Modeling of Energy Efficiency for Residential Buildings Using Artificial Neuronal Networks by José Antonio Álvarez, Juan Ramón Rabuñal, Dolores García-Vidaurrázaga, Alberto Alvarellos, Alejandro Pazos

“…To determine this thermal behavior and its representative parameters, we usually have to use destructive auscultation techniques in order to determine the composition of the different layers of the envelope. In this work, we present a nondestructive, fast, and cheap technique based on artificial neural network (ANN) models that predict the energy performance of a house, given some of its characteristics. …”
Get full text

Development of a Model and Designing a System for Water Purification from Hydrocarbons by Igor Meixner, Lovorka Gotal Dmitrovic, Jan Meixner

“…The purification includes extracting and processing the floating hydrocarbon layer, removing the wastewater layer, and extracting soft tar. …”
Get full text

A proposed deep learning model for multichannel ECG noise reduction by Jay Prakash Maurya, Manish Manoria, Sunil Joshi

“…This article proposed a novel deep learning-based solution for multichannel ECG noise reduction, through utilizing the capabilities of fully convolutional neural network along with the Jacobin regularization to ensure confining and preserving local information. Cascaded layered approach was framed in encoder and decoder sections of model where denoising and reconstruction process worked and compared on standard performance parameters with recent denoising deep autoencoders. …”
Get full text

Leveraging transformer models to predict cognitive impairment: accuracy, efficiency, and interpretability by Kai Ma, Junzhi Zhang, Xinhang Huang, Mengyang Wang

“…Conclusion The enhanced Transformer model offers superior accuracy and efficiency in predicting cognitive decline compared to traditional models. …”
Get full text

Thermal Modelling of Metals and Alloys Irradiated by Pulsed Electron Beam: Focus on Rough, Heterogeneous and Multilayered Materials by Andrea Lucchini Huspek, Valentina Mataloni, Ali Mohtashamifar, Luca Paterlini, Massimiliano Bestetti

Get full text

The Impacts of Reservoir Heterogeneities on the CO₂-Enhanced Oil Recovery Process—A Case Study of Daqingzijing Block in Jilin Oilfield, China by Zetang Li, Tianfu Xu, Hailong Tian, Ruosheng Pan

“…Under the homogeneous and heterogeneous porosity and permeability conditions of a reservoir, the displacement characteristics during a CO₂–oil displacement process were analyzed. The layered heterogenous model had the best oil displacement effect, with its oil displacement amount reaching 8.46 × 10⁴ kg, while the homogeneous model and the spatially heterogenous model had lower values; they were 1.51 × 10⁴ and 1.42 × 10⁴, respectively. …”
Get full text

Optimization of Process Parameters for Advanced High-Strength Steel JSC980Y Automotive Part Using Finite Element Simulation and Deep Neural Network by Aekkapon Sunanta, Surasak Suranuntchai

“…From the result, a Deep Neural Network (DNN) with two hidden layers performed with the highest accuracy compared to the other models. …”
Get full text

Research on the DC Ice-Melting Model and Its Influencing Factors on the Overhead Contact Systems of an Electrification Railway by Guosheng Huang, Mingli Wu, Jieyi Liang, Songping Fu, Fuqiang Tian, Xiaojuan Pei, Qiujiang Liu, Teng Li

“…The model covers the physical processes such as convective heat transfer between conductor and air, heat conduction between overhead contact system and ice layer during ice melting, and considers the latent heat factor of ice melting. …”
Get full text

A Color-Based Multispectral Imaging Approach for a Human Detection Camera by Shuji Ono

“…In contrast, we treat clothing detection as a proxy for human detection and construct a lightweight machine learning model (multi-layer perceptron) based on these four wavelengths. …”
Get full text

Experimental modeling of chemical burning of the esophagus using different concentrations of alkali solution by I. Yu. Karpova, P. V. Peretyagin, N. Yu. Orlinskaya, T. E. Potemina, V. V. Parshikov

“…The purpose and objectives of the study: is to create an experimental model of a chemical burn of the esophagus with alkali to study the pathological transformation of the tissues of the upper gastrointestinal tract.Materials and methods. …”
Get full text

Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders by HU Tianzhu, SHEN Yulong, REN Baoquan, HE Ji, LIU Chengliang, LI Hongjun

“…In order to solve the problems of high energy consumption and high reliance on manual annotation data of traditional intelligent attack detection methods in UAV networks, a lightweight UAV network online anomaly detection model based on a double-layer memory-enhanced autoencoder integrated architecture was proposed. …”
Get full text

THE IMPACT OF LIQUEFIED NATURAL GAS COMPOSITION AND TECHNOLOGICAL CHARACTERISTICS OF THE STARTING STORAGE OF THE EQUIPMENT AT THE TIME OF OCCURRENCE OF THE PHENOMENON OF ROLLOVER by R. A. Khuramshina, A. I. Yamalov

“…Using the mathematical program ANSYS, the rollover process in the liquefied natural gas storage was modeled. …”
Get full text

Deriving equivalent symbol-based decision models from feedforward neural networks by Sebastian Seidel, Uwe M. Borghoff

“…The resulting symbolic structures effectively capture FNN decision processes and enable scalability to deeper networks through iterative refinement of subpaths for each hidden layer. …”
Get full text

Comprehensive Performance Assessment of Multi-Neural Ensemble Model for Mortality Prediction in ICU by M. Fathima Begum, Subhashini Narayan

“…The development of models to estimate the mortality rate of critically ill patients in the intensive care unit(ICU) is significantly enhanced by technologies based on artificial intelligence. …”
Get full text

Impedance Model Study of Duct Sound Liner under High Speed Airflow by YAN Meng, FU Liang, ZHA Guotao, HE Caichun

“…In this paper, an acoustic impedance model of double-layer MPP sound liner with two resonant frequencies is derived which is based on the acoustic impedance model of single layer MPP sound liner by the transfer matrix method (TMM). …”
Get full text

Model Constrained by Visual Hierarchy Improves Prediction of Neural Responses to Natural Scenes. by Ján Antolík, Sonja B Hofer, James A Bednar, Thomas D Mrsic-Flogel

“…We assume that a population of V1 neurons shares a common pool of thalamic inputs, and consists of two layers of simple and complex-like V1 neurons. When fit to recordings of a local population of mouse layer 2/3 V1 neurons, our model offers an accurate description of their response to natural images and significant improvement of prediction power over the current state-of-the-art methods. …”
Get full text

Nonlinear prediction model of vehicle network traffic management based on the internet of things by Zhijie Peng, Lili Yin

“…System architecture consists of three spatially separated layers: IoT sensor network for data collection, real-time data processing pipeline and the user interface for visualization. …”
Get full text

Crushing Modeling and Crushing Characterization of Silage <i>Caragana korshinskii Kom.</i> by Wenhang Liu, Zhihong Yu, Aorigele, Qiang Su, Xuejie Ma, Zhixing Liu

“…Currently, conventional crushing equipment generally suffers from uneven particle size distribution, high energy consumption, and low processing efficiency. In this study, a layered aggregate model was constructed using the discrete element method (DEM), and the Hertz–Mindlin with Bonding contact model was employed to characterize the heterogeneous mechanical properties between the epidermis and the core. …”
Get full text

Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models? by P. Sun, P. B. Holden, H. J. B. Birks, H. J. B. Birks

“…To explore the relative merits of these two approaches, we have developed a two-layered machine-learning reconstruction model MEMLM (Multi Ensemble Machine Learning Model). …”
Get full text

Time Series Foundation Model for Improved Transformer Load Forecasting and Overload Detection by Yikai Hou, Chao Ma, Xiang Li, Yinggang Sun, Haining Yu, Zhou Fang

“…Simple load forecasting and overload prediction models, such as LSTM and XGBoost, are unable to handle the increasing amount of data in power systems. …”
Get full text