AGV Scheduling and Energy Consumption Optimization in Automated Container Terminals Based on Variable Neighborhood Search Algorithm by Ning Zhao, Rongao Li, Xiaoming Yang

“…The research results show that the model and variable neighborhood search algorithm proposed in this paper have a significant effect on reducing the total energy consumption of AGVs and show good stability and practical application potential.…”
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Optimization of urban green space in Wuhan based on machine learning algorithm from the perspective of healthy city by Xuechun Zhou, Xiaofei Zou, Wenzuixiong Xiong

“…Adopting a healthy city development perspective, the research aims to assess the impact of green space optimization on urban health, economic performance, and social structure.MethodsA multivariable model was constructed using random forest and Support Vector Machine (SVM) algorithms to evaluate the influence of key indicators on urban green space. …”
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Optimal Dynamics Control in Trajectory Tracking of Industrial Robots Based on Adaptive Gaussian Pseudo-Spectral Algorithm by Jing Zhang, Xiaokai Zhu, Te Chen, Guowei Dou

“…The results show that compared with the control variable parameterization method and the traditional Gaussian pseudo-spectral method, the proposed dynamic optimal control method based on an adaptive Gaussian point reconstruction algorithm can effectively improve the solving time and efficiency of constrained optimization problems, thereby further enhancing the dynamic optimization control and trajectory tracking effect of industrial robots.…”
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Using crafted features and polar bear optimization algorithm for short-term electric load forecast system by Mansi Bhatnagar, Gregor Rozinaj, Radoslav Vargic

“…Optimized hyperparameters with PBO effectively decreased RMSE, MAE, and MAPE and improved the model prediction, showcasing the capability of the PBO in hyperparameter tuning for STLF. …”
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Empowering Retail Through Advanced Consumer Product Recognition Using Aquila Optimization Algorithm With Deep Learning by Mohammed Alghamdi, Hanan Abdullah Mengash, Mohammed Aljebreen, Mohammed Maray, Abdulbasit A. Darem, Ahmed S. Salama

“…To achieve this, the ACPR-AOADL model first pre-processes the input data utilizing a Wiener filter (WF) to improve the image quality. …”
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A dual layer secure and energy-efficient model for border surveillance using sea lion inspired strategy in wireless sensor networks by Jayachandran J, Vimaladevi K

“…This paper presents a Dual Layer Sea Lion Optimization algorithm (DL-SLnOA) model, a bio-inspired, clustering and routing that focuses on energy efficiency and security to enhance performance under challenging conditions. …”
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An optimized feature selection using triangle mutation rule and restart strategy in enhanced slime mould algorithm by Ibrahim Musa Conteh, Gibril Njai, Abass Conteh, Qingguo Du

“…This paper proposes an improved feature selection method based on an improved Slime Mould Algorithm (SMA), called the Triangular Mutation Rule Restart Strategy Slime Mould Algorithm (TRSMA), to overcome some of the shortcomings of the SMA, including premature convergence, poor population diversity, and local optima entrapment. …”
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A Temporal Convolutional Network–Bidirectional Long Short-Term Memory (TCN-BiLSTM) Prediction Model for Temporal Faults in Industrial Equipment by Jinyin Bai, Wei Zhu, Shuhong Liu, Chenhao Ye, Peng Zheng, Xiangchen Wang

“…First, preprocessed industrial operation data are fed into the model, and hyperparameter optimization is conducted using the Optuna framework to improve training efficiency and generalization capability. …”
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Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments by Amin Wen, Tonghua Wu, Xiaofan Zhu, Jie Chen, Jianzong Shi, Peiqing Lou, Dong Wang, Xin Ma, Xiaodong Wu

“…The results show that (i) the lowest <i>t</i> value (0°) captured the microtopograhy of the troughs, while the larger <i>L</i> values paired with a DEM resolution of 50 cm diminished the impact of minor noise, improving the accuracy of trough detection; (ii) the optimized Geomorphon model produced trough maps with a high accuracy, achieving mIOU and F1 Scores of 0.89 and 0.90 in PB and 0.84 and 0.87 in WDL, respectively; and (iii) compared with the polygonal boundaries, the trough maps can derive the heterogeneous features to quantify the degradation of PPG. …”
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Development and validation of a multiple myeloma diagnostic model based on systemic lupus erythematosus-associated genes and identification of specific genes by Yuepei Liu, Songshan Liu

“…To establish a diagnostic model for SLE-related MM, we compared 113 combinations of 12 machine learning algorithms, ultimately determining the optimal model. …”
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A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

“…However, for treatment using neural networks based on improved Particle Swarm Optimization (PSO), known as PSONN, the accuracy and performance of current models must be improved. …”
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Dynamic response force control of electrohydraulic servo actuator of active suspension based on intelligent optimization algorithm. by Qinghe Guo, Mengchao Wang, Renjun Liu, Yurong Chen, Shenghuai Wang, Hongxia Wang

“…To address these challenges, a fractional-order PID (FOPID) controller optimization method based on the Multi-Strategy Improved Beluga Whale Optimization (MSIBWO) algorithm is proposed. …”
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Optimization of cable connection layout of unattended AC/DC joint construction station based on INFO algorithm by Long Hu, Zhiwei Yu, Minxin Liang, Xiaoying Chen, Lixia Chen, Guohui Huang

“…Using the INFO algorithm, the feasible solutions of the model are formed into a search domain and solved, and finally the optimal cable connection layout results are output. …”
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Path planning algorithm for WCE with joint energy replenishment and data collection based on multi-objective optimization by Zhenchun WEI, Renhao SUN, Zengwei LYU, Jianghong HAN, Lei SHI, Junyi XU

“…Considering limited energy of the wireless charging equipment (WCE) in wireless rechargeable sensor network,an energy replenishment strategy and a data collection strategy are designed.On the basis of these,a path planning model for WCE with functions of joint energy replenishment and data collection based on multi-objective optimization is constructed with two optimization objectives,maximizing the total energy utility of WCE and minimizing the average delay of data transmission of all the sensor nodes in the network.To deal with it,a multi-objective ant colony optimization algorithm based on elitist strategy was proposed,where the state transition strategy and the pheromone updating strategy were improved.Then,the Pareto set was obtained in terms of this multi-objective optimization problem.The parameter setting of ant colony algorithm’s effects on the proposed algorithm were analyzed under 20 sensor nodes.50 groups of contrastive experiments show that the average number of energy utilization obtained by ES-MOAC algorithm is 4.53% higher than that of NSGA-II algorithm.The average number of average delay of all node data transmission obtained by ES-MOAC algorithm is 5.12% lower than that of NSGA-II algorithm.…”
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Research on optimization design method of ship's living compartment layout based on multi-population genetic algorithm by MA Lin, CHEN Dengkai, SHI Hongqi, LIAO Wenyi

“…It combines emergency evacuation needs to establish a compartment layout optimization model. Additionally, adaptive improvements are made to the genetic operations of the multi-population genetic algorithm, enhancing its applicability to the optimization design of multi-layered ship compartments. …”
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Hybrid optimization of thermally-enhanced Zn-Fe LDH catalysts for fenton-like reactions: Integrating design of experiments with machine learning models for optimisation by Ramadhan Muhammad Naufal, Nawwal Hikmah, Dessy Ariyanti

“…This study presents a novel hybrid modeling framework that combines Response Surface Methodology (RSM) with machine learning (ML) algorithms– Support Vector Regression (SVR) and Gradient Boosting Regression (GBR)– to contribute to the predictive modeling and optimization of thermally-activated ZnFe-LDH based Fenton catalysis. …”
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Critical sliding surface location method for anisotropic slope based on anisotropic yield criterion and optimization algorithm by Zhenfu Zhang, Yongjun Zhang, Sijia Liu, Mingzhong Gao, Fei Liu, Jintao Wang

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Optimizing Solid Rocket Missile Trajectories: A Hybrid Approach Using an Evolutionary Algorithm and Machine Learning by Carlo Ferro, Matteo Cafaro, Paolo Maggiore

“…This paper introduces a novel approach for modeling and optimizing the trajectory and behavior of small solid rocket missiles. …”
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Optimization and Multimachine Learning Algorithms to Predict Nanometal Surface Area Transfer Parameters for Gold and Silver Nanoparticles by Steven M. E. Demers, Christopher Sobecki, Larry Deschaine

“…However, the expansion and testing of this model for nanoparticles of different metal composition is needed to develop a greater variety of nanosensors for medical and commercial applications. …”
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Frequency Response Function-Based Finite Element Model Updating Using Extreme Learning Machine Model by Yu Zhao, Zhenrui Peng

“…To further improve the generalization ability, the input weights and biases of ELM are optimized by Lévy flight trajectory-based whale optimization algorithm (LWOA). …”
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