Differential Diagnosis Model of Hypocellular Myelodysplastic Syndrome and Aplastic Anemia Based on the Medical Big Data Platform by Jianhui Wu, Lu Zhang, Sufeng Yin, Haidong Wang, Guoli Wang, Juxiang Yuan

“…Finally, with the support of medical big data, using logistic regression, decision tree, BP neural network, and SVM four classification algorithms, the decision tree algorithm is optimal for the classification of hypo-MDS and AA and analyzes the characteristics of the optimal model misjudgment data.…”
Get full text

Edge computing-based ensemble learning model for health care decision systems by Asir Chandra Shinoo Robert Vincent, Sudhakar Sengan

“…The main drawback of traditional Machine Learning (ML) techniques is their failure to predict reliably. To solve this problem, the proposed model creates an Ensemble Extreme Learning Machine (EN-ELM) algorithm that combines predictors trained on several different data sets. …”
Get full text

Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology by Yurong Zhang, Wenliang Wu, Xianqing Zhou, Jun-Hu Cheng

“…The feature variables were extracted by a variable iterative space shrinkage approach (VISSA), competitive adaptive reweighted sampling (CARS), and a successive projections algorithm (SPA). Partial least squares regression (PLSR), support vector machine (SVM), and extreme learning machine (ELM) models were developed to predict crude fatty acid values of soybeans. …”
Get full text

Thermoluminescence Properties of Plagioclase Mineral and Modelling of TL Glow Curves with Artificial Neural Networks by Mehmet Yüksel, Emre Ünsal

“…In addition, an artificial neural network (ANN) model was developed to predict TL glow curves using three optimization algorithms, including Levenberg–Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG). …”
Get full text

IGWO-MALSTM: An Improved Grey Wolf-Optimized Hybrid LSTM with Multi-Head Attention for Financial Time Series Forecasting by Mingfu Zhu, Haoran Qi, Panke Qin

“…The present study investigates the potential of time series forecasting (TSF) in financial application scenarios, aiming to predict future spreads and inform investment decisions more effectively. …”
Get full text

Intelligent Resource Allocation for Immersive VoD Multimedia in NG-EPON and B5G Converged Access Networks by Razat Kharga, AliAkbar Nikoukar, I-Shyan Hwang

“…The SDN framework manages the entire network, predicts bandwidth requirements, and operates the immersive media dynamic bandwidth allocation (IMS-DBA) algorithm to efficiently allocate bandwidth to IVoD network traffic, ensuring that QoS metrics are met for IM services. …”
Get full text

Exploring alumina nanoparticle deposition in heat exchangers with hexagonal tubes: A hybrid approach integrating numerical simulations and machine learning by Seyed Hamed Godasiaei, Pouyan Talebizadehsardari, Amir Keshmiri

“…The proposed hybrid model demonstrated an impressive predictive accuracy of 97 % using the DNN algorithm, confirming its reliability and robustness for industrial applications.…”
Get full text

The balance between traffic control and economic development in tourist cities under the context of COVID-19: A case study of Xi'an, China. by Wang Xiang, Zezhi Wang, Xin Pan, Xiaobing Liu, Xuedong Yan, Li Chen

“…The results show that the Pearson correlation coefficient between the predicted data of this improved model and the actual data is 0.996, the R-square in the regression analysis is 0.993, with a significance level of below 0.001, suggesting that the predicted data of the model are more accurate. …”
Get full text

Microseismic Signals in Heading Face of Tengdong Coal Mine and Their Application for Rock Burst Monitoring by JianJu Ren, Wenlong Zhang, Zheng Wu, Ji Li, Ying Shen

“…Through trial operation, it is found that large energy (three-channel and four-channel triggering) coal vibration events successfully predicted a rock burst. The MS system of 117 track gateway of Tengdong coal mine should be able to remove the interference signals in real time through the algorithm and take the number of large energy coal vibration signal rather than all coal vibration events as the predictor for rock burst risk monitoring.…”
Get full text

Analysis of a nonsteroidal anti inflammatory drug solubility in green solvent via developing robust models based on machine learning technique by Lijie Jiang, Qi Li, Huiqing Liao, Hourong Liu, Bowen Tan

“…Abstract This study develops and evaluates advanced hybrid machine learning models—ADA-ARD (AdaBoost on ARD Regression), ADA-BRR (AdaBoost on Bayesian Ridge Regression), and ADA-GPR (AdaBoost on Gaussian Process Regression)—optimized via the Black Widow Optimization Algorithm (BWOA) to predict the density of supercritical carbon dioxide (SC-CO2) and the solubility of niflumic acid, critical for pharmaceutical processes. …”
Get full text

Studi Komparasi Naive Bayes, K-Nearest Neighbor, dan Random Forest untuk Prediksi Calon Mahasiswa yang Diterima atau Mundur by Puteri Sejati, Munawar Munawar, Marzuki Pilliang, Habibullah Akbar

“…This study used the classification method to predict prospective students. They are accepted or withdrawn. …”
Get full text

Spectroscopic Quantification of Metallic Element Concentrations in Liquid-Propellant Rocket Exhaust Plumes by Siyang Tan, Song Yan, Xiang Li, Tong Su, Qingchun Lei, Wei Fan

“…This paper develops a hybrid method combining atomic emission spectroscopy (AES) theory with a genetic algorithm (GA) optimized backpropagation (BP) network to quantify the metallic element concentrations in liquid-propellant rocket exhaust plumes. …”
Get full text

Vehicular-Computational Resource Geofencing: Efficient Spatiotemporal Uncertainty Estimation by Ghada Afifi, Bassem Mokhtar

“…We evaluate the efficiency of the proposed resource geofencing algorithm under different realistic operating conditions. …”
Get full text

A hierarchical Bayesian approach for identifying socioeconomic factors influencing self-rated health in Japan by Makoto Nakakita, Teruo Nakatsuma

“…Furthermore, we used the ancillary-sufficiency interweaving strategy (ASIS) algorithm to improve the efficiency of the MCMC method for the panel data logit model. …”
Get full text

Gentle Introduction to Artificial Intelligence for High-School Students Using Scratch by Julian Estevez, Gorka Garate, Manuel Grana

“…In this paper we focus on innovative ways to introduce high school students to the fundamentals and operation of two of the most popular AI algorithms. We describe the elements of a workshop where we provide an academic use-create-modify scaffolding where students work on the Scratch partial coding of the algorithms so they can explore the behavior of the algorithm, gaining understanding of the underlying computational thinking of AI processes. …”
Get full text

Development of Recurrent Neural Networks for Thermal/Electrical Analysis of Non-Residential Buildings Based on Energy Consumptions Data by Elisa Belloni, Flavia Forconi, Gabriele Maria Lozito, Martina Palermo, Michele Quercio, Francesco Riganti Fulginei

“…Simplifying input variables can enhance the applicability of artificial intelligence techniques in predicting energy and thermal performance. This study proposes a neural network-based approach to characterize the thermal–energy relationship in commercial buildings, aiming to provide an efficient and scalable solution for performance prediction. …”
Get full text

Hierarchical Sensing Framework for Polymer Degradation Monitoring: A Physics-Constrained Reinforcement Learning Framework for Programmable Material Discovery by Xiaoyu Hu, Xiuyuan Zhao, Wenhe Liu

“…This paper introduces a novel physics-informed deep learning framework that integrates multi-scale molecular sensing data with reinforcement learning algorithms to enable intelligent characterization and prediction of polymer degradation dynamics. …”
Get full text

Unboxing Tree ensembles for interpretability: A hierarchical visualization tool and a multivariate optimal re-built tree by Giulia Di Teodoro, Marta Monaci, Laura Palagi

“…The interpretability of models has become a crucial issue in Machine Learning because of algorithmic decisions' growing impact on real-world applications. …”
Get full text

Real-Time Anomaly Detection in IoMT Networks Using Stacking Model and a Healthcare- Specific Dataset by Hadjer Goumidi, Samuel Pierre

“…Seven machine learning algorithms, including Random Forest, XGBoost, and Artificial Neural Networks (ANN), were rigorously tested, leading to the development of a novel stacking ensemble model. …”
Get full text

Exploring the binding potential of natural compounds to carbonic anhydrase of cyanobacteria through computer-based simulations by Archana Padhiary, Showkat Ahmad Mir, Aiswarya Pati, Binata Nayak

“…Next, the In-silico methodologies such as molecular docking and molecular dynamic simulations, free energy landscape analysis, hydrogen bond analysis, and binding free energy calculations were performed using various algorithms under virtual physiological conditions to identify potential SAR molecules against carbonic anhydrase. …”
Get full text