Development and validation of a deep reinforcement learning algorithm for auto-delineation of organs at risk in cervical cancer radiotherapy by Li Yucheng, Qiu Lingyun, Shao Kainan, Jia Yongshi, Zhan Wenming, Ding Jieni, Chen Weijun

“…Among these images, 122 CT images were used as a training set for the algorithm training of the DRL model based on the SAM model, and 28 CT images were used for the test set. …”
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An improved MP-NMO correction method based on multiparameter fitting and its application by Xiaohui YANG, Pengfei YU, Jiawei ZHANG

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Fault Diagnosis of Wind Turbine Gearbox Based on Mel Spectrogram and Improved ResNeXt50 Model by Xiaojuan Zhang, Feixiang Jia, Yayu Chen

“…Compared to CNN, ResNet50, ResNeXt50, and CBAM-ResNet50 methods, the CBAM-ResNeXt50-ArcLoss model achieved improvements of 13.3, 3.6, 2.4, and 1.3, respectively. …”
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A Graphite Ore Grade Recognition Method Based on Improved Inception-ResNet-v2 Model by Xueyu Huang, Renjie Pan, Jionghui Wang

“…To address the variability and low timeliness of traditional manual methods and the limited accuracy of deep learning due to image complexity and feature similarity, we propose an improved Inception-ResNet-v2 model for graphite ore grade recognition. …”
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Research on Interval Probability Prediction and Optimization of Vegetation Productivity in Hetao Irrigation District Based on Improved TCLA Model by Jie Ren, Delong Tian, Hexiang Zheng, Guoshuai Wang, Zekun Li

“…Experimental data indicate that the TCLA model improves prediction accuracy by 10.57–26.47% compared to conventional models (Long Short-Term Memory (LSTM), Transformer). …”
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Sentiment Analysis Algorithm Based on Deep Transfer Learning for Multi-Source Data Fusion by Long Qin

“…The experiment outcomes indicate that the artificial bee colony-improved particle swarm optimization algorithm designed in the study has the minimum convergence value under single-peak and multi-peak test functions, with a standard deviation of less than 0.25 and a success rate of 100% in optimization. …”
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Soybean Yield Estimation Using Improved Deep Learning Models With Integrated Multisource and Multitemporal Remote Sensing Data by Jian Li, Junrui Kang, Ji Qi, Jian Lu, Hongkun Fu, Baoqi Liu, Xinglei Lin, Jiawei Zhao, Hengxu Guan, Jing Chang, Zhihan Liu

“…Empirical analyses showed that TransBiHGRU-PSO demonstrated improved estimation capability and generalizability compared to multiple benchmark models. …”
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An integrated model of threshold-based scaling and fractional admission controlling to improve resource utilization efficiency in 5G core networks. by Ly Cuong Hoa, Thanh Chuong Dang, Viet Minh Nhat Vo

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A Bayesian Optimization Approach for Tuning a Grouping Genetic Algorithm for Solving Practically Oriented Pickup and Delivery Problems by Cornelius Rüther, Julia Rieck

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Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

“…In comparison to manually designed HDLM, the proposed approach achieves up to 97.86% model compression with a 0.34% accuracy improvement, while a variant achieves 96.24% compression with a 0.23% accuracy improvement. …”
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Review of optimization modeling and solution of long-distance natural gas pipeline network by Peng ZHOU, Qi WEI

“…In terms of model solutions, multiple heuristic algorithms were summarized. …”
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Accelerated Algorithm based on Modified Z-Buffer for Numerically Simulating the Dynamic Radar Echo from Wind Turbines by Bo Tang, Zhendong Zhu, Zhiyu Shang, Bin Xu, Gang Liu, Cheng Fan

“…The scattering points that make lower contributions to the radar echo are eliminated, and the simulation of one to eight wind turbine radar echoes is performed to demonstrate the speed that the proposed algorithm can improve. The dynamic radar echo of two wind turbines is simulated to verify the accuracy of the accelerated algorithm. …”
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Optimization and Verification of One-dimensional Three-field Model for Transient Analysis of Pressurized Water Reactor by YUAN Leqi1, LI Zanwang1, 2, FAN Jie1, 3, GOU Junli1, SHAN Jianqiang1

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An optimized method for short-term load forecasting based on feature fusion and ConvLSTM-3D neural network by Xiaofeng Yang, Shousheng Zhao, Kangyi Li, Wenjin Chen, Si Zhang, Jingwei Chen

“…Simultaneously, the SHAP algorithm filters weather variables to identify highly correlated weather features. …”
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Inverse Kinematics: Identifying a Functional Model for Closed Trajectories Using a Metaheuristic Approach by Raúl López-Muñoz, Mario A. Lopez-Pacheco, Mario C. Maya-Rodriguez, Eduardo Vega-Alvarado, Leonel G. Corona-Ramírez

“…Additionally, a method to identify a functional model that describes the effector trajectories is introduced using the same optimization technique. …”
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Computer graphics processing technology based on GIS model and its application by Quanpeng Ji

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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…In addition, the second phase is named feature selection, and it is dependent on the Arithmetic Optimization Algorithm (AOA) being used to improve the Growth Optimizer (GO). …”
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Exploration of Machine Learning Models for Prediction of Gene Electrotransfer Treatment Outcomes by Alex Otten, Michael Francis, Anna Bulysheva

“…This study elucidates areas where predictive ML algorithms may ideally inform GET study design to accelerate optimization and improve efficiencies upon the further training of these models.…”
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FAULT DIAGNOSIS OF ROLLING BEARINGS BASED ON SDP AND IMPROVED SAM⁃MobileNetv2 by ZHANG TianYuan, SUN HuEr, ZHU JiYang, ZHAO Yang

“…Traditional fault diagnosis methods for rolling bearings are difficult to accurately and efficiently achieve fault classification.A method of rolling bearing fault classification based on symmetrized dot pattern(SDP)and improved SAM⁃MobileNetv2 was proposed.Firstly,the bearing vibration signal was transformed into two⁃dimensional images with rich characteristic information by SDP algorithm.Secondly,the two⁃dimensional images were fed into the SAM⁃MobileNetv2 network model,which extracted and classified fault feature information.Improved SAM⁃MobileNetv2 networks used the adaptive activation function ACON to replace the ReLU6 activation function in SAM⁃MobileNetv2 to improve model classification performance.Finally,this model was compared with various models.The experimental results show that this model can accurately and efficiently realize the classification of rolling bearing faults,using Case Western Reserve University bearing fault data with an accuracy rate of 99.5%,using the University of Ottawa bearing failure data with an accuracy rate of 97.2%.…”
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Improved FraSegNet-Based Rock Nodule Identification Method and Application by Yanbo Zhang, Guanghan Zhang, Qun Li, Xulong Yao, Hao Zhou

“…The algorithm was validated with the Barton–Bandis model and Hoek–Brown criterion. …”
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