Outlier Detection and Correction for Monitoring Data of Water Quality Based on Improved VMD and LSSVM by Guangpei Sun, Peng Jiang, Huan Xu, Shanen Yu, Dong Guo, Guang Lin, Hui Wu

“…The LSSVM algorithm increases the fitting accuracy and decreases correction error in comparison with SVM and BP neural network, which provides important references for the implementation of environmental protection measures.…”
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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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Static Mechanical Properties and Microscopic Analysis of Hybrid Fiber Reinforced Ultra-High Performance Concrete with Coarse Aggregate by Shengbing Liu, Yonglei Zhang

“…Finally, three kinds of strength parameters are predicted based on the back propagation (BP) neural network system. The absolute value of the relative error between the predicted strength and the experimental value is less than 5%, which indicates that the prediction model proposed in this paper can provide a reference for the multiobjective optimization of the mix proportion of hybrid fiber ultra-high performance concrete.…”
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A Machine Learning-Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel by Ngoc-Long Tran, Trong-Ha Nguyen, Van-Tien Phan, Duy-Duan Nguyen

“…The purpose of this study is to develop a practical artificial neural network (ANN) model for predicting the atmospheric corrosion rate of carbon steel. …”
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Time-Frequency Analysis and Target Recognition of HRRP Based on CN-LSGAN, STFT, and CNN by Jianghua Nie, Yongsheng Xiao, Lizhen Huang, Feng Lv

“…Aiming at the problem of radar target recognition of High-Resolution Range Profile (HRRP) under low signal-to-noise ratio conditions, a recognition method based on the Constrained Naive Least-Squares Generative Adversarial Network (CN-LSGAN), Short-time Fourier Transform (STFT), and Convolutional Neural Network (CNN) is proposed. Combining the Least-Squares Generative Adversarial Network (LSGAN) with the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP), the CN-LSGAN is presented and applied to the HRRP denoise. …”
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A Convection Nowcasting Method Based on Machine Learning by Aifang Su, Han Li, Liman Cui, Yungang Chen

“…The test analysis demonstrated that the algorithm combined the image feature extraction ability of the convolutional neural network (CNN) and the sequential learning ability of the long short-term memory network (LSTM) model to establish an end-to-end deep learning network, which could deeply extract high-order features of radar echoes such as structural texture, spatial correlation, and temporal evolution compared with the traditional algorithm. …”
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Data-driven model discovery and model selection for noisy biological systems. by Xiaojun Wu, MeiLu McDermott, Adam L MacLean

“…Simulations from the fitted neural network are then used to infer models using sparse regression. …”
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Identification of diabetic retinopathy lesions in fundus images by integrating CNN and vision mamba models. by Zenglei Liu, Ailian Gao, Hui Sheng, Xueling Wang

“…Considering these analyses, this work presents a comprehensive deep learning model that combines convolutional neural network and vision mamba models. This model is designed to accurately identify and classify diabetic retinopathy lesions displayed in fundus images. …”
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Neural ODEs for holographic transport models without translation symmetry by Zhuo-Fan Gu, Yu-Kun Yan, Shao-Feng Wu

“…We convert the flow equation to a Neural Ordinary Differential Equation (Neural ODE), which is a neural network with continuous depth and produces output through a black-box ODE solver. …”
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Exploring the Relationships between Subjective Evaluations and Objective Metrics of Vehicle Dynamic Performance by Jianyou Zhao, Jing Liu, Liping Yang, Ping He

“…Finally, an overall subjective evaluation model related to the three objective metrics was established based on the Probabilistic Neural Network (PNN). The analysis results demonstrated that the correlation coefficients of the three groups of data were greater than 0.5 and that each subjective evaluation was significantly correlated with its corresponding objective metric. …”
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Dual-Vehicle Heterogeneous Collaborative Scheme with Image-Aided Inertial Navigation by Zi-Ming Wang, Chun-Liang Lin, Chian-Yu Lu, Po-Chun Wu, Yang-Yi Chen

“…Our approach harnesses advanced image feature-recognition techniques, employing an enhanced scale-invariant feature transform algorithm and a neural network model. The recognition of prominent scene features is prioritized, thus improving recognition speed and precision. …”
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Fast and low‐power leading‐one detectors for energy‐efficient logarithmic computing by Mohammad Saeed Ansari, Shyama Gandhi, Bruce F. Cockburn, Jie Han

“…The Mitchell logarithmic multiplier and a neural network are considered to further illustrate the practicality of the proposed designs.…”
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Action Selection and Operant Conditioning: A Neurorobotic Implementation by André Cyr, Frédéric Thériault

“…We propose simulating an AS process by using a small spiking neural network (SNN) as the lower neural organisms, in order to control virtual and physical robots. …”
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Movie scene segmentation using object detection and set theory by Ijaz Ul Haq, Khan Muhammad, Tanveer Hussain, Soonil Kwon, Maleerat Sodanil, Sung Wook Baik, Mi Young Lee

“…In this article, we investigated this problem through a novel intelligent Convolutional Neural Network (CNN) based three folded framework. The first fold segments the input movie into shots, the second fold detects objects in the segmented shots and the third fold performs object-based shots matching for detecting scene boundaries. …”
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Comparative Analysis of Battery State of Charge Estimation Methods by Margal Ali, El Daoudi Soukaina, Khallouq Abdelmounaim, Karama Asma

“…This paper presents three methods for estimating SoC: the extended Kalman filter (EKF), the adaptive Luenberger observer (ALO), and a neural network model employing nonlinear auto-regressive with eXogenous inputs (NARX). …”
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A guidance to intelligent metamaterials and metamaterials intelligence by Chao Qian, Ido Kaminer, Hongsheng Chen

“…For metamaterials intelligence, we particularly unfold three canonical categories, i.e., wave-based neural network, mathematical operation, and logic operation, all of which directly execute computation, detection, and inference task in physical space. …”
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Predicting the urban water demand by equipping intelligent-based methods with discrete wavelet transform function by Mohammad Reza Alikhani, Ramtin Moeini

“…For this purpose, in this research, artificial intelligence and data mining methods, including genetic programming (GP), gene expression programming (GEP), artificial neural network (ANN), and discrete wavelet transform function, are used to predict the daily drinking water consumption values of WDN. …”
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YOLO-UNet Architecture for Detecting and Segmenting the Localized MRI Brain Tumor Image by Nur Iriawan, Anindya A. Pravitasari, Ulfa S. Nuraini, Nur I. Nirmalasari, Taufik Azmi, Muhammad Nasrudin, Adam F. Fandisyah, Kartika Fithriasari, Santi W. Purnami, null Irhamah, Widiana Ferriastuti

“…This paper employed deep learning to detect and segment brain tumor MRI images by combining the convolutional neural network (CNN) and fully convolutional network (FCN) methodology in serial. …”
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Multilevel Attention and Multiscale Feature Fusion Network for Author Classification of Chinese Ink-Wash Paintings by Wei Jiang, Xianglian Meng, Ji Xi

“…The model extracts three types of feature maps from the low-level, middle-level and high-level layers of the pretrained deep neural network firstly. Then, the low-level and middle-level feature maps are processed by the spatial attention module, nevertheless the high-level feature maps are processed by the scale invariance module to increase the scale-invariance properties. …”
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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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