Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp.... by Mohd Shamzi Mohamed, Joo Shun Tan, Rosfarizan Mohamad, Mohd Noriznan Mokhtar, Arbakariya B. Ariff

“…RSM capability was also weighed against an artificial neural network (ANN) approach for predicting a composition that would result in maximum lipid productivity, Prlipid. …”
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Performance analysis of K-nearest neighbor, support vector machine, and artificial neural network classifiers for driver drowsiness detection with different road geometries by Zhenlong Li, Qingzhou Zhang, Xiaohua Zhao

“…This article comparatively analyzed the performance of K-nearest neighbor, support vector machine, and artificial neural network classifiers for driver drowsiness detection with different road geometries (straight segments and curve segments) based on a driving simulator. …”
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Investigating continuous intention to use metaverse in higher education institutions: a dual-staged structural equation modeling-artificial neural network approach by Reham Adel Ali, Mohamed Soliman, Muhammad Roflee Weahama, Muhammadafeefee Assalihee, Imran Mahmud

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COVID-19 Detection Using Deep Convolutional Neural Networks and Binary Differential Algorithm-Based Feature Selection from X-Ray Images by Mohammad Saber Iraji, Mohammad-Reza Feizi-Derakhshi, Jafar Tanha

“…As a result, this paper presents a hybrid approach based on deep convolutional neural networks that are very effective tools for image classification. …”
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BLSENet: A Novel Lightweight Bilinear Convolutional Neural Network Based on Attention Mechanism and Feature Fusion Strategy for Apple Leaf Disease Classification by Tianyu Fang, Jialin Zhang, Dawei Qi, Mingyu Gao

“…To solve this problem, a lightweight bilinear convolutional neural network (CNN) model named BLSENet based on attention mechanism is designed. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Discussion An autoencoder is a type of artificial neural network used for learning efficient encoding of unlabeled data (unsupervised learning). …”
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New bitongling regulates gut microbiota to predict angiogenesis in rheumatoid arthritis via the gut-joint axis: a deep neural network approach by Yin Guan, Xiaoqian Zhao, Yun Lu, Yue Zhang, Yan Lu, Yue Wang

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Deep Learning-Based Damage Assessment in Cherry Leaves by Burakhan Cubukcu, Hazel BOZCU

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Assessing ECG Interpretation Expertise in Medical Practitioners Through Eye Movement Data and Neuromorphic Models by Syed Mohsin Bokhari, Muhammad Shafi, Fazal Noor, Sarmad Sohaib, Saad Alqahtany, Mark Donnelly

Subjects: “…Spiking neural networks (SNN)…”
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Measurement of Total Flow Rates in Horizontal Well Oil-Water Two-Phase Flows by the Application of BP Neural Network Algorithm to Production Array Logs by Xin Zhang, Hongwei Song, Haimin Guo, Xinlei Shi

“…To obtain the total flow rate of oil-water two-phase flows in horizontal wells, in this paper, Multiple Array Production Suite (MAPS), which is also called Production Array Logs (PAL), is used to conduct simulation experiments, uses BP neural network (BPNN) algorithm to train the data samples, and establishes the prediction models of the total flow rates of oil-water two-phase flows in horizontal wells. …”
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Analysis and Optimization of the Spatial Patterns of Commercial Service Facilities Based on Multisource Spatiotemporal Data and Graph Neural Networks: A Case Study of Beijing, China by Yihang Xiao, Cunzhi Li, Zhiwu Zhou, Dongyang Hou, Xiaoguang Zhou

“…This paper utilizes multisource spatiotemporal data, employing geographic spatial analysis methods and graph neural network models to explore the spatial structure of commercial service facilities in Beijing and their relationships with population density and land use, thereby achieving a detailed classification of the commercial service patterns at the natural neighborhood scale. …”
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Using Flow 3D Simulation, Multiple Nonlinear Regression Approach, and Artificial Neural Network Approach Approaches to Study the Behavior of Vertical Drop Structures by Shaikhli Hasan Al, Mohammed Sarah Hashim, Al-Khafaji Zainab

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Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya by Yashon O. Ouma, Clinton O. Okuku, Evalyne N. Njau

“…To overcome the lack of data in water quality monitoring and prediction, this paper presents an approach based on the feedforward neural network (FNN) model for the simulation and prediction of dissolved oxygen (DO) in the Nyando River basin in Kenya. …”
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Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

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Harvesting Solar Energy: Prediction of Daily Global Horizontal Irradiance Using Artificial Neural Networks and Assessment of Electrical Energy of Photovoltaic at North Eastern Ethiopia by Tegenu A. Woldegiyorgis, Abera D. Assamnew, Gezahegn A. Desalegn, Sentayehu Y. Mossie

“…Thus, the objectives of this article were: (i) assessing daily global horizontal irradiance using network types‐activation functions of artificial neural network (ANN); and (ii) evaluating the daily energy delivered to and available on photovoltaic (PV) cells of GaAs at Kemissie, Woldiya, and Hayk, in the northeastern part of Ethiopia. …”
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A Novel Design of a Neural Network-Based Fractional PID Controller for Mobile Robots Using Hybridized Fruit Fly and Particle Swarm Optimization by Ghusn Abdul Redha Ibraheem, Ahmad Taher Azar, Ibraheem Kasim Ibraheem, Amjad J. Humaidi

“…This work offers the analysis, design, and simulation of a new neural network- (NN) based nonlinear fractional control structure. …”
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Development an Artificial Neural Network Model for Estimating Cost of R/C Building by Using Life-Cycle Cost Function: Case Study of Mexico City by Henry E. Reyes, Juan Bojórquez, Laura Cruz-Reyes, Sonia E. Ruiz, Alfredo Reyes-Salazar, Edén Bojórquez, Manuel Barraza, Antonio Formisano, Omar Payán, José R. Torres

“…The objective of this study is to develop an artificial neural network (ANN) model that can estimate the total expected cost of R/C buildings by using LCC functions. …”
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Brittleness evaluation of main coal seams in Permian Taiyuan-Shanxi formations, Baode block, Ordos Basin: based on a convolutional neural network method by Qingfeng ZHANG, Ziling LI, Jikun ZHANG, Shuai HAO, Xiaoguang SUN, Yanjie SHANG, Yun ZUO

Subjects: “…convolutional neural network…”
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Evaluating Neural Network Performance in Predicting Disease Status and Tissue Source of JC Polyomavirus from Patient Isolates Based on the Hypervariable Region of the Viral Genome by Aiden M. C. Pike, Saeed Amal, Melissa S. Maginnis, Michael P. Wilczek

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Traffic flow modelling of vehicles on a six lane freeway: Comparative analysis of improved group method of data handling and artificial neural network model by Isaac Oyeyemi Olayode, Alessandro Severino, Frimpong Justice Alex, Elmira Jamei

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