Connectivity-Enhanced 3D Deployment Algorithm for Multiple UAVs in Space–Air–Ground Integrated Network by Shaoxiong Guo, Li Zhou, Shijie Liang, Kuo Cao, Zhiqun Song

“…Finally, a height optimization algorithm is proposed to adjust the height of each UAV, completing the 3D deployment of multiple UAVs. …”
Get full text

LBT-YOLO: A Lightweight Road Targeting Algorithm Based on Task Aligned Dynamic Detection Heads by Pei Tang, Zhenyu Ding, Minnan Jiang, Weikai Xu, Mao Lv

“…After a series of improvements, LBT-YOLO outperforms YOLOv8n and other detection algorithms on the Autonomous Driving BDD100K dataset, with an average accuracy improvement of 2.4% while reducing the number of model parameters by 48.2%.…”
Get full text

Improved Aerial Surface Floating Object Detection and Classification Recognition Algorithm Based on YOLOv8n by Lili Song, Haixin Deng, Jianfeng Han, Xiongwei Gao

“…To address the aforementioned challenges, we proposed an improved YOLOv8-HSH algorithm based on YOLOv8n. The proposed algorithm introduces several key enhancements: (1) an enhanced HorBlock module to facilitate multi-gradient and multi-scale superposition, thereby intensifying critical floating object characteristics; (2) an optimized CBAM attention mechanism to mitigate background noise interference and substantially elevate detection accuracy; (3) the incorporation of a minor target recognition layer to augment the model’s capacity to discern floating objects of differing dimensions across various environments; and (4) the implementation of the WIoU loss function to enhance the model’s convergence rate and regression accuracy. …”
Get full text

Precision forecasting for hybrid energy systems using five deep learning algorithms for meteorological parameter prediction by Ceren Ceylan, Zehra Yumurtacı

“…Using five years of Istanbul meteorological data (2018–2022), optimal algorithms were systematically identified for each parameter through rigorous hyperparameter optimization and cross-validation. …”
Get full text

Evaluation of Thermal Damage Effect of Forest Fire Based on Multispectral Camera Combined with Dual Annealing Algorithm by Pan Pei, Xiaojian Hao, Ziqi Wu, Rui Jia, Shenxiang Feng, Tong Wei, Wenxiang You, Chenyang Xu, Xining Wang, Yuqian Dong

“…This study introduces an innovative approach combining multispectral imaging with a dual annealing constrained optimization algorithm to enable dynamic monitoring of fire temperature distribution. …”
Get full text

Synergetic simplified super-twisting algorithm control for stability enhancement of PV/BESS-based DC microgrid by Naamane Debdouche, Ali Chebabhi, Habib Benbouhenni, Fatma-Zohra Hadjaidji, Z. M. S. Elbarbary, Saad F. Al-Gahtani

“…It ensures the desired voltage level at the common DC bus while tailoring energy allocation to meet load requirements. …”
Get full text

An Efficient Large-Scale 3D Map Stitching Algorithm Using Automatic Overlapping Area Identification by Hsien-I Lin, Muhammad Ahsan Fatwaddin Shodiq, An-Kai Jeng, Chun-Wei Chang

“…The proposed automatic method incorporates the DBSCAN algorithm for clustering, template matching for identifying corresponding clusters, and a binary-search algorithm for parameter optimization. …”
Get full text

Emerging technologies in airway management: a narrative review of intubation robotics and anatomical structure recognition algorithms by Weixiong Chen, Yu Tian, Yingjie Wang, Lili Feng, Mannan Abdul, Shuangshuang Li, Wenxian Li, Yuan Han

Get full text

Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm. by Rudy Clausen, Buyong Ma, Ruth Nussinov, Amarda Shehu

“…In this paper we propose a novel algorithm, SIfTER, which is based instead on stochastic optimization to circumvent the computational challenge of exploring the breadth of a protein's structure space. …”
Get full text

An efficient algorithm for pedestrian fall detection in various image degradation scenarios based on YOLOv8n by Jianhui Xun, Xuefeng Wang, Xiufang Wang, Xiaoliang Fan, Peishuai Yang, Zhifei Zhang

“…Additionally, the Cross Stage Partial Bottleneck with 2 Convolution Block (C2f) was optimized to reduce computational load and parameter count without compromising performance, while the Inner Extended Intersection over Union (Inner-EIoU) loss function was employed to improve bounding box regression accuracy and speed. …”
Get full text

Improved MobileVit deep learning algorithm based on thermal images to identify the water state in cotton by Kaijun Jin, Jihong Zhang, Ningning Liu, Miao Li, Zhanli Ma, Zhenhua Wang, Jinzhu Zhang, Feihu Yin

“…This study introduces a method for identifying the moisture state of cotton using an enhanced MobileVit deep learning algorithm. This approach incorporates the Efficient Channel Attention (ECA) mechanism into the Fusion component of the MobileVit model, optimizes the first convolution in the Fusion component by replacing it with Depthwise Separable Convolution (DsConv), and substitutes the Local representation with the MobileOne block. …”
Get full text

A competitive coevolution-based evolutionary algorithm for the parallel inverse design of multiple soft network materials by Xiao Feng, Yuchen Lai, Xing Yang, Yongbin Yu, Fangling Li, Xiangxiang Wang, Jiacheng Liang, Jingye Cai, Shunze Cao

“…To address these design constraints, we developed an innovatively competitive coevolution-based differential evolution algorithm with multi-population architecture (CCMPDE). …”
Get full text

Novel Approach for Energy Balancing With Intermittent Renewable Energy Source Using Multi-Objective Genetic Algorithm by Ahmad Shah Irshad, M. H. Elkholy, Nahar F. Alshammari, Gul Ahmad Ludin, Tomonobu Senjyu, Gabor Pinter, Alexey Mikhaylov

“…Despite some energy losses, the contribution of each system is derived from the optimization process, where the FPV system contributes approximately 29% of the total energy produced, while the hydroelectric system provides the remaining 71%. …”
Get full text

Development of machine learning algorithms to predict viral load suppression among HIV patients in Conakry (Guinea) by Degninou Yehadji, Degninou Yehadji, Geraldine Gray, Carlos Arias Vicente, Petros Isaakidis, Petros Isaakidis, Abdourahimi Diallo, Saa Andre Kamano, Thierno Saidou Diallo

Get full text

Applying Canny edge detection and Hough transform algorithms to identify irrigation channel boundaries in irrigation districts by LU Hongfei, MAO Hanyu, ZHOU Hao, ZHEN Bo, ZHONG Yao, YANG Bo

“…【Result】Resizing the images to 800 × 400 pixels yielded optimal results, reducing detection time to less than 1.3 seconds while maintaining accurate representation of the channel boundaries. …”
Get full text

A Fine-Grained Aircraft Target Recognition Algorithm for Remote Sensing Images Based on YOLOV8 by Xiao-Nan Jiang, Xiang-Qian Niu, Fan-Lu Wu, Yao Fu, He Bao, Yan-Chao Fan, Yu Zhang, Jun-Yan Pei

“…This article addresses the issues of missed and false detections in existing aircraft target fine-grained recognition algorithms for remote sensing images by proposing an improved algorithm based on YOLOv8, called FD-YOLOv8 (Focus Detail-YOLOv8). …”
Get full text

Hyperspectral Estimation of Chlorophyll Content in Ginseng Fruit Leaves Based on Wavelet Transform and VCPA-GA Algorithm by Guo Jinfeng, Zhang Zhicong, Umut Hasan, Zhou Zhongye, Xu Wenyu, Yusup Ahmat

“…This is because the wavelet transform process has some errors that increase with the number of decomposition layers. (2) The VCPA-GA hybrid variable selection algorithm merges the strengths of the VCPA and GA, addressing the tendency of the VCPA to select fewer variables and overcoming GA's limitations in handling many variables which can lead to overfitting, providing a theoretical basis for estimating ginseng fruit LCC using hyperspectral remote sensing. (3) Among the four machine-learning models, predictions from to 1-2 and 6-7 layers were generally lower than those of the 0 layer, while predictions from the 3–5 layers are higher, showing an overall trend of initial increase followed by a decrease as the number of wavelet decomposition layers increased. (4) Ginseng fruit leaf hyperspectral data processed by the DWT-VCPA-GA algorithm with a 4-layer DWT spectrum yielded the best predictive performance in the BP-AdaBoost regression model, with R2=0.919, mean absolute percentage error = 2.090%, and relative percentage difference = 3.900. (5) After optimizing the BPNN regression model with various algorithms, only some optimized models improved their predictive performance and accuracy to a certain extent, making the choice of the right optimization algorithm crucial for model improvement.…”
Get full text

Artificial Intelligence Dystocia Algorithm (AIDA) as a Decision Support System in Transverse Fetal Head Position by Antonio Malvasi, Lorenzo E. Malgieri, Tommaso Difonzo, Reuven Achiron, Andrea Tinelli, Giorgio Maria Baldini, Lorenzo Vasciaveo, Renata Beck, Ilenia Mappa, Giuseppe Rizzo

“…Additionally, the investigation analyzed the potential role of Artificial Intelligence Dystocia Algorithm (AIDA) as an innovative decision support system in standardizing diagnostic approaches and optimizing clinical decision-making in cases of fetal malposition. …”
Get full text

Intelligent recognition of “geological-engineering” sweet spots in tight sandstone reservoirs - an application to a tight gas reservoir in Ordos Basin, China by Kui Chen, Minghao Zhao, Minghao Zhao, Yansong Feng, Xiaoyan Fu, Yifei Wang, Hui Guo, Jingchen Ding, Qi Chen, Qi Chen

“…This study, based on an integrated geological-engineering perspective and utilizing data analysis and multiple machine learning methods, innovatively proposes a regression prediction model that integrates the Triangulation Topology Aggregation Optimizer (TTAO) algorithm, Random Forest (RF), and Multi-Head Self-Attention Mechanism (MSA), aiming to enhance the accuracy of oil and gas sweet spot identification. …”
Get full text

Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system by Qianwen LI, Jianfeng CHEN, Miao CUI, Guangchi ZHANG

“…A rechargeable unmanned aerial vehicle (UAV) aided wireless sensor network was considered, which consists of multiple ground terminals with a large amount of time-sensitive data to be collected.Due to the limited battery capacity, the UAV cannot collect the data from all terminals through a single flight mission, and it needs to return to the charging pile to replenish its flight energy several times during the whole mission.The optimization of the terminal scheduling, trajectory, flight speed and transmission rate for the UAV was studied to maximize the number of terminals whose data had been collected within the data lifetime limit.Due to the variable coupling and the existence of discrete binary scheduling variables, the considered optimization problem is difficult to solve.To tackle such a difficulty, an efficient algorithm was proposed based on the stochastic optimization and the feature engineering.Specifically, the flight hover communication protocol was introduced to simplify the UAV flight process.And then a terminal scheduling algorithm was innovatively proposed with the influence factor and the stochastic preference, which extracted the features that affect the service time of the UAV, optimized the weights of the features, and further simplified the optimization problem into multiple subproblems.The subproblems were then solved by using the block coordinate descent and successive convex approximation techniques.Simulation results show that the proposed optimization algorithm achieves significant performance gains over several benchmark schemes in the scenarios with different data lifetime requirements and different numbers of ground terminals.…”
Get full text