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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Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…While many methodologies have been developed, cross-validation is perhaps the most widely accepted, often being part of the model development process by optimizing the hyperparameters of predictive algorithms. …”
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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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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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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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Improvement of the technique applied to preserve species and varieties of <i>Fragaria</i> L. in the field genebank at Krymsk Experiment Breeding Station of VIR by V. N. Podorozhniy, N. A. Piyanina

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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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Towards precision agriculture: metaheuristic model compression for enhanced pest recognition by Sana Parez, Norah Saleh Alghamdi, Tahir Mahmood, Waseem Ullah, Muhammad Attique Khan, Taha Houda, Naqqash Dilshad

“…The core of this approach integrates InceptionV3 as a backbone feature extractor to capture rich and discriminative features, enhanced further using a channel attention (CA) mechanism for feature refinement. To reduce model complexity and improve deployment feasibility, a metaheuristic optimization algorithm was incorporated that significantly reduces computational overhead without compromising performance. …”
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Human fall direction recognition in the indoor and outdoor environment using multi self-attention RBnet deep architectures and tree seed optimization by Awais Khan, Jung-Yeon Kim, Chomyong Kim, Muhammad Attique Khan, Hyojin Shin, Jiyoung Woo, Yunyoung Nam

“…To optimize feature selection and improve classification performance while reducing computational costs, we employed the tree seed algorithm on the self-attention features of 7-RBNet and 9-RBNet self-attention models. …”
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Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing by Kun Cui, Ming Chi, Yong Zhao, Zhi-Wei Liu

“…The proposed line search-based global Levenberg&#x2013;Marquardt algorithm addresses the limitations of existing algorithms with necessary and innovative improvements to tackle the challenge of global convergence in nonsmooth optimization problems. …”
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Research on switch migration method based on minimum cost path by Yingxu LAI, Yewei PU, Jing LIU

“…In order to protect the controller,especially the controller in backbone network,from security threats and attacks,improve the security of the software-defined network (SDN) control plane,a switch migration algorithm based on minimum cost path was proposed.A load prediction module was added to the migration model,which executed a controller load prediction algorithm to obtain a load prediction matrix,and then a migration-target controller set was determined according to the load prediction matrix.The improved Dijkstra algorithm was used to determine the minimum cost path.According to the load state of the controller and the traffic priority of the switch to be migrated,the optimal migration switch set was determined.The problem of isolated nodes was solved that may occur during the migration process.The experimental results show that the migration timing of the algorithm is more reasonable,the selection of the migration controller and the target controller is more reasonable,the load balancing of the control plane is realized,the number of migrations and cost are reduced,and the performance of the controller is improved.…”
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AlgaeClass&#x005F;Net: Optimizing Few-Shot Marine Microalgae Classification With Multi-Scale Feature Enhancement Network by Dan Liu, Guihong Yuan, Huachao Tan, Yanbo Jiang, Hai Bi, Yuan Cheng

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Evaluation method of e-government audit information based on big data analysis by Jingui He, Hansi Ya

“…Furthermore, a parallel PSO-RF algorithm combining Particle Swarm Optimization (PSO) and Random Forest (RF) is designed to enhance classification performance and computational efficiency. …”
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A statistical study on factors influencing piezoelectric properties of upside-down composites towards machine learning-driven development for recycling by Sivagnana Sundaram Anandakrishnan, Suhas Yadav, Mohadeseh Tabeshfar, Mikko Nelo, Jani Peräntie, Yang Bai

“…The approach lays down a foundation for scaling up the optimization of the recycled materials by providing training and/or testing datasets for possible machine learning algorithms via potential high-throughput manufacturing routes.…”
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A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…Traditional energy management methods, based on static models or heuristic algorithms, often fail to handle real-time grid dynamics, leading to suboptimal energy distribution, high operational costs, and significant energy wastage. …”
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Power Dispatch Stability Technology Based on Multi-Energy Complementary Alliances by Yiming Zhao, Chengjun Zhang, Changsheng Wan, Dong Du, Jing Huang, Weite Li

“…It aims to enhance dispatch stability and energy utilization through an innovative Distributed Overlapping Coalition Formation (DOCF) model. A distributed algorithm utilizing tabu search is proposed to solve the complex optimization problem in power resource allocation. …”
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