Financial Distress Warning: An Evaluation System including Ecological Efficiency by Shuang Wu, Hui Zhang, Yuan Tian, Liyuan Shi

“…Based on the data of listed companies, Data Envelopment Analysis (DEA) is applied to evaluating the business efficiency, financial efficiency, financing efficiency, human capital efficiency, and ecological efficiency, and the accuracy of the evaluation system that includes ecological efficiency is measured by artificial neural networks (ANNs). Besides, the logit model is applied to test the results. …”
Get full text

Swarming Computational Procedures for the Coronavirus-Based Mathematical SEIR-NDC Model by Suthep Suantai, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Watcharaporn Cholamjiak

“…The numerical solutions of the SEIR-NDC model are presented by using the computational framework of artificial neural networks (ANNs) together with the swarming optimization procedures aided with the sequential quadratic programming. …”
Get full text

Applying Adaptive Neural Fuzzy Inference System to Improve Concrete Strength Estimation in Ultrasonic Pulse Velocity Tests by Loan T. Q. Ngo, Yu-Ren Wang, Yi-Ming Chen

“…To improve the result of nondestructive testing methods, this research applies artificial neural networks and adaptive neural fuzzy inference system in predicting the concrete strength estimation using nondestructive testing method, the ultrasonic pulse velocity test. …”
Get full text

A Fuzzy Inference System for the Conjunctive Use of Surface and Subsurface Water by Liang-Cheng Chang, Hone-Jay Chu, Yi-Wen Chen

“…Subsequently, water allocations in the surface water system are simulated by using linear programming techniques, and the responses of subsurface water system with respect to pumping are forecasted by using artificial neural networks. The operating rule for the water systems is that the more abundant water system supplies more water. …”
Get full text

A Comprehensive Investigation of Fraud Detection Behavior in Federated Learning by Sun Rui

“…The comparison involves three machine learning models - Artificial Neural Networks (ANN), Random Forest (RF), and Convolutional Neural Networks (CNN) - to assess their efficacy in the FL context. …”
Get full text

Experimental Investigation and Prediction of Compressive Strength of Ultra-High Performance Concrete Containing Supplementary Cementitious Materials by Jisong Zhang, Yinghua Zhao, Haijiang Li

“…Furthermore, to minimise the experimental workload of future studies, a prediction model is developed to predict the compressive strength of the UHPC using artificial neural networks (ANNs). The results indicate that the developed ANN model has high accuracy and can be used for the prediction of the compressive strength of UHPC with these SCMs.…”
Get full text

Forecasting Alisadr Cave Tourism Demand using Combination of Short-term and Long-term Forecasts by Elaheh Malekzadeh Hamedani, Marjan Kaedi, Zahra Zojaji

“…For this purpose, a method based on artificial neural networks is presented, in which the results of linear and non-linear methods and short-term and long-term forecasts are combined. …”
Get full text

Developing multifactorial dementia prediction models using clinical variables from cohorts in the US and Australia by Caitlin A. Finney, David A. Brown, Artur Shvetcov

“…Tree-based machine learning algorithms and artificial neural networks were used. APOE genotype was the best predictor of dementia cases and healthy controls. …”
Get full text

Forecasting the Cell Temperature of PV Modules with an Adaptive System by Giuseppina Ciulla, Valerio Lo Brano, Edoardo Moreci

“…In this work an alternative method, based on the employment of artificial neural networks (ANNs), was proposed to predict the operating temperature of a PV module. …”
Get full text

A novel prediction model of grounding resistance based on long short-term memory by Xinghai Pu, Jing Zhang, Fei Wang, Shuai Xue

“…Furthermore, the study benchmarks the LSTM model’s performance against traditional Artificial Neural Networks, confirming the LSTM’s superior predictive accuracy regarding time-dependent changes in grounding resistance. …”
Get full text

An Improved Direct Torque Control with an Advanced Broken-Bar Fault Diagnosis for Induction Motor Drives by Oualid Aissa, Abderrahim Reffas, Hicham Talhaoui, Djamel Ziane, Abdelhakim Saim

“…This paper presents an advanced strategy combining fuzzy logic and artificial neural networks (ANNs) for direct torque control (DTC) and broken-bar fault diagnosis in induction motors. …”
Get full text

Vortex generators in heat sinks: Design, optimisation, applications and future trends by Mohammad Ismail, Abdullah Masoud Ali, Sol-Carolina Costa Pereira

“…Strategies such as nanofluids, dimples, Response Surface Methodology analysis and Artificial Neural Networks are crucial to improve VG designs to maximise thermal efficiency and minimise pressure loss. …”
Get full text

Machine learning integrated with in vitro experiments for study of drug release from PLGA nanoparticles by Yu Sun, Shuhuai Qin, Yingli Li, Naimul Hasan, Yan Vivian Li, Jiangguo Liu

“…Experimental data collected from about 50 papers are analyzed by machine learning algorithms including linear regression, principal component analysis, Gaussian process regression, and artificial neural networks. The focus is to understand the effect of drug solubility, drug molecular weight, particle size, and pH-value of the release matrix/environment on drug release profiles. …”
Get full text

Multi-GPU Development of a Neural Networks Based Reconstructor for Adaptive Optics by Carlos González-Gutiérrez, María Luisa Sánchez-Rodríguez, José Luis Calvo-Rolle, Francisco Javier de Cos Juez

“…The Complex Atmospheric Reconstructor based on Machine Learning (CARMEN) is an algorithm based on artificial neural networks, designed to compensate the atmospheric turbulence. …”
Get full text

Image Reconstruction for High-Performance Electrical Capacitance Tomography System Using Deep Learning by Yanpeng Zhang, Deyun Chen

“…Therefore, an artificial neural network of the capacitance (ANNoC) system is introduced to estimate capacitance measurements.…”
Get full text

Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral Bridges by Željka Beljkaš, Miloš Knežević, Snežana Rutešić, Nenad Ivanišević

“…The estimation model was developed by using artificial neural networks. The best artificial neural network model showed high accuracy in material consumption estimation expressed as the mean absolute percentage error, 8.56% for concrete consumption estimate and 17.31% for reinforcement consumption estimate.…”
Get full text

Neural network-based robot localization using visual features by Felipe Trujillo-Romero

“…It incorporates an object recognition module that leverages local features and unsupervised artificial neural networks to identify non-dynamic elements in a room and assign them positions. …”
Get full text

Seismic Damage Rapid Assessment of Road Networks considering Individual Road Damage State and Reliability of Road Networks in Emergency Conditions by Jinlong Liu, Hanxi Jia, Junqi Lin, Heng Hu

“…In addition, artificial neural networks are used to evaluate the damage state of an individual road based on the factors that are selected with higher importance. …”
Get full text

3MT Competition (EUSIPCO2024): A peek into the black box: Insights into the functionality of complex-valued neural networks for multichannel speech enhancement by Annika Briegleb

“…Artificial neural networks (ANNs) have become an important part of signal processing research. …”
Get full text

Integrating AI and statistical methods for enhancing civil structures: current trends, practical issues and future direction by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Maisarah Ali

“…This review systematically examines how advanced optimization techniques, including artificial neural networks (ANNs), Design of Experiments (DOE), and fuzzy logic (FL), are transforming civil engineering practices. …”
Get full text