Calibration Transfer of Soil Total Carbon and Total Nitrogen between Two Different Types of Soils Based on Visible-Near-Infrared Reflectance Spectroscopy by Xue-Ying Li, Yan Liu, Mei-Rong Lv, Yan Zou, Ping-Ping Fan

“…The former could only be used for correction among instruments, while the latter fundamentally solved the problem of model sharing across different samples.…”
Get full text

Three-dimensional reconstruction and structural surface identification of high steep slopes based on UAV close-range photogrammetry by Linfeng WANG, Hui JIANG, Ning TANG, Xiaoming HUANG, Guojin TAN

“…An adaptive KNN algorithm is introduced to enhance the coplanarity detection passing rate in point clouds, while optimal planar equations are fitted using the least squares method. …”
Get full text

Optimizing ensemble learning for satellite-based multi-hazard monitoring and susceptibility assessment of landslides, land subsidence, floods, and wildfires by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Farman Ali, Biswajeet Pradhan, Soo-Mi Choi

“…To address this gap, this study uses two meta-heuristic algorithms (Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)) to provide an optimized Random Forest (RF) model with better predictive ability. …”
Get full text

A Hardware Accelerator for Real-Time Processing Platforms Used in Synthetic Aperture Radar Target Detection Tasks by Yue Zhang, Yunshan Tang, Yue Cao, Zhongjun Yu

“…The deep learning object detection algorithm has been widely applied in the field of synthetic aperture radar (SAR). …”
Get full text

Integration of Distributed Energy Resources in Unbalanced Networks Using a Generalized Normal Distribution Optimizer by Laura Sofía Avellaneda-Gómez, Brandon Cortés-Caicedo, Oscar Danilo Montoya, Jesús M. López-Lezama

“…A leader–followeroptimization framework is adopted, where the leader stage utilizes the Generalized Normal Distribution Optimization (GNDO) algorithm to generate candidate solutions, while the follower stage conducts power flow calculations through successive approximation to assess the objective value. …”
Get full text

Damage Identification of Railway Bridge KW51 Conditions Using Deep-Learning-Based 1D CNN Model by Ali Al-Ghalib, Sawsan Mahmoud

“…This paper compares the damage identification outcomes of the Machine Learning (ML) and Deep Learning (DL) algorithms. The algorithms in both approaches have employed vibration data from the benchmark railway bridge KW51. …”
Get full text

ADMM-TransNet: ADMM-Based Sparse-View CT Reconstruction Method Combining Convolution and Transformer Network by Sukai Wang, Xueqin Sun, Yu Li, Zhiqing Wei, Lina Guo, Yihong Li, Ping Chen, Xuan Li

“…Compared with other deep learning algorithms, the proposed algorithm has better generalization and higher reconstruction accuracy.…”
Get full text

Novel hybrid arithmetic-equilibrium optimizer as robust tuner for power system stabilizer (PSS) parameters in interconnected electrical power system by Imam Robandi, Mohamad Almas Prakasa, Muhammad Ruswandi Djalal, Shigemasa Takai, Arimbi Kumala Sari, Mochammad Adri Satria Musti

“…A wider-distributed optimal solution and better convergence are also offered by the proposed algorithm. Besides that, the application in the optimal tuning shows that the proposed algorithm can provide the best PSS parameters in different objective functions with better average and standard deviation values. …”
Get full text

Robust Beamforming for Superdirective Antenna Arrays and Experimental Validations by Mengying Gao, Haifan Yin, Liangcheng Han, Jingcheng Xie

“…Numerical and electromagnetic (EM) simulations verify the effectiveness of the DoS and the OC-QCLS algorithm. The improvement in communication performance achieved by the OC-QCLS algorithm is demonstrated through its superior average spectral efficiency. …”
Get full text

Research on Construction and Updating of Global Grid Maps in Mining Truck Autonomous Driving Scenarios by DENG Chao, LONG Teng, YUAN Xiwen, LI Cheng

“…The closest point to the origin in each sector is extracted to define the boundary for a drivable area, while points on a circle with a 30-meter radius serve as the boundary for a scanning area, leading to the construction of partially enclosed drivable and scanning areas using the Bresenham's algorithm. …”
Get full text

Temporal Community Detection and Analysis with Network Embeddings by Limengzi Yuan, Xuanming Zhang, Yuxian Ke, Zhexuan Lu, Xiaoming Li, Changzheng Liu

“…To address these issues, we propose TCDA-NE, a novel TCD algorithm that combines evolutionary clustering with convex non-negative matrix factorization (Convex-NMF). …”
Get full text

Hybrid Metaheuristic Optimized Random Forest Models for Predicting Compressive Strength of Alkali Activated Concrete by Mana Alyami, Muhammad Faisal Javed, Irfan Ullah, Hisham Alabduljabbar, Furqan Ahmad

“…A random forest (RF) model was optimized using six metaheuristic algorithms: differential evolution (DEA), human felicity algorithm (HFA), nuclear reaction optimization (NRO), lightning search algorithm (LSA), Harris hawks optimization (HHO), and tunicate swarm algorithm (TSA). …”
Get full text

Interval-Aware Scheduling of Surveillance Drones: Exact and Heuristic Approaches by Kaito Mori, Hiroki Nishikawa, Hiroyuki Tomiyama

“…In comparison to the Greedy method, the Multi-stage method achieved an average improvement of 37.8% in total flight time, while its algorithm runtime deteriorated by a maximum of 1.26 seconds. …”
Get full text

Intelligent approach to detecting online fraudulent trading with solution for imbalanced data in fintech forensics by Saad M. Darwish, Amr Ibrahim Salama, Adel A. Elzoghabi

“…Traditional machine learning algorithms trained on unbalanced datasets tend to bias towards the majority class (legitimate transactions) and may overlook minority class (fraudulent transactions) patterns. …”
Get full text

FLE-YOLO: A Faster, Lighter, and More Efficient Strategy for Autonomous Tower Crane Hook Detection by Xin Hu, Xiyu Wang, Yashu Chang, Jian Xiao, Hongliang Cheng, Firdaousse Abdelhad

“…To address the complexities of crane hook operating environments, the challenges faced by large-scale object detection algorithms on edge devices, and issues such as frame rate mismatch causing image delays, this paper proposes a faster, lighter, and more efficient object detection algorithm called FLE-YOLO. …”
Get full text

An Enhanced Distribution System Performance with Optimization Techniques for Location of Electrical Vehicle Charging Stations by Sainadh Singh Kshatri, Venkata Anjani Kumar G, Chilakapati Lenin Babu, Palepu Suresh Babu

“…The proposed methodology leverages the Grey Wolf Optimization (GWO) metaheuristic algorithm, enthused by the grey wolves hunting, to identify the most strategic locations for EVCSs. …”
Get full text

Enhancing task execution: a dual-layer approach with multi-queue adaptive priority scheduling by Mansoor Iqbal, Muhammad Umar Shafiq, Shouzab Khan, Obaidullah, Saad Alahmari, Zahid Ullah

“…Various task scheduling algorithms ensure optimized and efficient use of computing resources. …”
Get full text

Real-Time Series Arc Fault Detection and Appliances Classification in AC Networks Based on Competing Convolutional Kernels by Francesco Ferracuti, Riccardo Felicetti, Luca Cavanini, Patrick Schweitzer, Andrea Monteriu

“…Achieved results show a detection accuracy of approximately 99%, with appliance classification performance around 98%, with inference times ranging from 2.8 to 172.0 ms while executing the algorithm on an ARM Cortex-based board.…”
Get full text

Cropping Pattern Classification Using Artificial Neural Networks and Evapotranspiration Estimation in the Eastern Mediterranean Region of Turkey by Mahmut Çetin, Muhammet Said Golpinar, Mehmet Ali Akgül, Hakan Aksu, Omar Alsenjar

“…In line with this, this study aims to classify each crop type using the ANN algorithm and calculate crop evapotranspiration (ETc). …”
Get full text

Forecasting Wind Power Generation Using Artificial Neural Network: “Pawan Danawi”—A Case Study from Sri Lanka by Amila T. Peiris, Jeevani Jayasinghe, Upaka Rathnayake

“…The models were tested with three training algorithms, namely, Levenberg-Marquardt (LM), Scaled Conjugate Gradient (SCG), and Bayesian Regularization (BR) training algorithms. …”
Get full text