Optimization Design of Lazy-Wave Dynamic Cable Configuration Based on Machine Learning by Xudong Zhao, Qingfen Ma, Jingru Li, Zhongye Wu, Hui Lu, Yang Xiong

“…To address this challenge, this study proposes a closed-loop optimization framework that couples machine learning with intelligent optimization algorithms for a dynamic cable configuration design. …”
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A Hybrid Three-Staged, Short-Term Wind-Power Prediction Method Based on SDAE-SVR Deep Learning and BA Optimization by Ruiqin Duan, Xiaosheng Peng, Cong Li, Zimin Yang, Yan Jiang, Xiufeng Li, Shuangquan Liu

“…Wind power prediction (WPP) is necessary to the safe operation and economic dispatch of power systems. In order to improve the prediction accuracy of WPP, in this paper we propose a three-step model named SDAE-SVR-BA to be applied in short-term WPP based on stacked-denoising-autoencoder (SDAE) feature processing, bat algorithm (BA) optimization and support vector regression (SVR). …”
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Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms by Dongmei Yu, Zitao Wang, Chao Yue, Jianping Wang

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Fitting membrane resistance along with action potential shape in cardiac myocytes improves convergence: application of a multi-objective parallel genetic algorithm. by Jaspreet Kaur, Anders Nygren, Edward J Vigmond

“…Performance was compared to a genetic algorithm using only AP morphology data. The optimal parameter sets and goodness of fit as computed by the different methods were compared. …”
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Leader-follower Optimal Selection Method for Distributed Control System in Active Distribution Networks by Jian Le, Liangang Zhao, Cao Wang, Qian Zhou, Yang Wang

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Hybrid Machine Learning Model for Predicting Shear Strength of Rock Joints by Daxing Lei, Yaoping Zhang, Zhigang Lu, Hang Lin, Yifan Chen

“…To address these challenges, this study proposes a hybrid ML model that integrates a multilayer perceptron (MLP) with the slime mold algorithm (SMA), termed the SMA-MLP model. …”
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Dynamic weighted ensemble model for predictive optimization in green sand casting: Advancing industry 4.0 manufacturing by Rajesh V․ Rajkolhe, Dr. Sanjay S․ Bhagwat, Dr. Priyanka V․ Deshmukh

“…The gains were statistically significant (p < 0.05) based on paired t-test analysis, confirming that DWE offers superior prediction consistency.The proposed DWE model supports real-time optimization in green sand casting, helping reduce defects and improve quality outcomes. …”
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A CNN-Based Approach for Classical Music Recognition and Style Emotion Classification by Yawen Shi

“…Meanwhile, in this study, a novel loss function has been devised to more effectively assess the model&#x2019;s performance. For searching for optimal performance of the model, a novel optimization algorithm also be proposed to find optimal hyperparameters of loss function. …”
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Optimization of vehicle routing problems combining the demand urgency and road damage for multiple disasters by Ran Li, Xiaofei Ye, Shuyi Pei, Xingchen Yan, Tao Wang, Jun Chen, Pengjun Zheng

“…A set of evaluation index systems for multiple disasters was established to quantify the urgency of demand. The routing optimization model of emergency vehicles for multiple disasters was proposed by combining demand urgency and road damage, and the non-dominated sorting genetic algorithm II (NSGA-II) was used to simulate and validate the model. …”
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A Novel Back Propagation Neural Network Based on the Harris Hawks Optimization Algorithm for the Remaining Useful Life Prediction of Lithium-Ion Batteries by Yuyang Zhou, Zijian Shao, Huanhuan Li, Jing Chen, Haohan Sun, Yaping Wang, Nan Wang, Lei Pei, Zhen Wang, Houzhong Zhang, Chaochun Yuan

“…In order to achieve accurate and reliable RUL prediction, a novel RUL prediction method which employs a back propagation (BP) neural network based on the Harris Hawks optimization (HHO) algorithm is proposed. This method optimizes the BP parameters using the improved HHO algorithm. …”
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Achieving Faster and Smarter Chest X-Ray Classification With Optimized CNNs by Hassen Louati, Ali Louati, Khalid Mansour, Elham Kariri

“…Finally, model compression through filter pruning, driven by evolutionary algorithms, trims redundant parameters to improve computational efficiency while preserving model accuracy. …”
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A hybrid ultra-short-term photovoltaic power prediction framework integrating ant colony optimization for clustering with Bi-GRU by Xinyi Liu, Zitao Wang, Yang Wang, Shanke Liu, Lijun Yu

“…This hybrid framework employs an improved Ant Colony Optimization algorithm fused with K-Means pre-clustering (K-MACO) to perform unsupervised learning on samples within the physical feature space of radiation patterns, humidity, and temperature dynamics, classifying weather scenarios into sunny, cloudy, and rainy types. …”
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Heat Pump Temperature Trajectory Planning Algorithm for Bus Voltage Sag Suppression by Yangyang ZHAO, Lan LIU, Wei ZHAO, Shuang ZENG, Anqi LIANG, Hanqiu WANG, Kai MA

“…The simulation results show that the proposed algorithm can significantly suppress the transient sag of DC bus voltage in the process of heat pump temperature regulation, which are well suited to the smooth control and improving stability of building’s DC microgrid system.…”
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Numerical Modeling on the Damage Behavior of Concrete Subjected to Abrasive Waterjet Cutting by Xueqin Hu, Chao Chen, Gang Wang, Jenisha Singh

“…In this study, a numerical framework based on a coupled Smoothed Particle Hydrodynamics (SPH)–Finite Element Method (FEM) algorithm incorporating the Riedel–Hiermaier–Thoma (RHT) constitutive model is proposed to investigate the damage mechanism of concrete subjected to abrasive waterjet. …”
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Improving crop rotation classification using a random forest model incorporating spatial heterogeneity by Xiaomi Wang, Qi Tang, Kang Yang

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Prediction of Coiled Tubing Erosion Rate Based on Sparrow Search Algorithm Back-Propagation Neural Network Model by Yinping Cao, Fengying Fang, Guowei Wang, Wenyu Zhu, Yijie Hu

“…To accurately predict the erosion rate of coiled tubing, this study studied the influence law of erosion rate through experiments, screened the main influencing factors of erosion rate by grey relational analysis (GRA), and established a back-propagation neural network (BPNN) model optimized by the sparrow search algorithm (SSA) to predict the erosion rate. …”
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Optimizing VGG16 deep learning model with enhanced hunger games search for logo classification by Mohammed Hussain, Thaer Thaher, Mohamed Basel Almourad, Majdi Mafarja

“…In this paper, we propose an optimized deep learning architecture called EHGS-VGG16 designed based on the VGG16 model and boosted by an enhanced Hunger Games Search (EHGS) algorithm for hyperparameter tuning. …”
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Action Recognition, Tracking, and Optimization Analysis of Training Process Based on SVR Model and Multimedia Technology by Xuejiao Zhong

“…In order to explore the action recognition, tracking, and optimization analysis of the training process based on the SVR model and multimedia technology, the author proposes based on the radial basis function model, researching a new surrogate model technology-support vector regression (SVR). …”
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Performance Analysis and Improvement of Machine Learning with Various Feature Selection Methods for EEG-Based Emotion Classification by Sherzod Abdumalikov, Jingeun Kim, Yourim Yoon

“…The following feature selection methods were explored: filter (SelectKBest with analysis of variance (ANOVA) <i>F</i>-test), embedded (least absolute shrinkage and selection operator (LASSO) tuned using Bayesian optimization (BO)), and wrapper (genetic algorithm (GA)) methods. …”
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Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithm by Xiaole Tang, Hao Lu, Yanting Kang, Wenjun Zhao

“…The substantial volatility of photovoltaic (PV) power output presents challenges to the stable operation of power grids. To improve the accuracy and stability of PV power prediction, this study proposes a PV power prediction system based on a dual-layer decomposition strategy and a dynamic grouping multi-objective Coati optimization algorithm (DGMOCOA). …”
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