Ma

“…Subsequently, the paper presented a DHNN-3SAT model optimized by genetic algorithms combined with K-modes clustering. …”
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Improved Monthly Runoff Prediction of OSELM Based on Secondary Decomposition Technique and Optimization of Ten "Bird" Swarm Algorithms by DENG Zhiyu, CUI Dongwen

“…To improve the accuracy of monthly runoff time series prediction and enhance the performance of online sequential extreme learning machine (OSELM) prediction, ten "bird" swarm algorithms were compared and validated for optimization, including satin bowerbird optimizer (SBO)/Harris hawks optimization (HHO)/seagull optimization algorithm (SOA)/African vultures optimization algorithm (AVOA)/coot optimization algorithm (COOT)/pelican optimization algorithm (POA)/eagle perching optimization (EPO)/osprey optimization algorithm (OOA). …”
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Prediction Model for Compaction Quality of Earth-Rock Dams Based on IFA-RF Model by Weiwei Lin, Yuling Yan, Pu Xu, Xiao Zhang, Yichuan Zhong

“…The method utilizes a dynamic inertia weight, an adaptive factor, and a differential evolution strategy to enhance the search capability of the firefly algorithm. Furthermore, the random forest (RF) algorithm’s <i>Ntree</i> and <i>Mtry</i> parameters are adaptively optimized through the improved firefly algorithm (IFA) to develop a dam compaction quality prediction model. …”
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Knowledge reasoning and strategy optimization for ship operation and maintenance based on digital twin and improved KD tree algorithm by Liyao ZHANG, Ziqian GUO, Ruifang LI, Xun YE, Tao MA

“…Based on the database, a method for ship O&M knowledge reasoning and strategy generation using an improved KD tree algorithm is proposed. Neighboring cases are weighted using Gaussian distance weighting, and the whale optimization algorithm (WOA) is used to optimize the characteristic attributes of ship equipment to achieve accurate knowledge reasoning. …”
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Study of Impact of Moment Information in Demand Forecasting on Distributionally Robust Fulfillment Rate Improvement Algorithm by Haodong Feng

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SCSO: snake optimization with sine-cosine algorithm for parameter extraction of solar photovoltaic models by Qingrui Li, Yongquan Zhou, Qifang Luo

“…The proposed algorithm incorporates three key improvements: (1) integration of the Sine–Cosine Algorithm to enhance the bio-inspired Snake Optimization, balancing exploration and exploitation; (2)The parameters C 1 and C 2 are adaptively adjusted, and the Newton–Raphson method is introduced to accelerate the algorithm’s convergence speed which accelerates convergence; and (3) application of a lens imaging reverse learning strategy to improve exploration capabilities and population diversity, preventing the algorithm from becoming trapped in local optima. …”
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Optimization of Rendering Parameters of Cesium 3DTiles Model Based on Differential Evolution Algorithm by Doujun Zhang, Yong Wu, Youcong Ni, Tinghuang Zhang, Chenxiang Gao

“…In this paper, we proposed a multi-strategy probabilistic discrete differential evolution algorithm (MSPDDE) for finding the optimal values of the rendering parameters of Cesium 3DTiles model, which increases the search space and improves the convergence speed by introducing multiple mutation strategies. …”
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Territorial Space Optimization Method Based on Multi-Objective Genetic Algorithm and FLUS Model by Lin Ge

“…The innovation of the research lies in the optimization of the multi-objective genetic algorithm by improving the crossover and mutation process of genetic operators, enhancing the adaptability of the algorithm in dynamic environments, and improving the prediction accuracy of the spatial quantity structure of the national territory. …”
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Pedestrian Re-Recognition Algorithm Based on Optimization Deep Learning-Sequence Memory Model by Feng-Ping An

“…Based on the above explanation, this paper proposes a pedestrian re-recognition algorithm based on an optimized LSTM deep learning-sequence memory learning model. …”
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Research on the Development Model of Rural Tourism Based on Multiobjective Planning and Intelligent Optimization Algorithm by Lu Yang, Xiaoying Dong

“…In order to improve the effect of rural tourism development, this study combines multiobjective planning and intelligent optimization algorithms to analyze the development mode of rural tourism and further deals with the problem of multisensor target tracking under unknown input interference conditions by designing a tourism network consensus algorithm. …”
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Deep learning for algorithmic trading: A systematic review of predictive models and optimization strategies by MD Shahriar Mahmud Bhuiyan, MD AL Rafi, Gourab Nicholas Rodrigues, MD Nazmul Hossain Mir, Adit Ishraq, M.F. Mridha, Jungpil Shin

“…This systematic literature review explores recent advancements in the application of DL algorithms to algorithmic trading with a focus on optimizing financial market predictions. …”
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Research on the optimization of mortar mix proportion based on neural network models and genetic algorithm by Chunyu Jiang

“…The genetic algorithm is then applied to optimize the model’s predictions, yielding the optimal mix design. …”
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Model Optimization for High-Yield Biocrude in Co-Hydrothermal Liquefaction of Municipal Sludge by Botian HAO, Yunfei DIAO, Ya WEI, Donghai XU

“…After training with the Levenberg-Marquardt algorithm, the model′s R2 significantly improved to 0.9989, demonstrating the superiority of neural networks in modeling nonlinear complex systems. …”
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An Innovative Inversion Method of Potato Canopy Chlorophyll Content Based on the AFFS Algorithm and the CDE-EHO-GBM Model by Xiaofei Yang, Qiao Li, Honghui Li, Hao Zhou, Jinyan Zhang, Xueliang Fu

“…Gradient Boosting Machine (GBM) model parameters were optimized using a hybrid strategy improved Elephant Herd Optimization (EHO) algorithm (CDE-EHO) that combines Differential Evolution (DE) and Cauchy Mutation (CM). …”
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An Operation Optimization Strategy of the Combined Power Generation System with Wind Power &amp; Pumped Storage Based on Improved Whale Algorithm by LI Kecheng, YANG Ning

“…In order to solve the model, based on the basic whale optimization algorithm, a multi-objective whale optimization algorithm is developed by adding external population and leader selection mechanism, and the control parameter in the algorithm is improved to obtain an improved multi-objective whale optimization algorithm. …”
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Performance and improvement of deep learning algorithms based on LSTM in traffic flow prediction by Wei Xu, Eric Blancaflor, Mideth Abisado

“…This paper introduces an improved LSTM (Long Short-Term Memory) algorithm and sliding window technology to improve the accuracy and stability of traffic flow prediction. …”
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Research on pose estimation algorithm of non-cooperative target tracked vehicles based on PnP model by Zhigang Ren, Xinagjun Tang, Guoquan Ren, Dinghai Wu

“…Finally, the pose equation is solved by finding the local minimum of the cost function through algebraic optimization, thus avoiding convergence issues in iterative optimization. …”
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