Predicting Patients’ Revisit Intention Based on Satisfaction Scores: Combination of Penalized Regression and Neural Networks by Farshid Abdi, Shaghayegh Abolmakarem, Amir Karbassi Yazdi, Paul Leger, Yong Tan, Giuliani Coluccio

“…Moreover, the findings demonstrate that the Artificial Neural Network model best fits the predictive model and offers the highest reliability. …”
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Rancidity Estimation of Perilla Seed Oil by Using Near-Infrared Spectroscopy and Multivariate Analysis Techniques by Suk-Ju Hong, Shin-Joung Rho, Ah-Yeong Lee, Heesoo Park, Jinshi Cui, Jongmin Park, Soon-Jung Hong, Yong-Ro Kim, Ghiseok Kim

“…Preprocessing methods were applied to the transmittance spectra of perilla seed oil, and multivariate analysis techniques, such as principal component regression (PCR), partial least squares regression (PLSR), and artificial neural network (ANN) modeling, were employed to develop the models. …”
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Evaluation of Contemporary Computational Techniques to Optimize Adsorption Process for Simultaneous Removal of COD and TOC in Wastewater by Areej Alhothali, Hifsa Khurshid, Muhammad Raza Ul Mustafa, Kawthar Mostafa Moria, Umer Rashid, Omaimah Omar Bamasag

“…This study was aimed at evaluating the artificial neural network (ANN), genetic algorithm (GA), adaptive neurofuzzy interference (ANFIS), and the response surface methodology (RSM) approaches for modeling and optimizing the simultaneous adsorptive removal of chemical oxygen demand (COD) and total organic carbon (TOC) in produced water (PW) using tea waste biochar (TWBC). …”
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Prediction of Frequency for Simulation of Asphalt Mix Fatigue Tests Using MARS and ANN by Ali Reza Ghanizadeh, Mansour Fakhri

“…Two methods including Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Network (ANN) methods were then employed to predict the effective length (i.e., frequency) of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. …”
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Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission by Sandeep Sachdeva, Maninder Singh, U. P. Singh, Ajat Shatru Arora

“…To reduce the error of load forecasting, fuzzy method has been used with Artificial Neural Network (ANN) and OFDM transmission is used to get data from outer world and send outputs to outer world accurately and quickly. …”
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Rapid Fluid Velocity Field Prediction in Microfluidic Mixers via Nine Grid Network Model by Qian Li, Yuwei Chen, Taotao Sun, Junchao Wang

“…Using this theory, we developed and trained an artificial neural network (ANN) to predict the fluid dynamics within microfluidic mixers. …”
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Vibration Reliability Analysis of Aeroengine Rotor Based on Intelligent Neural Network Modeling Framework by Jia-Qi Liu, Yun-Wen Feng, Cheng Lu, Wei-Huang Pan, Da Teng

“…INNMF is based on the artificial neural network (ANN) algorithm through improved particle swarm optimization (PSO) algorithm and Bayesian Regularization (BR) optimization. …”
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Price Prediction for Fresh Agricultural Products Based on a Boosting Ensemble Algorithm by Nana Zhang, Qi An, Shuai Zhang, Huanhuan Ma

“…The prediction performance of the Light gradient boosting machine model is evaluated by comparing it against multiple benchmark models (ARIMA, decision tree, random forest, support vector machine, XGBoost, and artificial neural network) in terms of accuracy, generalizability, and robustness on different datasets and under different time windows. …”
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Optimal Learning Behavior Prediction System Based on Cognitive Style Using Adaptive Optimization-Based Neural Network by Ghada Aldabbagh, Daniyal M. Alghazzawi, Syed Hamid Hasan, Mohammed Alhaddad, Areej Malibari, Li Cheng

“…The learning behavior and browsing behavior features are extracted and incorporated into the input of artificial neural network (ANN). Hence, in this paper, the neural network weights are optimized with the use of grey wolf optimizer (GWO) algorithm. …”
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A Software Tool for Optimal Sizing of PV Systems in Malaysia by Tamer Khatib, Azah Mohamed, K. Sopian

“…The software has the capabilities of predicting the metrological variables such as solar energy, ambient temperature and wind speed using artificial neural network (ANN), optimizes the PV module/ array tilt angle, optimizes the inverter size and calculate optimal capacities of PV array, battery, wind turbine and diesel generator in hybrid PV systems. …”
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Machine learning-driven power prediction in continuous extrusion of pure titanium for enhanced structural resilience under extreme loading by Ahmed Ghazi Abdulameer, Muhannad M. Mrah, Maryam Bazerkan, Luttfi A. Al-Haddad, Mustafa I. Al-Karkhi

“…Specifically, an Artificial Neural Network (ANN) model optimized using Stochastic Gradient Descent (SGD) was introduced to forecast power requirements with high precision. …”
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A Novel Kernel for RBF Based Neural Networks by Wasim Aftab, Muhammad Moinuddin, Muhammad Shafique Shaikh

“…In this work, we introduce a novel RBF artificial neural network (ANN) where the basis function utilizes a linear combination of ED based Gaussian kernel and a cosine kernel where the cosine kernel computes the angle between feature and center vectors. …”
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Active Vibration Control of the Sting Used in Wind Tunnel: Comparison of Three Control Algorithms by Xing Shen, Yuke Dai, Mingxuan Chen, Lei Zhang, Li Yu

“…This paper details three algorithms, respectively, Classical PD Algorithm, Artificial Neural Network PID (NNPID), and Linear Quadratic Regulator (LQR) Optimal Control Algorithm, which can realize active vibration control of sting used in wind tunnel. …”
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Effect of Caesalpinia decapetala on the Dry Sliding Wear Behavior of Epoxy Composites by Hailemariam Biratu, Mengistu Gelaw, Kiran Shahapurkar, Venkatesh Chenrayan, Manzoore Elahi M. Soudagar, Vineet Tirth, Ali Algahtani, Tawfiq Al-Mughanam

“…The grey relational analysis- (GRA-) coupled artificial neural network (ANN) hybrid technique was employed for the prediction and validation. …”
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Fault Diagnosis and Detection in Industrial Motor Network Environment Using Knowledge-Level Modelling Technique by Saud Altaf, Muhammad Waseem Soomro, Mirza Sajid Mehmood

“…This paper presents efficient supervised Artificial Neural Network (ANN) learning technique that is able to identify fault type when situation of diagnosis is uncertain. …”
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Utilizing Machine Learning-based Classification Models for Tracking Air Pollution Sources: A Case Study in Korea by Yelim Choi, Bogyeong Kang, Daekeun Kim

“…Using 972 datasets consisting of five emission sources and 27 air pollutants, different classification models were implemented and subsequently compared: Random Forest (RF), Naïve Bayes Classifier (NBC), Support Vector Machine (SVM), Artificial Neural Network (ANN), and K-Nearest Neighbors (K-NN). …”
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Combined interaction of fungicides binary mixtures: experimental study and machine learning-driven QSAR modeling by Mohsen Abbod, Ahmad Mohammad

“…QSAR modeling was conducted to assess their fungicidal activity through multiple linear regression (MLR), support vector machine (SVM), and artificial neural network (ANN). Most mixtures exhibited additive interaction, with the CA model proving more accurate than the IA model in predicting fungicidal activity. …”
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Analysis of the Correlation between Emerging Industry Development and University Students’ Entrepreneurship Based on Big Data by Yufeng Pan, Hui Huang

“…Experiments show that the big data integration system established by GM correlation analysis and ant colony Elman regression artificial neural network has high accuracy and can well identify the priority relevance of the industrial direction of strategic emerging industries to college students’ entrepreneurship. …”
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Improving prediction of solar radiation using Cheetah Optimizer and Random Forest. by Ibrahim Al-Shourbaji, Pramod H Kachare, Abdoh Jabbari, Raimund Kirner, Digambar Puri, Mostafa Mehanawi, Abdalla Alameen

“…Quantitative analysis demonstrates that the CO-RF model surpasses other techniques, Logistic Regression (LR), Support Vector Machine (SVM), Artificial Neural Network, and standalone Random Forest (RF), both in the training and testing phases of SR prediction. …”
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Accurate Recognition and Simulation of 3D Visual Image of Aerobics Movement by Wenhua Fan, Hyun Joo Min

“…The structure of the deep artificial neural network is similar to the structure of the biological neural network, which can be well applied to the 3D visual image recognition of aerobics movements. …”
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