Robust Analysis and Parameters Identification of the Nonlinear Multistage Dynamical System in Batch Fermentation of Glycerol by Xu Zhang, Xinying Wang, Enmin Feng, Zhilong Xiu

“…Then we establish a parameter identification model and construct the particle swarm optimization algorithm to solve it. …”
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Intelligent design of Fe–Cr–Ni–Al/Ti multi-principal element alloys based on machine learning by Kang Xu, Zhengming Sun, Jian Tu, Wenwang Wu, Huihui Yang

“…Multi-principal element alloys (MPEAs), distinguished by their complex compositions and exceptional mechanical properties, pose significant challenges for conventional predictive approaches in mechanical property optimization. This study proposes an innovative intelligent optimization algorithm (OA) to refine feature selection in machine learning (ML) models, targeting the prediction of ultimate tensile strength (UTS) and fracture elongation (FE) in MPEAs. …”
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Enhanced Convolutional Neural Network for Accurate Crop Recommendation System on Climate Data by Adnan Myasar M., AI_Sadi Hafidh l., Abhilash Pideka Kundil

“…The chosen features are classified and Improved Convolutional Neural Network (ICNN) algorithm predicts crops accurately. …”
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Underwater acoustic channel estimation method based on response generative network by XU Ming, ZHANG Qi

“…The input signal of the generative network was updated by a weight and bias update algorithm based on L1-regularized least squares. Finally, to address the instability of traditional deep learning models for underwater acoustic signals, a decomposed optimization algorithm based on Bures-Wasserstein objective function was proposed. …”
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Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement by Jie Fang, Wenwu Li, Dunchu Chen

“…It replaces the traditional energy storage model with this model and then solves the EV and SOP collaborative planning model using a second-order conical planning algorithm with the objective function of minimizing the annual integrated cost. …”
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A Three-Dimensional Phenotype Extraction Method Based on Point Cloud Segmentation for All-Period Cotton Multiple Organs by Pengyu Chu, Bo Han, Qiang Guo, Yiping Wan, Jingjing Zhang

“…In addition, to address the challenge of accurately segmenting overlapping regions between different cotton organs, we introduced an optimization strategy that combines point distance mapping with curvature-based normal vectors and developed an improved region-growing algorithm to achieve fine segmentation of multiple cotton organs, including leaves, stems, and flower buds. …”
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A Hierarchical Reinforcement Learning Framework for Multi-Agent Cooperative Maneuver Interception in Dynamic Environments by Qinlong Huang, Yasong Luo, Zhong Liu, Jiawei Xia, Ming Chang, Jiaqi Li

“…To address the challenges of real-time decision-making and resource optimization in multi-agent cooperative interception tasks within dynamic environments, this paper proposes a hierarchical framework for reinforcement learning-based interception algorithm (HFRL-IA). …”
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Energy Storage Regulation Method of Base Stations in 5G Integrated Distribution Network Based on Energy Sharing and Trading Coordination by Yanru WANG, Xiyang YIN, Qinghai OU, Wenjie MA, Hui LIU, Zhigang DU

“…Then, with the optimization objectives of promoting energy sharing of 5G base stations, improving operation efficiency of base stations, and participating in peak shaving and valley filling, the optimization problem of energy storage regulation of base stations in a 5G integrated distribution network is constructed, and an energy storage regulation algorithm of 5G base stations based on energy sharing and trading coordination is proposed. …”
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Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction by Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu

“…By leveraging attention parameters, ELPM acquires spatio-temporal adaptive weights, enabling accurate location predictions. We also design an improved service allocation strategy, MESDA, based on the Gray Wolf Optimization (GWO) algorithm. …”
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Adaptive Safe Data Driven Control Strategy for Closed Loop System by Wen Ruchun

“…Finally, some simulation results are given to show our theoretical results on adaptive safe data driven control and its improved switching form. Generally, this new paper extends our previous contributions about data driven control to complete its synthesis research, combining some advanced factors together from both the academic theory and practice, for example, adaptation, safety, optimization theory and algorithm, switching logic together.…”
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Energy-Efficient Resource Allocation for Near-Field MIMO Communication Networks by Tong Lin, Jianyue Zhu, Junfan Zhu, Yaqin Xie, Yao Xu, Xiao Chen

“…A low-complexity optimization algorithm is proposed to realize the joint optimization of power and antenna number. …”
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A Long-Term Shared Autonomous Vehicle System Design Problem considering Relocation and Pricing by Jingjing Tian, Hongfei Jia, Guanfeng Wang, Yu Lin, Ruiyi Wu, Ao Lv

“…Then, we integrate the Particle Swarm Optimization (PSO) algorithm with the optimization solver Gurobi to address the complex problem. …”
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Cost Index Predictions for Construction Engineering Based on LSTM Neural Networks by Jiacheng Dong, Yuan Chen, Gang Guan

“…This research extended current algorithm tools that can be used to forecast cost indexes and evaluated the optimization mechanism of the algorithm in order to improve the efficiency and accuracy of prediction, which have not been explored in current research knowledge.…”
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Outdoor location scheme with fingerprinting based on machine learning of mobile cellular network by Zhichao ZHOU, Yi FENG, Xiaohan XIA, Yuyao FENG, Chao CAI, Jiahui QIU, Lihui YANG, Yunxiao WU

“…The positioning scheme based on mobile cellular network technology is one of the important technical approaches to provide network optimization, emergency rescue, police patrol and location services.The traditional positioning scheme based on cell base station location information has low positioning accuracy and large positioning error, so it cannot meet the requirements of some positioning applications.The scheme based on fingerprint location can greatly improve the location accuracy, save computational cost and enhance the usability based on the coarse location scheme of the cell and become the hotspot of the research.Rasterization and non-rasterization of outdoor fingerprint location scheme based on machine learning were studied and analyzed to meet the business requirements of outdoor fingerprint location.By means of parameter weighting, data fitting and other methods, large-scale fingerprint data were cleaned to improve the effectiveness of data sources.Through the realization of sub-modules such as demarcating research area, rasterizing, constructing fingerprint database, training model, correcting model, non-rasterizing, rough positioning coupling, matching parameter and training parameter, the operation efficiency and positioning accuracy of the algorithm were analyzed and optimized, and the key indexes affecting the algorithm performance were determined.Then, the performance of two fingerprint-based localization schemewas analyzed based on the simulation results.Finally, the typical scenarios of the fingerprint location scheme based on machine learning in practical application were presented.…”
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基于分层模糊优化的湿式多片离合器起步控制研究 by 闫光辉, 关志伟, 童敏勇

“…According to the control theory of wet multi-plate clutch and starting process,taking full account of starting impact and sliding friction works,the starting process is analyzed and the control parameters of each starting process are selected.And then the hierarchical fuzzy optimization control strategy of clutch engagement occupation-empty ratio is proposed,which means the first analysis of starting intention,followed by initial occupation-empty ratio control,and finally to optimize occupation-empty ratio.Based on the control strategy,the control model and algorithm of hierarchical fuzzy optimization is designed.After vehicle simulation and compare with other control strategies,the results show that the strategy can effectively identify the driver’s starting intention,improve the smoothness of the wet clutch and reduce the starting impact and sliding friction works.…”
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Multi-Objective Technology-Based Approach to Home Healthcare Routing Problem Considering Sustainability Aspects by Ahmed Adnan Zaid, Ahmed R. Asaad, Mohammed Othman, Ahmad Haj Mohammad

“…<i>Methods</i>: The model was solved using a metaheuristic algorithm approach via the Ant Colony Optimization algorithm and the Non-Dominated Sorting technique due to the ability of such a combination to work out with dynamic models with uncertainties and multi-objectives. …”
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Multi-UAV Cooperative Air Combat Target Assignment Method Based on VNS-IBPSO in Complex Dynamic Environment by Yiyuan Li, Weiyi Chen, Shukan Liu, Guang Yang, Fan He

“…This method improves upon the limitations of the BPSO algorithm, such as limited local search capability and premature convergence, by combining variable neighborhood search and an improved binary particle swarm optimization algorithm. …”
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Motion State Estimation with Bandwidth Constraints and Mixed Cyber-Attacks for Unmanned Surface Vehicles: A Resilient Set-Membership Filtering Framework by Ziyang Wang, Peng Lou, Yudong Wang, Juan Li, Jiasheng Wang

“…Then, a recursive optimization algorithm is utilized to achieve optimal estimation performance. …”
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SDFA-Net: Synergistic Dynamic Fusion Architecture With Deformable Attention for UAV Small Target Detection by Yunsong Qi, Hengwei Cao

“…Through cross-domain validation of the ALU and HIT-UAV datasets, the ablation experiments and comparative analysis fully validated the effectiveness of the algorithmic improvement, and its detection accuracy and robustness were significantly improved over the baseline model. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…PCA exhibited superior performance in information compression and modeling stability. Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). …”
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