Sparse support path generation for multi-axis curved layer fused filament fabrication by Tak Yu Lau, Dong He, Yamin Li, Yihe Wang, Danjie Bi, Lulu Huang, Pengcheng Hu, Kai Tang

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YOLOv9-GSSA model for efficient soybean seedlings and weeds detection by Baihe Liang, Liangchen Hu, Guangxing Liu, Peng Hu, Shaosheng Xu, Biao Jie

“…To tackle these issues, we propose a real-time detection algorithm called YOLOv9-GSSA. The improved Mosaic-Dense algorithm increases object density at the model's input layer, enhancing its ability to capture detailed features. …”
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Research on Non-Probabilistic Reliability Partitioning Methods for Large Workspace Robots by Jianping Sun, Weian Yang, Xin Meng, Jun Peng, Zhaoping Tang

“…The method considers the differences in non-probabilistic reliability of robot end positions in different workspace ranges and uses KLFCM clustering combined with a genetic algorithm to perform a two-stage hierarchical partitioning optimization. …”
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A Model for Bus Crew Scheduling Problem with Multiple Duty Types by Mingming Chen, Huimin Niu

“…., day duty) has also been considered. An optimization model is formulated as a 0-1 integer programming problem to improve the efficiency of crew scheduling at the minimum expense of total idle time of crew for a circle bus line. …”
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A Continuous Space Path Planning Method for Unmanned Aerial Vehicle Based on Particle Swarm Optimization-Enhanced Deep Q-Network by Le Han, Hui Zhang, Nan An

“…To address this issue, we introduce the particle swarm optimization (PSO) algorithm into DQN to convert the discrete action space into a continuous one. …”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…This approach resolves the issues of excessive iterations and high computational costs associated with conventional hyperparameter optimization methods, significantly enhancing the model’s predictive performance. …”
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Hybrid chaotic firefly decision making model for Parkinson’s disease diagnosis by Sujata Dash, Ajith Abraham, Ashish Kr Luhach, Jolanta Mizera-Pietraszko, Joel JPC Rodrigues

“…In this article, a novel chaos-based stochastic model is proposed by combining the characteristics of chaotic firefly algorithm with Kernel-based Naïve Bayes (KNB) algorithm for diagnosis of Parkinson’s disease at an early stage. …”
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Fields2Benchmark: An open-source benchmark for coverage path planning methods in agriculture by Gonzalo Mier, Ana María Casado Faulí, João Valente, Sytze de Bruin

“…The agricultural coverage path planning problem focuses on optimizing coverage paths for agricultural operations. …”
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Classification of English Translation Teaching Models based on Multiple Intelligence Theory by Xiaoli Li

“…Moreover, this paper adopts Fisher’s discriminant method and Bayesian discriminant method to classify the English translation teaching samples. In order to improve the discrimination accuracy of the extreme learning machine algorithm, this paper applies the particle swarm optimization extreme learning machine algorithm to the research on the classification of English translation teaching samples and proposes an intelligent English classification teaching model based on the actual situation of English translation teaching. …”
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Exploring dynamical whole-brain models in high-dimensional parameter spaces. by Kevin J Wischnewski, Florian Jarre, Simon B Eickhoff, Oleksandr V Popovych

“…To enable the parameter optimizations for the high-dimensional model fitting to empirical data, we applied two dedicated mathematical optimization algorithms (Bayesian Optimization, Covariance Matrix Adaptation Evolution Strategy). …”
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Research on Credit Default Prediction Model Based on TabNet-Stacking by Shijie Wang, Xueyong Zhang

“…First, use the PyTorch deep learning framework to construct an improved TabNet structure. The multi-population genetic algorithm is used to optimize the Attention Transformer automatic feature selection module. …”
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Fine-Tuned Machine Learning Classifiers for Diagnosing Parkinson’s Disease Using Vocal Characteristics: A Comparative Analysis by Mehmet Meral, Ferdi Ozbilgin, Fatih Durmus

“…Six different machine learning classifiers, namely SVM, k-NN, DT, NN, Ensemble and Stacking models, were developed and optimized via Bayesian Optimization (BO), Grid Search (GS) and Random Search (RS). …”
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Revolutionizing pharmacology: AI-powered approaches in molecular modeling and ADMET prediction by Irfan Pathan, Arif Raza, Adarsh Sahu, Mohit Joshi, Yamini Sahu, Yash Patil, Mohammad Adnan Raza, Ajazuddin

“…The fusion of Artificial intelligence (AI) with computational chemistry has revolutionized drug discovery by enhancing compound optimization, predictive analytics, and molecular modeling. …”
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Application of PSO-Optimized Twin Support Vector Machine in Medium and Long-Term Load Forecasting under the Background of New Normal Economy by Xiang He, Yan Chen, Kai Hu, Lin Wan

“…In order to improve the accuracy of medium and long-term load forecasting in the new normal economy, this paper combines the PSO-optimized twin support vector machine to build a medium and long-term load forecasting model under the background of the new normal economy. …”
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Improving total bone marrow and lymphoid irradiation: feasibility of intensity-modulated proton therapy (IMPT) and dosimetric comparison with helical tomotherapy (HT) by Dayananda Shamurailatpam Sharma, Arjunan Manikandan, Gaganpreet Singh, Sanjib Gayen, Sham Sundar, Aishwarya G, Rangasamy S, Mahammood Suhail, Rajesh S, Ganapathy Krishnan, Revathi Raj, Srinivas Chilukuri, Jose Easow, Rakesh Jalali

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UCSwin‐UNet model for medical image segmentation based on cardiac haemangioma by Jian‐Ting Shi, Gui‐Xu Qu, Zhi‐Jun Li

“…To evaluate the effectiveness of the proposed model, this paper demonstrates its optimality through ablation experiments and comparisons with other mainstream models. …”
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A Study on the Impact of Obstacle Size on Training Models Based on DQN and DDQN by Lu Siyu, Tao Ye, Zeng Junwei, Zuo Qihuan

“…Various parameters such as obstacle size and complexity influence the agent's performance, promoting efficient learning and policy optimization using both DQN and DDQN algorithms under different configurations. …”
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Rescheduling of Multi-Scenario and Multi-Objective Dynamic Changes of Ship Group Construction by ZHANG Aoyuan, HU Xiaofeng, ZHANG Yahui

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Deep reinforcement learning for multi-objective location optimization of onshore wind power stations: a case study of Guangdong Province, China by Yanna Gao, Hong Dong, Liujun Hu, Fanhong Zeng, Yuqun Gao, Zhuonan Huang, Shaohua Wang, Shaohua Wang

“…To solve this model at large scale, a deep reinforcement learning (DRL) algorithm is designed and implemented. …”
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Intelligent building construction site safety inspection model based on YOLOX by Hairong Huang, Lian Yuan, Huiji Wang, Haoran Yuan

“…At the same time, the optimized YOLOX algorithm will be applied to the construction of a model for safety detection in intelligent building construction sites. …”
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