Modeling of the Power Station Boiler Combustion Efficiency Considering Multiple Work Condition with Feature Selection by TANG Zhenhao, WU Xiaoyan, CAO Shengxian

“…It is difficult for power station boiler efficiency to measure precisely A datadriven modeling method is proposed to establish the boiler combustion efficiency model, according to the machine learning theories A classification and regression trees (CART) algorithm provides correlated variables which have significant relation with the boiler combustion efficiency by data analysis Then, a KNearest Neighbor (KNN) classifies the samples to distinguish the data from different work conditions Based on the classified data, a least square support vector machine (LSSVM) optimized by differential evolution (DE) algorithm is proposed to establish a datadriven model (DDMMF) The parameters of LSSVM are optimized dynamically by DE to improve the model accuracy Finally, the prediction model is corrected dynamically for further improvement of the prediction accuracy The experimental results based on actual production data illustrate that the proposed approach can predict the boiler combustion efficiency accurately, which meets the requirements of boiler control and optimization…”
Get full text

Student employment forecasting model based on random forest and multi-features fusion by Zhenguo Xing, Xiao Wu, Jiangjiang Li

“…Secondly, in order to improve the accuracy of the prediction model, a feature selection model combining principal component analysis and random forest algorithm is used to select the optimal subset from the original features. …”
Get full text

Optimasi Algoritma Support Vector Machine Berbasis Kernel Radial Basis Function (RBF) Menggunakan Metode Particle Swarm Optimization Untuk Analisis Sentimen by Cucun Very Angkoso, Khozainul Asror, Ari Kusumaningsih, Andi Kurniawan Nugroho

“…These reviews are an important source of information for application developers to understand user perceptions, identify problems, and improve service quality. The study investigates the effectiveness of the Particle Swarm Optimization (PSO) method for balanced and unbalanced datasets and how well it improves sentiment analysis accuracy when applied to the Support Vector Machine (SVM) algorithm when using Radial Basis Function (RBF) kernel. …”
Get full text

Hybridized Deep Learning Model for Perfobond Rib Shear Strength Connector Prediction by Jamal Abdulrazzaq Khalaf, Abeer A. Majeed, Mohammed Suleman Aldlemy, Zainab Hasan Ali, Ahmed W. Al Zand, S. Adarsh, Aissa Bouaissi, Mohammed Majeed Hameed, Zaher Mundher Yaseen

“…In the second scenario, a comparable AI model hybridized with genetic algorithm (GA) as a robust bioinspired optimization approach for optimizing the related predictors for the PRSC is proposed. …”
Get full text

Hybrid CNN-Transformer Model for Accurate Impacted Tooth Detection in Panoramic Radiographs by Deniz Bora Küçük, Andaç Imak, Salih Taha Alperen Özçelik, Adalet Çelebi, Muammer Türkoğlu, Abdulkadir Sengur, Deepika Koundal

“…The integration is further optimized with the Weighted Boxes Fusion (WBF) algorithm, where WBF parameters are tuned using Bayesian optimization. …”
Get full text

IWOA-LSTM based intrinsic structural identification of steel fiber concrete by Ping Li, Jie Feng, Shiwei Duan

“…In order to accurately identify the high-temperature constitutive model taking into account the damage evolution, a high-temperature constitutive identification model using the Improved Whale Algorithm (IWOA) optimised Long Short-Term Memory (LSTM) neural network is presented. …”
Get full text

An Enhanced and Lightweight YOLOv8-Based Model for Accurate Rice Pest Detection by Guisuo Liu, Juxing Di, Qing Wang, Yan Zhao, Yang Yang

“…This paper proposes RicePest-YOLO, a practical and generalizable model designed for agricultural pest detection, based on structural optimization and lightweight strategies applied to the YOLOv8 architecture. …”
Get full text

Reaction Behavior and Kinetic Model of Hydroisomerization and Hydroaromatization of Fluid Catalytic Cracking Gasoline by Haijun Zhong, Xiwen Song, Shuai He, Xuerui Zhang, Qingxun Li, Haicheng Xiao, Xiaowei Hu, Yue Wang, Boyan Chen, Wangliang Li

“…These findings provide valuable guidance for the optimization, design, and operation of FCC gasoline hydro-upgrading units, as well as for catalyst development, with the aim of improving process efficiency and fuel quality.…”
Get full text

ASHM-YOLOv9: A Detection Model for Strawberry in Greenhouses at Multiple Stages by Yan Mo, Shaowei Bai, Wei Chen

“…Quick and accurate identification of strawberry plants at different stages can provide important information for automated strawberry planting management. We propose an improved multistage identification model for strawberry based on the YOLOv9 algorithm—the ASHM-YOLOv9 model. …”
Get full text

Research on AIGC Technology Driven Innovation Models and Risk Management in the Financial Sector by Gong Lipeng

“…Finally, this article proposes strategies such as improving the regulatory system, optimizing algorithm transparency, and strengthening data governance to promote the healthy development of AIGC technology in the financial sector.…”
Get full text

Enhanced Superpixel-Guided ResNet Framework with Optimized Deep-Weighted Averaging-Based Feature Fusion for Lung Cancer Detection in Histopathological Images by Karthikeyan Shanmugam, Harikumar Rajaguru

“…Segmentation and feature selection enhance performance, improving diagnostic accuracy. Future work may explore further optimizations and hybrid models.…”
Get full text

MetaStackD A robust meta learning based deep ensemble model for prediction of sensors battery life in IoE environment by D. Gayathri, S. P. Shantharajah

“…Leveraging regression algorithms such as Random Forest, Gradient Boosting, Light Gradient Boosting, Categorical Boosting and Extreme Gradient Boosting, we have modeled the non-linear and temporal dynamics of sensor battery degradation, thereby enabling proactive maintenance strategies, dynamic energy management, and resource allocation. …”
Get full text

Research review of digital modeling technologies with 3D spatial visualization for pipelines by Xin LIU, Shengwen TU, Yanfang HOU, Dong LIN, Jie SHU, Yu TANG

“…MethodsFrom the perspective of software and algorithm characteristics, this paper classifies visual modeling technologies for pipelines into three categories: 3D modeling software, secondary development based on existing components, and underlying development. …”
Get full text

Deep learning-based classification of coronary arteries and left ventricle using multimodal data for autonomous protocol selection or adjustment in angiography by Arpitha Ravi, Philipp Bernhardt, Mathis Hoffmann, Florian Kordon, Siming Bayer, Stephan Achenbach, Andreas Maier

“…This model has the potential to streamline clinical workflows, improve diagnostic accuracy, and enhance safety for both patients and operators.…”
Get full text

FUR-DETR: A Lightweight Detection Model for Fixed-Wing UAV Recovery by Yu Yao, Jun Wu, Yisheng Hao, Zhen Huang, Zixuan Yin, Jiajing Xu, Honglin Chen, Jiahua Pi

“…Therefore, this paper proposes a lightweight visual detection model based on transformer architecture to further optimize computational efficiency. …”
Get full text

Research on Urban Rainfall Runoff Pollution Prediction Model Based on Feature Fusion by Junping Yao, Tianle Sun

“…Meanwhile, the characteristics of rainfall runoff pollution are analyzed from the perspectives of the main sources of rainfall runoff pollution, the types of rainfall runoff pollution, and the initial erosion. The neural network algorithm is optimized and trained according to the sample data to obtain the sample features; the sample data are predicted according to the extracted sample features, and the prediction model is generated by using the feature fusion technology for two groups of prediction results to generate the prediction model and realize the water drop prediction. …”
Get full text

A state-of-the-art novel approach to predict potato crop coefficient (Kc) by integrating advanced machine learning tools by Saad Javed Cheema, Masoud Karbasi, Gurjit S. Randhawa, Suqi Liu, Travis J. Esau, Kuljeet Singh Grewal, Farhat Abbas, Qamar Uz Zaman, Aitazaz A. Farooque

“…A machine learning approach using XGBoost, optimized with the Chaos Game algorithm (CGO-XGBoost), was employed to predict Kc. …”
Get full text

Facilitating real-time LED-based photoacoustic imaging with DenP2P: An optimized conditional generative adversarial deep learning solution by Avijit Paul, Srivalleesha Mallidi

“…Signal quality can be improved by traditional noise removal algorithms, but deep learning models outperform non-learning methods. …”
Get full text

Machine learning-based e-commerce platform repurchase customer prediction model. by Cheng-Ju Liu, Tien-Shou Huang, Ping-Tsan Ho, Ping-Tsan Ho, Jui-Chan Huang, Ching-Tang Hsieh

“…Finally, through two sets of contrast experiments, it is proved that the algorithm selected in this paper can effectively filter the features, which simplifies the complexity of the model to a certain extent and improves the classification accuracy of machine learning. …”
Get full text

Observer-based finite-time event-triggered secure control for fuzzy implicit systems against deception attacks: A single-link flexible joint robotic application by M. Kchaou, L. Ladhar, M. Omri, R. Abbassi, H. Jerbi

“…Furthermore, the Gray Wolf Optimization (GWO) algorithm is employed alongside linear matrix inequality techniques to optimize the gains of both the controller and the observer. …”
Get full text