Improved PICEA-g-based multi-objective optimization scheduling method for distribution network with large-scale electric vehicles by Meiyi Huo, Songling Pang, Hailong Zhao

“…Abstract Large-scale electric vehicle access to the distribution grid for charging can affect the security and economic operation of the grid. In this paper, an optimal scheduling method for large-scale EV access to the distribution grid based on the improved preference-inspired co-evolutionary algorithm using goal vectors (PICEA-g) is proposed. …”
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Coordinated Optimization Method for Distributed Energy Storage and Dynamic Reconfiguration to Enhance the Economy and Reliability of Distribution Network by Caihong Zhao, Qing Duan, Junda Lu, Haoqing Wang, Guanglin Sha, Jiaoxin Jia, Qi Zhou

“…Subsequently, a hybrid optimization algorithm combining an improved Aquila Optimizer-Second-Order Cone Programming (IAO-SOCP) is proposed to solve the coordinated optimization model. …”
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RSM-YOLOv11: Lightweight Steel Surface Defect Segmentation Algorithm Research Based on YOLOv11 Improvement by Zenghai Shan, Hu Haoyan, Changjian Zhu, Shaowen Du, Hongtao Jing, Wang Haibin

“…To address these issues, this paper proposes an improved YOLOv11 segmentation model, RSM-YOLOv11. The Space-to-Depth Convolution (SPD-Conv) module is introduced to replace the traditional convolutional layer. …”
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Distributed data trading algorithm based on multi-objective utility optimization by Xiaohong HUANG, Yong ZHANG, Desheng SHAN, Yekui QIAN, Lu HAN, Dandan LI, Qun CONG

“…The traditional centralized data trading models are not well applicable to the current intelligent era where everything is interconnected and real-time data is generated, and in order to maximize the use of collected data, it is essential to design an effective data trading framework.Therefore, a distributed data trading framework based on consortium blockchain was proposed, which realized P2P data trading without relying on a third party.Aiming at the problem that existing data trading models only consider the factors of the data itself and ignore the factors related to user tasks, a bi-level multi-objective optimization model was constructed based on multi-dimensional factors, such as data quality, data attributes, attribute relevance and consumer competition, to optimize the utilities of data provider (DP) and data consumer (DC).To solve the above model, an improved multi-objective genetic algorithm-collaborative NSGAII was proposed, calculated by the cooperation of DP, DC and data aggregator (AG).The simulation results show that the collaborative NSGAII achieves better performance in terms of the utilities of DP and DC, thus realizing more effective data trading.…”
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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

“…The concept of explainable artificial intelligence was adopted by incorporating permutation feature importance ranking and Shapley Additive explanations values to identify the feature set that optimized a model's performance while reducing computational complexity. …”
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Integrating Genetic Algorithm and Geographically Weighted Approaches into Machine Learning Improves Soil pH Prediction in China by Wantao Zhang, Jingyi Ji, Binbin Li, Xiao Deng, Mingxiang Xu

“…This study integrates Geographic Weighted Regression (GWR) with three ML models (Random Forest, Cubist, and XGBoost) and designs and develops three geographically weighted machine learning models optimized by Genetic Algorithms to improve the prediction of soil pH values. …”
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Evaluation and Improvement of Ocean Color Algorithms for Chlorophyll-<i>a</i> and Diffuse Attenuation Coefficients in the Arctic Shelf by Yubin Yao, Tao Li, Qing Xu, Xiaogang Xing, Xingyuan Zhu, Yubao Qiu

“…The proposed OCx-AS series for Chl-<i>a</i> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>Κ</mi></mrow><mrow><mi mathvariant="normal">d</mi></mrow></msub></mrow></semantics></math></inline-formula>-DAS models for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>Κ</mi></mrow><mrow><mi mathvariant="normal">d</mi></mrow></msub><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></semantics></math></inline-formula> significantly reduce retrieval errors, achieving RMSE improvements of over 50% relative to global standard algorithms. …”
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The Path Tracking Control of Unmanned Surface Vehicles Based on an Improved Non-Dominated Sorting Genetic Algorithm II-Based Multi-Objective Nonlinear Model Predictive Control Meth... by Yunzhe Guo, Qidan Zhu, Jinyou Mou

“…This paper proposes a multi-objective nonlinear model predictive control (MOMPC) method based on an improved non-dominated sorting genetic algorithm II (NSGAII) for the path tracking problem of unmanned surface vehicles (USVs). …”
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Intelligent Teaching Recommendation Model for Practical Discussion Course of Higher Education Based on Naive Bayes Machine Learning and Improved <i>k</i>-NN Data Mining Algorithm by Xiao Zhou, Ling Guo, Rui Li, Ling Liu, Juan Pan

“…Then, relying on the student grouping, we use the matching features between the students’ interest vector and the practical topic vector to construct an intelligent teaching recommendation model based on an improved <i>k</i>-NN data mining algorithm, in which the optimal complete binary encoding tree for the discussion topic is modeled. …”
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Revalorization of Vinasse as a Farmland Improver Through Multi-Objective Genetic Algorithms: A Circular Economy Approach by Aarón Montiel-Rosales, Nayeli Montalvo-Romero, Gregorio Fernández-Lambert, Horacio Bautista-Santos, Yair Romero-Romero, Juan Manuel Carrión-Delgado

“…This study showed that vinasse improved soil fertility, quality, and health, with an optimal ratio of mixture formed by 40% vinasse and 60% irrigation water. …”
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Improved performance of single sided axial flux for reduction in cogging torque (IMPACT) by Ahmed Dawood, Junaid Ikram, Muhammad Bilal Riaz, Khurram Saleem Alimgeer, Shumaila Javeed

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Detection Model for Cotton Picker Fire Recognition Based on Lightweight Improved YOLOv11 by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song, Yi Wu

“…The improved detection algorithm maintains high accuracy while achieving faster inference speed and fewer model parameters. …”
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Orga-Dete: An Improved Lightweight Deep Learning Model for Lung Organoid Detection and Classification by Xuan Huang, Qin Gao, Hanwen Zhang, Fuhong Min, Dong Li, Gangyin Luo

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Risk Assessment of Heavy Rain Disasters Using an Interpretable Random Forest Algorithm Enhanced by MAML by Yanru Fan, Yi Wang, Wenfang Xie, Bin He

“…Based on disaster system theory, we constructed a heavy rain disaster risk assessment framework from four dimensions. We improved the application of model-agnostic meta-learning (MAML) in hyperparameter optimization for the random forest (RF) algorithm, thereby developing the MAML-RF heavy rain disaster risk assessment model. …”
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Intelligent Modeling and Experimental Investigation of the Collar's Impact on Reducing Scour around the Spur Dike by Hojat Karami, Alireza Rezaei, Amin Atarodi

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Chaotic Mountain Gazelle Optimizer Improved by Multiple Oppositional-Based Learning Variants for Theoretical Thermal Design Optimization of Heat Exchangers Using Nanofluids by Oguz Emrah Turgut, Mustafa Asker, Hayrullah Bilgeran Yesiloz, Hadi Genceli, Mohammad AL-Rawi

“…This theoretical research study proposes a novel hybrid algorithm that integrates an improved quasi-dynamical oppositional learning mutation scheme into the Mountain Gazelle Optimization method, augmented with chaotic sequences, for the thermal and economical design of a shell-and-tube heat exchanger operating with nanofluids. …”
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Trajectory Tracking in Autonomous Driving Based on Improved hp Adaptive Pseudospectral Method by Yingjie Liu, Qianqian Wang

“…At the same time, the tracking error of the lateral distance under the condition of <i>u</i> = 30 km/h is smaller than that of <i>u</i> = 90 km/h. The optimal path tracking control using the improved hp adaptive pseudospectral method has higher accuracy and better control effect compared to traditional control algorithms. …”
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Learning Improvement Heuristics for Multi-Unmanned Aerial Vehicle Task Allocation by Boyang Fan, Yuming Bo, Xiang Wu

“…Specifically, a Transformer-based model is proposed to learn design NeuroSelect Heuristic for DPSO to improve the evolutionary process. …”
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Usage of the optimal fuzzy system models on chloride diffusion of concrete by Shuai Sun

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A new approach for bin packing problem using knowledge reuse and improved heuristic by Jie Fang, Xubing Chen, Yunqing Rao, Yili Peng, kuan Yan

“…The computational experiments show that the proposed algorithm for the bin packing problem using knowledge reuse and improved heuristic (KRIH) has good robustness. …”
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