Methylene Blue Adsorption BY UV-Treated Graphene Oxide Nanoparticles (UV/n-GO): Modeling and Optimization Using Response Surface Methodology and Artificial Neural Networks by M. Venkata Ratnam, Manikkampatti Palanisamy Murugesan, Srikanth Komarabathina, S. Samraj, Mohammedsani Abdulkadir, Muktar Abdu Kalifa

“…Furthermore, the batch adsorption studies were modelled using response surface modelling (RSM) and artificial neural networks (ANNs). Investigations employing FTIR, XRD, and SEM were carried out to characterize the adsorbent. …”
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Modeling and Analysis of Mechanical Properties of Aluminium Alloy (A413) Processed through Squeeze Casting Route Using Artificial Neural Network Model and Statistical Technique by R. Soundararajan, A. Ramesh, S. Sivasankaran, A. Sathishkumar

“…Artificial Neural Network (ANN) approach was used for predicting and analyzing the mechanical properties of A413 aluminum alloy produced by squeeze casting route. …”
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Forecasting Daily Precipitation Using Hybrid Model of Wavelet-Artificial Neural Network and Comparison with Adaptive Neurofuzzy Inference System (Case Study: Verayneh Station, Nahavand) by Abazar Solgi, Vahid Nourani, Amir Pourhaghi

“…Then, these subseries were applied as input data for artificial neural network, to predict daily precipitation, and compared with results of adaptive neurofuzzy system. …”
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Modeling of CO2 solubility and partial pressure in blended diisopropanolamine and 2-amino-2-methylpropanol solutions via response surface methodology and artificial neural network by Zohreh Khoshraftar

“…Abstract In this study, Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were developed to estimate the equilibrium solubility and partial pressure of CO2 in blended aqueous solutions of diisopropanolamine (DIPA) and 2-amino-2-methylpropanol (AMP). …”
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A Hybrid Forecasting Model Based on Bivariate Division and a Backpropagation Artificial Neural Network Optimized by Chaos Particle Swarm Optimization for Day-Ahead Electricity Price by Zhilong Wang, Feng Liu, Jie Wu, Jianzhou Wang

“…Based on the chaos particle swarm optimization (CPSO), the backpropagation artificial neural network (BPANN), and the idea of bivariate division, this paper proposes a bivariate division BPANN (BD-BPANN) method and the CPSO-BD-BPANN method for forecasting electricity price. …”
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Intermittent series direct current arc fault detection in direct current more‐electric engine power systems based on wavelet energy spectra and artificial neural network by J. Thomas, R. Telford, P. J. Norman, G. M. Burt

“…This paper addresses these unique MEA/MEE issues through the proposal of a new generalised real‐time arc fault detection methodology (WaSp) based on time–frequency domain‐extracted features applied to a feed‐forward Artificial Neural Network (ANN). The paper outlines the analysis of arc fault time–frequency domain features. …”
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A Comparison of Machine Learning-Based Approaches in Estimating Surface PM_2.5 Concentrations Focusing on Artificial Neural Networks and High Pollution Events by Shijin Wei, Kyle Shores, Yangyang Xu

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The Statistical Detecting of Sulfur Hexafluoride and Nitrous Oxide Effect on Seasonal Rainfalls in Iran During Recent Decade by Yosef Ghavidel Rahimi, Maysam Tolabi Nejad, Manochehr Farajzadeh

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Prediction of size distribution of iron ore granules and permeability of its bed by Lv X., Bai C., Huang X., Qiu G.

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Accuracy comparison of Elamn and Jordan artificial neural networks for air particular matter concentration (PM 10) prediction using MODIS satellite images, a case study of Ahvaz. by javad sadidi, hani rezayan, Mohammad reza barshan

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Comparing prediction accuracy for 30-day readmission following primary total knee arthroplasty: the ACS-NSQIP risk calculator versus a novel artificial neural network model by Anirudh Buddhiraju, Michelle Riyo Shimizu, Tony Lin-Wei Chen, Henry Hojoon Seo, Blake M. Bacevich, Pengwei Xiao, Young-Min Kwon

“…This study aims to compare the predictive accuracy of the SRC with a novel artificial neural network (ANN) algorithm for 30-day readmission after primary TKA, using the same set of clinical variables from a large national database. …”
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Determination of the effect of GA3 applications on plant development, nutrient content change and analysis of root architectural features using ML artificial neural network modelling in Tulipa saxatilis by Sari Ömer

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Optimization of Residual Wall Thickness Uniformity in Short-Fiber-Reinforced Composites Water-Assisted Injection Molding Using Response Surface Methodology and Artificial Neural Network-Genetic Algorithm by Haiying Zhou, Hesheng Liu, Tangqing Kuang, Qingsong Jiang, Zhixin Chen, Weipei Li

“…Response surface methodology (RSM) and artificial neural network (ANN) optimized by genetic algorithm (GA) were employed to map the relationship between the process parameters and the standard deviation (SD) depicting the RWTU. …”
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Predictive modeling and optimization of noise emissions in a palm oil methyl ester-fueled diesel engine using response surface methodology and artificial neural network integrated with genetic algorithm by J.M. Zikri, M.S.M. Sani, M.F.F.A. Rashid, J. Muriban, G.S. Prayogo

“…This research examines the predictive performance of two modeling techniques—Response Surface Methodology (RSM) and an Artificial Neural Network enhanced by a Genetic Algorithm (ANN-GA)—in relation to noise emission levels from a single-cylinder diesel engine running on palm oil methyl ester (POME). …”
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Application of a Multi‐Layer Artificial Neural Network in a 3‐D Global Electron Density Model Using the Long‐Term Observations of COSMIC, Fengyun‐3C, and Digisonde by Wang Li, Dongsheng Zhao, Changyong He, Yi Shen, Andong Hu, Kefei Zhang

“…In this study, multiple observations during 2005–2019 from space‐borne global navigation satellite system (GNSS) radio occultation (RO) systems (COSMIC and FY‐3C) and the Digisonde Global Ionosphere Radio Observatory are utilized to develop a completely global ionospheric three‐dimensional electron density model based on an artificial neural network, namely ANN‐TDD. The correlation coefficients of the predicted profiles all exceed 0.96 for the training, validation and test datasets, and the minimum root‐mean‐square error of the predicted residuals is 7.8 × 104 el/cm3. …”
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Innovation of Urban Circular Economy Growth Path Based on Neural Network by Weifeng Qiu, Yi Yang

Subjects: “…Artificial neural network…”
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Model of Automatic Classification and Localization of Images by L. V. Serebryanaya, K. Y. Bochkarev, A. Y. Popitich

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Automatic Image Colorization Based on Convolutional Neural Networks by L. V. Serebryanaya, V. V. Potaraev

Subjects: “…artificial neural network…”
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Optimal adjustment of deep neural network parameters in estimating lost vital sign data in body wireless sensor networks by Aboulfazl Ebrahimi, Mahboubeh Shamsi, Morteza Mohajjel

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Air Pollution Forecasting Using Artificial and Wavelet Neural Networks with Meteorological Conditions by Qingchun Guo, Zhenfang He, Shanshan Li, Xinzhou Li, Jingjing Meng, Zhanfang Hou, Jiazhen Liu, Yongjin Chen

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