Application of a GA-BP Neural Network in Accurately Characterizing the Diffusion Range of Groundwater Pollutants by Jiayun JI, Xiao XIAO, Pinlu YANG, Yang LIU, Yahong ZHOU

“…The GA-BP neural network, optimized with a Genetic Algorithm, showed the best performance, filling gaps in data and allowing for a more accurate concentration distribution map. …”
Get full text

Enhancing climate action evaluation using artificial neural networks: An analysis of SDG 13 by Cosimo Magazzino, Zakaria Zoundi

“…It examines seven critical 2023 SDG Global Index indexes to model and predict environmental performance. The innovative use of ANNs allows for capturing complex and non-linear interactions among sustainability indicators, surpassing traditional linear models. …”
Get full text

Power quality solutions for rail transport using AI-based unified power quality conditioners by D. K. Nishad, A. N. Tiwari, Saifullah Khalid, Sandeep Gupta

“…Abstract This paper proposes an artificial intelligence-based Unified Power Quality Conditioner (AI-UPQC) and a unique Dynamic K-factor PI (DKPI) algorithm for PI-UPQC to address power quality issues in electrified railway systems. …”
Get full text

H∞ Consensus Design and Online Scheduling for Multiagent Systems with Switching Topologies via Deep Reinforcement Learning by Haoyu Cheng, Ruijia Song, Linpeng Xu, Di Zhang, Shengli Xu

“…Moreover, the online scheduling is formulated as a Markov decision process, and the deep deterministic policy gradient (DDPG) algorithm in the framework of actor-critic is proposed for the compensation of disturbance to explore optimal control policy. …”
Get full text

Rolling window for detecting multiple Chan signatures to diagnose excessive water production by Ahmed MohamedSalih Musa Hamdoon, A. P. Mohammed Abdalla Ayoub Mohammed, A. P. Khaled Abdalla Elraies

“…A successful interactive model with the rolling window feature was developed to track slope changes in Chan signatures, resulting in a 7–10% improvement in pattern detection accuracy compared to static features. …”
Get full text

CareNexus: Integrated solutions for Healthcare Communication by Alexandru Ioan BULZAN

“…A secure authentication based on multiple factors and the use of encryption algorithms, an interface based on different user roles and a prediction system based on model training had been implemented. …”
Get full text

Soft computing approaches of direct torque control for DFIM Motor's by Zakariae Sakhri, El-Houssine Bekkour, Badre Bossoufi, Nicu Bizon, Mishari Metab Almalki, Thamer A.H. Alghamdi, Mohammed Alenezi

Get full text

An Application of Site Selection for Solid Waste Management System Using Neutrosophic Set by A.Savitha Mary, D. Sarukasan, C. Kayelvizhi, L. Jethruth Emelda Mary, F. Josephine Daisy, K. Pitchaimani

“…These factors significantly influence waste collection, processing, and disposal methods. To improve the efficiency and accuracy of waste management site selection, novel computational algorithms have been developed using a proposed distance formula. …”
Get full text

Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation by Liang Liu, Xige Zhang, Jiahui Zhou, Kai Niu, Zixuan Guo, Yawen Zhao, Meng Zhang

“…Additionally, by analyzing the relationship between performance and reliability, we proposed optimization methods to improve reliability while ensuring a high performance was maintained. …”
Get full text

HASSDE-NAS: Heuristic–Adaptive Spectral–Spatial Neural Architecture Search with Dynamic Cell Evolution for Hyperspectral Water Body Identification by Feng Chen, Baishun Su, Zongpu Jia

“…Additionally, a bidirectional fusion alignment cell jointly optimizes spectral and spatial dependencies. A heuristic cell search algorithm optimizes the network architecture through architecture stability, feature diversity, and gradient sensitivity analysis, which improves search efficiency and model robustness. …”
Get full text

Handwritten W-Net for High-Frequency Guided Single-Image Super-Resolution by Xiang Yang, Chen Fang, Xiaolan Xie, Minggang Dong

“…However, existing research has methodological limitations owing to the constraints posed by the model architecture and loss guidance used for optimization. …”
Get full text

Multi-Source Heterogeneous Data-Driven Digital Delivery System for Oil and Gas Surface Engineering by Wei Zhang, Zhixiang Dai, Taiwu Xia, Gangping Chen, Yihua Zhang, Jun Zhou, Cui Liu

“…To address the challenges of data fragmentation, inconsistent standards, and weak interactivity in oil and gas field surface engineering, this study proposes an intelligent delivery system integrated with three-dimensional dynamic modeling. Utilizing a layered collaborative framework, the system combines optimization algorithms and anomaly detection methods during data processing to enhance the relevance and reliability of high-dimensional data. …”
Get full text

Enhanced Position-Aided Beam Prediction Using Real-World Data and Enhanced-Convolutional Neural Networks by Ahmed Abd El Moaty Mohamed Gouda, Ehab K. I. Hamad, Aziza I. Hussein, M. Mourad Mabrook, A. A. Donkol

“…The proposed E-CNN model has been investigated across nine different scenarios from the DeepSense 6G dataset and compared against the conventional algorithms. …”
Get full text

Development of PYMUS+ Code for Quantitative Evaluation of Nuclear Material Accounting (NMA) System by Byung Hee Won, Hee-Sung Shin, Se Hwan Park, Seong-Kyu Ahn

“…It is also important to quantitatively evaluate the performance of NMA system including NRTA from the standpoints of Safeguards and Security by Design (SSBD) prior to construction of nuclear-material-handling facilities. Such evaluation improves safeguards effectiveness and efficiency. Modeling and Simulation (M&S) work is a good way to evaluate performance for various NMA systems and to determine the optimal one among different options. …”
Get full text

Estimation of the Number of Active Sweat Glands Through Discrete Sweat Sensing by Jelte R. Haakma, Elisabetta Peri, Simona Turco, Eduard Pelssers, Jaap M. J. den Toonder, Massimo Mischi

“…Based on our findings, we provide recommendations for optimal device layouts to improve accuracy in estimating active sweat glands. …”
Get full text

Deep learning-based semantic segmentation with novel navigation line extraction for autonomous agricultural robots by Chijioke Leonard Nkwocha, Ning Wang

“…Then, we proposed a novel navigation line extraction algorithm based on the Douglas–Peucker algorithm which uses the output mask from the semantic segmentation to extract the centre navigation line for robot guidance. …”
Get full text

Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…The model’s strong performance and interpretability suggest its potential application in clinical decision support systems to improve diagnostic stewardship, reduce unnecessary cultures, and optimize resource use in suspected BSI cases.…”
Get full text

Method of Diagnostics of Operation Modes of Individual Heat Supply Units, Allowing to Detect Pre-Emergency Situations at an Early Stage by Dvortsevoy A.I., Borush O.V., Khoreva V.A., Yakovina I.N.

“…This was confirmed by the "Elbow Method", which determined the optimal number, which made it possible to significantly improve the forecasting of emergency modes. …”
Get full text

Leveraging Feature Sets and Machine Learning for Enhanced Energy Load Prediction: A Comparative Analysis by Fernando Pedro Silva Almeida, Mauro Castelli, Nadine Côrte-Real

“…This study addresses the gap in existing research by comprehensively analyzing the performance of various machine learning algorithms, including ensemble learning and deep learning models, to improve prediction accuracy. …”
Get full text

Predicting Employee Turnover Using Machine Learning Techniques by Adil Benabou, Fatima Touhami, My Abdelouahed Sabri

“…This study aims to identify the most effective machine learning model for predicting employee attrition, thereby providing organizations with a reliable tool to anticipate turnover and implement proactive retention strategies.Objective: This study aims to address the challenge of employee attrition by applying machine learning techniques to provide predictive insights that can improve retention strategies.Methods: Nine machine learning algorithms are applied to a dataset of 1,470 employee records. …”
Get full text