Forward model emulator for atmospheric radiative transfer using Gaussian processes and cross validation by O. Lamminpää, J. Susiluoto, J. Hobbs, J. McDuffie, A. Braverman, H. Owhadi

“…In contrast with artificial neural network (ANN)-based methods, it is interpretable, and its efficiency is based on learning a kernel in an engineered and expressive family of kernels.…”
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Predicting the Botanical Origin of Honeys with Chemometric Analysis According to Their Antioxidant and Physicochemical Properties by Anna Maria Kaczmarek, Małgorzata Muzolf-Panek, Jolanta Tomaszewska-Gras, Piotr Konieczny

“…The aim of this study was to develop models based on Linear Discriminant Analysis (LDA), Classification and Regression Trees (C&RT), and Artificial Neural Network (ANN) for the prediction of the botanical origin of honeys using their physicochemical parameters as well as their antioxidative and thermal properties. …”
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Advanced in Islanding Detection and Fault Classification for Grid-Connected Distributed Generation using Deep Learning Neural Network by Rusvaira Qatrunnada, Novizon Novizon, Mardini Hasanah, Tuti Angraini, Anton Anton

“…The use of an Artificial Neural Network (ANN) based on the learning vector quantization (LVQ) technique is proposed in this paper for fault classification and islanding detection in grid-connected distributed generators. …”
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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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Modeling saturation exponent of underground hydrocarbon reservoirs using robust machine learning methods by Abhinav Kumar, Paul Rodrigues, A. K. Kareem, Tingneyuc Sekac, Sherzod Abdullaev, Jasgurpreet Singh Chohan, R. Manjunatha, Kumar Rethik, Shivakrishna Dasi, Mahmood Kiani

“…In this communication, we aim to develop intelligent data-driven models of decision tree, random forest, ensemble learning, adaptive boosting, support vector machine and multilayer perceptron artificial neural network to predict rock saturation exponent parameter in terms of rock absolute permeability, porosity, resistivity index, true resistivity, and water saturation based on acquired 1041 field data. …”
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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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Efficiency-House Optimization to Widen the Operation Range of the Double-Suction Centrifugal Pump by Wenjie Wang, Majeed Koranteng Osman, Ji Pei, Shouqi Yuan, Jian Cao, Fareed Konadu Osman

“…A two-layer feedforward artificial neural network (ANN) and the Kriging model were combine based on a hybrid approximate model and solved with swarm intelligence for global best parameters that would maximize the pump efficiency. …”
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Experimental and analytical study on axial behaviour of square corrugated concrete filled single and double skin tube stub columns by Aya Mohsen Handousa, Mohamed Abdellatief, Fikry Abdo Salem, Nabil Mahmoud, Mohamed Ghannam

“…Furthermore, the study proposed two machine-learning models, namely Artificial Neural Network (ANN) and Gaussian Process Regression (GPR), to estimate the ultimate compressive strength of square CFDST columns. …”
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Computational-Based Approaches for Predicting Biochemical Oxygen Demand (BOD) Removal in Adsorption Process by Mohamed K. Mostafa, Ahmed S. Mahmoud, Mohamed S. Mahmoud, Mahmoud Nasr

“…Hence, this study is the first to develop a quadratic regression model and artificial neural network (ANN) for predicting biochemical oxygen demand (BOD) removal under different adsorption conditions. …”
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Nonintrusive Load Identification for Industrial Users Integrated with LSQR and Sequential Leader Clustering by Shuhui Yi, Yinglong Diao, Junjie Liu, Tian Fang, Xiaodong Yin

“…The results indicate that the model proposed can effectively achieve the nonintrusive industrial load identification, and least unified residue (LUR) is about 10−16, which is much better than the factorial hidden Markov model (FHMM) and the artificial neural network (ANN) model.…”
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Machine learning prediction of combat basic training injury from 3D body shape images. by Steven Morse, Kevin Talty, Patrick Kuiper, Michael Scioletti, Steven B Heymsfield, Richard L Atkinson, Diana M Thomas

“…Predictions were made using logistic regression, random forest, and artificial neural network (ANN) models. Model comparison was done using the area under the curve (AUC) of a ROC curve.…”
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A decision support system based on classification algorithms for the diagnosis of periodontal disease by Abdulrahman Alshehri, Mohammed Dahman, Mousa Assiri, Abdulkarim Alshehri, Sharifah Alqahtani, Mohammed Shaiban, Bashyer Alqahtani, Sabah Althbyani, Hatem Alhefdi, Khalid Hakami, Abdulbari Ali, Abdullah Saeed

“…Aims: The purpose of this study was to develop and evaluate a decision support system (DSS) based on selected classification algorithms, namely random forest (RF), support vector machine (SVM), artificial neural network (ANN), and logistic regression for the periodontal disease diagnosis. …”
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ESTIMATED ELECTRICITY BILLING SYSTEM AND ITS EFFECTS ON CONSUMERS IN RESIDENTIAL AND BUSINESS CENTRES IN WUKARI METROPOLIS, TARABA STATE by Abubakar Ahmadu, Vyonkhen Tanko Nacho

“…It is recommended among others the adoption of Artificial Neural Network (ANN) to gauge consumers’ energy consumption pending the provision of prepaid meters and that National Electricity Regulatory Commission (NERC) should intensify efforts in the provision of free and/or subsidized prepaid meters to consumers. …”
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Implementing an Outgoing Longwave Radiation Climate Dataset from Fengyun 3E Satellite Data with a Machine-Learning Algorithm by Yanjiao Wang, Feng Yan

“…We designed a new correction model, “DeepFM”, implementing both a factorization machine algorithm and a deep artificial neural network to minimize daily mean differences between the datasets. …”
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A Hybrid Neuro-Fuzzy and Feature Reduction Model for Classification by Himansu Das, Bighnaraj Naik, H. S. Behera

“…It helps to deal with the uncertainty issues and assists the Artificial Neural Network- (ANN-) based model to achieve better performance. …”
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RSM-, ANN-, and GA-Based Process Optimization for Acid Centrifugation Treatment of Cane Molasses Toward Mitigating Calcium Oxide Fouling in Ethanol Plant Heat Exchanger by Lata Deso Abo, Sintayehu Mekuria Hailegiorgis, Mani Jayakumar, Sundramurthy Venkatesa Prabhu, Gadissa Tokuma Gindaba, Abas Siraj Hamda, B. S. Naveen Prasad

“…Furthermore, the implementation of an artificial neural network (ANN) provided a better prediction model for CaO reduction, with a substantial R-squared value of 0.99866. …”
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Optimizing hypertension prediction using ensemble learning approaches. by Isteaq Kabir Sifat, Md Kaderi Kibria

“…Five machine learning (ML) models such as logistic regression (LR), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGB), light gradient boosting machine (LGBM), and a stacking ensemble model were trained using selected features to predict HTN. …”
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The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County by ALI hashemi, Hojjatollah Yazdanpanah, Mehdi Momeni

“…To determine the significance of each independent variable in predicting the dependent variables, the artificial neural network method was employed. The findings showed that the climatic elements of precipitation, minimum temperature, maximum temperature, minimum humidity, and maximum humidity had the greatest effect on EVI, with values of 0.39, 0.3, 0.13, 0.1, and 0.06 respectively. …”
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Assessment of Artificial Intelligence Models for Developing Single-Value and Loop Rating Curves by Majid Niazkar, Mohammad Zakwan

“…As a result, the rating curves of eight different rivers were developed using the conventional method, evolutionary algorithm (EA), the modified honey bee mating optimization (MHBMO) algorithm, artificial neural network (ANN), MGGP, and the hybrid MGGP-GRG technique. …”
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