Estimation of Bearing Capacity of Strip Footing Rested on Bilayered Soil Profile Using FEM-AI-Coupled Techniques by Ahmed M. Ebid, Kennedy C. Onyelowe, M. Salah

“…Multiple numerical data were generated for the case under study and artificial intelligence (AI)-based techniques; generalized reduced gradient (GRG), genetic programming (GP), artificial neural network (ANN), and evolutionary polynomial regression (EPR) were used to predict the UBC. …”
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Automation of image processing through ML algorithms of GRASS GIS using embedded Scikit-Learn library of Python by Polina Lemenkova

“…Image processing using Machine Learning (ML) and Artificial Neural Network (ANN) methods was investigated by employing the algorithms of Geographic Resources Analysis Support System (GRASS) Geographic Information System GIS with embedded Scikit-Learn library of Python language. …”
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Development and external validation of machine learning-based models to predict patients with cellulitis developing sepsis during hospitalisation by Li Hu, Xilingyuan Chen, Rentao Yu

“…In external validation, the AUC of the artificial neural network (ANN) model was the highest, 0.830, while the AUC of the logistic regression (LR) model was the lowest, 0.792. …”
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Improving Deep Learning Forecasting Model Based on LSTM for Türkiye’s Hydro-Electricity Generation by Mehmet Bulut

“…LSTM (Long Short-Term Memory) plays an important role in hydropower forecasting, as it is a special artificial neural network designed to model complex relationships on time series data, which is affected by various meteorological factors such as precipitation, temperature, and hydrological data such as water level, such as hydroelectric power production. …”
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Exploration of Arrhenius activation energy and thermal radiation on MHD double-diffusive convection of ternary hybrid nanofluid flow over a vertical annulus with discrete heating by Shilpa B, V. Leela, Irfan Anjum Badruddin, Sarfaraz Kamangar, P. Ganesan, Abdul Azeem Khan

“…Also, the heat and mass transfer characteristics are forecasted and analyzed by considering the Levenberg–Marquardt backpropagating artificial neural network technique.…”
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Assessment of a Neural-Network-Based Optimization Tool: A Low Specific-Speed Impeller Application by Matteo Checcucci, Federica Sazzini, Michele Marconcini, Andrea Arnone, Mario Coneri, Luigi De Franco, Matteo Toselli

“…The design procedure relies on a modern optimization technique such as an Artificial-Neural-Network-based approach (ANN). The impeller geometry is parameterized in order to allow geometrical variations over a large design space. …”
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Evaluating the predictive potential of RSM and ANN models in treatment of greywater-syrup mixture using Ekowe clay-PEM microbial fuel cell by Livinus A. Obasi, Cornelius O. Nevo

“… This study provides a comparative evaluation of the ability of response surface methodology (RSM) and artificial neural network (ANN) to predict the performance of microbial fuel cell (MFC) driven by greywater-syrup substrate system as anolyte with respect to power generation and wastewater treatment. …”
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Spatial Downscaling of Daily Temperature Minima Using Machine Learning Methods and Application to Frost Forecasting in Two Alpine Valleys by Sudheer Bhakare, Michael Matiu, Alice Crespi, Dino Zardi

“…This study examines the performance of three machine learning models—namely, Artificial Neural Network (ANN), Random Forest (RF), and Convolutional Neural Network (CNN)—for spatial downscaling of seasonal forecasts of daily minimum temperature from 12 km to 250 m horizontal resolution. …”
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Prediction of BlastInduced Ground Vibration (BIGV) of Metro Construction Using Difference Evolution AlgorithmOptimized Gaussian Process (DE-GP) by Tengfei Jiang, Annan Jiang, Shuai Zheng, Mengfei Xu

“…The proposed model is compared with the empirical formulas, least square support vector machine (LSSVM), artificial neural network (ANN), and GP model, and its prediction performance is evaluated by statistical indicators such as root mean square error (RMSE). …”
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Hybrid Wind Speed Forecasting Model Study Based on SSA and Intelligent Optimized Algorithm by Wenyu Zhang, Zhongyue Su, Hongli Zhang, Yanru Zhao, Zhiyuan Zhao

“…The present study investigated singular spectrum analysis (SSA) with a reduced parameter algorithm in three time series models, the autoregressive integrated moving average (ARIMA) model, the support vector machine (SVM) model, and the artificial neural network (ANN) model, to forecast the wind speed in Shandong province, China. …”
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Multiobjective Neuro-Fuzzy Controller Design and Selection of Filter Parameters of UPQC Using Predator Prey Firefly and Enhanced Harmony Search Optimization by Koganti Srilakshmi, Gummadi Srinivasa Rao, Katragadda Swarnasri, Sai Ram Inkollu, Krishnaveni Kondreddi, Praveen Kumar Balachandran, C. Dhanamjayulu, Baseem Khan

“…The reference signals for voltage source converters of UPQC are produced by the Levenberg–Marquardt back propagation (LMBP) trained artificial neural network control (ANNC). This method removes the necessity for conventional dq0, abc complex shifting. …”
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Multiobjective Optimization of Surface Roughness and Tool Wear in High-Speed Milling of AA6061 by Machine Learning and NSGA-II by Anh-Tu Nguyen, Van-Hai Nguyen, Tien-Thinh Le, Nhu-Tung Nguyen

“…Four ML models were used to predict Ra and Vbmax: linear regression (LIN), support vector machine regression (SVR), a gradient boosting tree (GBR), and an artificial neural network (ANN). The input variables were the significant factors that affect the surface quality and tool wear: the feed rate, depth of cut, cutting speed, and cutting time. …”
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Application of Radial Basis Function Neural Network Coupling Particle Swarm Optimization Algorithm to Classification of Saudi Arabia Stock Returns by Khudhayr A. Rashedi, Mohd Tahir Ismail, Nawaf N. Hamadneh, S. AL Wadi, Jamil J. Jaber, Muhammad Tahir

“…These data are further used to train artificial neural network in conjunction with particle swarm optimization algorithm. …”
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Identification of Spectrally Similar Materials From Multispectral Imagery Based on Condition Number of Matrix by Maozhi Wang, Shu-Hua Chen, Jun Feng, Wenxi Xu, Daming Wang

“…The results for a case study to identify water, ice, snow, shadow, and other materials from Landsat 8 OLI data indicate that SF-CNM can identify the materials specified by the given samples successfully and accurately and that SF-CNM significantly outperforms those of spectral angle mapper algorithm, Mahalanobis classifier, maximum likelihood, and artificial neural network, and produces the performance similar to, even slightly better than that of support vector machine.…”
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A robust Parkinson’s disease detection model based on time-varying synaptic efficacy function in spiking neural network by Priya Das, Sarita Nanda, Ganapati Panda, Sujata Dash, Amel Ksibi, Shrooq Alsenan, Wided Bouchelligua, Saurav Mallik

“…Conventional PD detection algorithms are generally based on first and second-generation artificial neural network (ANN) models which consume high energy and have complex architecture. …”
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A performance-based generative design framework based on a design grammar for high-rise office towers during early design stage by Liwei Chen, Ye Zhang, Yue Zheng

“…Case study results demonstrate that, with the support of Artificial Neural Network, utilizing this system can not only globally explore the diversity of tower morphologies but also efficiently uncover greater energy-saving potential in complex architectural forms compared to simpler cubic forms, with an improvement of up to 7.76% during the early stages of design. …”
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Predicting the Number of COVID-19 Sufferers in Malang City Using the Backpropagation Neural Network with the Fletcher–Reeves Method by Syaiful Anam, Mochamad Hakim Akbar Assidiq Maulana, Noor Hidayat, Indah Yanti, Zuraidah Fitriah, Dwi Mifta Mahanani

“…Predicting the number of COVID-19 sufferers becomes an important task in the effort to curb the spread of COVID-19. Artificial neural network (ANN) is the prediction method that delivers effective results in doing this job. …”
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Molecular Modeling of Antimalarial Agents by 3D-QSAR Study and Molecular Docking of Two Hybrids 4-Aminoquinoline-1,3,5-triazine and 4-Aminoquinoline-oxalamide Derivatives with the... by Hanine Hadni, Mohamed Mazigh, El’mbarki Charif, Asmae Bouayad, Menana Elhallaoui

“…The QSAR model tested with artificial neural network (ANN) method shows high performance towards its predictability. …”
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Decentralized control system for unlimited street lighting poles with an intelligent, energy-saving off-grid maximum power point tracking battery charger by Hussain Attia, Ali Al-Ataby, Maen Takruri, Amjad Omar

“…Additionally, we investigate how solar energy as a clean renewable source might be included in the system, offering an off-grid street lighting dimming solution. A deep artificial neural network (ANN) algorithm is designed to have an effective response of maximum power point tracking (MPPT) in terms of accuracy and speed to obtain maximum electrical power from the incident light on a pair of photovoltaic panels fixed above an off-grid street light pole. …”
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Prediction of Current and Future Distributions of Chalcophora detrita (Coleoptera: Buprestidae) Under Climate Change Scenarios by Arif Duyar, Muhammed Arif Demir, Mahmut Kabalak

“…An ensemble model was created by using 11 different algorithms (Artificial Neural Network, Classification Tree Analysis, eXtreme Gradient Boosting, Flexible Discriminant Analysis, Generalised Additive Model, Generalised Boosting Model, Generalised Linear Model, Multivariate Adaptive Regression Splines, Maximum Entropy, Random Forest, Surface Range Envelope) to predict the potential suitable habitats of C. detrita. …”
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