A Joint Extraction Method of Entity Relations in Aquaculture Long Text Using N-Gram Fusion by BI Tiantian, ZHANG Sijia, SUN Xufei, WANG Shuitao, WANG Yihan, AN Zongshi

“…After that, the features of the long text slice matrix preprocessed by fusion N-Gram algorithm are extracted layer by layer, and the relative and absolute positions of slice matrix are modeled. …”
Get full text

Acoustic impedance inversion via voting stacked regression (VStaR) algorithms by Lutfi Mulyadi Surachman, Sanlin I. Kaka, Abdullatif Al-Shuhail

“…Abstract In this study, we focused on improving acoustic impedance (AI) in seismic exploration. …”
Get full text

Optimization of artificial intelligence in localized big data real-time query processing task scheduling algorithm by Maojin Sun, Luyi Sun

“…This research not only improves the efficiency of task processing, but also provides new ideas for optimizing future scheduling algorithms.…”
Get full text

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. …”
Get full text

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

Get full text

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. …”
Get full text

Multi-Timescale Battery-Charging Optimization for Electric Heavy-Duty Truck Battery-Swapping Stations, Considering Source–Load–Storage Uncertainty by Peijun Shi, Guojian Ni, Rifeng Jin, Haibo Wang, Jinsong Wang, Zhongwei Sun, Guizhi Qiu

“…The key contributions include the following: (1) the development of a battery-charging model for electric heavy-duty truck battery-swapping stations that accounts for the uncertainty in the power output of energy sources, loads, and storage; (2) the proposal of a day-ahead battery-charging optimization algorithm based on intra-day-optimization feedback information-gap decision theory (IGDT), which allows for dynamic adjustment of risk preferences; (3) the proposal of an intra-day battery-charging optimization algorithm based on an improved grasshopper optimization algorithm, which enhances algorithm convergence speed and stability, avoiding local optima. …”
Get full text

Multiscale Feature Modeling and Interpretability Analysis of the SHAP Method for Predicting the Lifespan of Landslide Dams by Zhengze Huang, Yuqi Bai, Hengyu Liu, Yun Lin

“…This study proposes a hybrid CNN–Transformer model optimized using the Improved Black-Winged Kite Algorithm (IBKA) aimed at improving the accuracy of landslide dam lifespan prediction by combining local feature extraction with global dependency modeling. …”
Get full text

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. …”
Get full text

Research on real time measurement model and measurement system for gas concentration in extraction drilling by Dayang Yu, Junhao Zhu, Xing Li, An He, Huaiqian Liu, Changjiang Chen, Yong Liu

Get full text

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. …”
Get full text

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

“…A case study using real-world data validates the proposed method, demonstrating significant improvements in forecasting accuracy.…”
Get full text

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

“…The proposed biased initialization with variable weights improves positional accuracy (72.5%) in relation to methods without dynamic updates. …”
Get full text

Computer graphics processing technology based on GIS model and its application by Quanpeng Ji

Get full text

Optimizing Vehicle Body Cross-Sections Using a Parametric Mathematical Model by Zhaohui Hu, Shuai Mo, Huang Liu, Fuhao Mo

“…In the example of this paper, after the optimization of the established meshless model, the mass of the whole vehicle is reduced by 30%, and the stiffness of the whole vehicle is greater than that of the benchmark vehicle (5128 N/mm, 4386 N/mm), and at the same time, compared with the conceptual design method of the body of CAE technology, the modeling time is greatly reduced, and the computational efficiency of the analytical method is greatly improved compared with the finite element method.…”
Get full text

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). …”
Get full text

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.…”
Get full text

Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

“…Compared with numerical simulation fitting results, the average absolute error in gas production prediction is reduced by 0.24 × 104 m3/d. Therefore, the improved LSTM neural network model demonstrates excellent performance in capacity prediction across different production stages, and the stage-specific productivity variations in infilling wells within middle and deep shale gas reservoirs in South Sichuan. …”
Get full text

Crustal Velocity Models Retrieved from Surface Wave Dispersion Data for Gujarat Region, Western Peninsular India by Vishwa Joshi

“…In each cluster, dispersion data were measured station by station which collectively formed a dispersion data file for a nonlinear inversion through Genetic algorithm. In this way, three crustal velocity models were generated for entire Gujarat. …”
Get full text

RLK-YOLOv8: multi-stage detection of strawberry fruits throughout the full growth cycle in greenhouses based on large kernel convolutions and improved YOLOv8 by Lei He, Lei He, Lei He, Dasheng Wu, Dasheng Wu, Dasheng Wu, Xinyu Zheng, Xinyu Zheng, Xinyu Zheng, Fengya Xu, Fengya Xu, Fengya Xu, Shangqin Lin, Shangqin Lin, Shangqin Lin, Siyang Wang, Siyang Wang, Siyang Wang, Fuchuan Ni, Fang Zheng

“…The proposed algorithm, an enhancement of YOLOv8, leverages the benefits of large kernel convolutions alongside a multi-stage detection approach.MethodRLK-YOLOv8 incorporates several improvements based on the original YOLOv8 model. …”
Get full text