Investigation of ANN Architecture for Predicting Load-Carrying Capacity of Castellated Steel Beams by Thuy-Anh Nguyen, Hai-Bang Ly, Van Quan Tran

“…This paper aims to propose an artificial neural network (ANN) model with optimal architecture to predict the load-carrying capacity of CSB with a scheme of the simple beam bearing load located at the center of the beam. …”
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Early Warning and Management Method of Abnormal Performance of Tourist Scenic Spots Assisted by Image Recognition Technology by Zhaozhen Song, Jing Lu

“…This study uses the convolutional neural network (CNN) method to realize the image recognition technology of the characteristics of the scenic area’s flow of people and tourists’ preferences, and these characteristics will be displayed to the managers in the form of images. …”
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A Three-Dimensional Anisotropic Diffusion Equation-Based Video Recognition Model for Classroom Concentration Evaluation in English Language Teaching by Yanghong Liu, Jintao Liu

“…DK features provide a nonlinear description of the correlation between successive face images and express face image sequences in the temporal dimension; depth features are extracted by a pretrained depth neural network model that can express the complex nonlinear mapping relationships of images and reflect the more abstract implicit information inside face images. …”
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A generic self-learning emotional framework for machines by Alberto Hernández-Marcos, Eduardo Ros

“…Applied in a case study, an artificial neural network trained on unlabeled agent’s experiences successfully learned and identified eight basic emotional patterns that are situationally coherent and reproduce natural emotional dynamics. …”
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Prediction of Dissolved Oxygen Concentration in Sewage Treatment Process Based on Data Recognition Algorithm by Lili Ma, Jiangping Liu

“…On the one hand, it avoids the excessive random or blind selection of the initial weight threshold of the neural network in the initial stage; on the other hand, in the optimization process of the weight threshold, two types of search mechanisms, FWA and COA, are used to give full play to their respective strengths and to continuously conduct information exchange and mutual cooperation between groups and individuals. …”
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Application of an Internet of Things Oriented Network Education Platform in English Language Teaching by Huizhen Li

“…By analyzing the current situation of the Internet of Things education platform, including its development and structure, this paper constructs the evaluation model of the combination of long-term memory neural network model and gray model and realizes the evaluation of the teaching effect of the Internet of Things education platform. …”
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Theory and Numerical Analysis of Extreme Learning Machine and Its Application for Different Degrees of Defect Recognition of Hoisting Wire Rope by Zhike Zhao, Xiaoguang Zhang

“…ELM was proposed based on the single-hidden layer feed-forward neural network (SLFNN). ELM is characterized by the easier parameter selection rules, the faster converge speed, the less human intervention, and so on. …”
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Improved feature reduction framework for sign language recognition using autoencoders and adaptive Grey Wolf Optimization by Rajeev Goel, Sandhya Bansal, Kavita Gupta

“…A handcrafted artificial neural network serves as the classifier within this integrated framework, denoted as AEGWO-Net. …”
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An Artificial Intelligence Mechanism for the Prediction of Signal Strength in Drones to IoT Devices in Smart Cities by Mohamad Reda A. Refaai, Vinjamuri S. N. C. H. Dattu, H. S. Niranjana Murthy, P. Pramod Kumar, B. Kannadasan, Abdi Diriba

“…Depending on many relevant criteria, an artificial neural network (ANN)-centered precise and effective method is provided to forecast the signal strength from such drones. …”
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Postcare for Repairing Nerve and Tendon Injury Based on Biomimetic Nano-Parallel Material Composite Protein by Junxia Fu, Xiaohong Tan, Yan Tang

“…It can use the BP algorithm in the neural network algorithm to simulate the parallel arrangement of tendon collagen fibers, which is more efficient than other schemes. …”
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Func-Bagging: An Ensemble Learning Strategy for Improving the Performance of Heterogeneous Anomaly Detection Models by Ruinan Qiu, Yongfeng Yin, Qingran Su, Tianyi Guan

“…Additionally, we design a specialized neural network, and by training it adequately, validate the rationality of the proposed adaptive weight distribution strategy, further improving the model’s robustness. …”
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A Channel Attention-Driven Optimized CNN for Efficient Early Detection of Plant Diseases in Resource Constrained Environment by Sana Parez, Naqqash Dilshad, Jong Weon Lee

“…To address this, we propose a lightweight convolutional neural network (CNN) designed for resource-constrained devices termed as <i>LeafNet</i>. …”
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An Integrated Bearing Fault Diagnosis Method Based on Multibranch SKNet and Enhanced Inception-ResNet-v2 by Baoquan Hu, Jun Liu, Yue Xu, Tianlong Huo

“…To solve the above problems, this paper proposes an integrated deep neural network that combines an improved selective kernel network (SKNet) with an enhanced Inception-ResNet-v2, named SIR-CNN. …”
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MONet: cancer driver gene identification algorithm based on integrated analysis of multi-omics data and network models by Yingzan Ren, Tiantian Zhang, Jian Liu, Fubin Ma, Jiaxin Chen, Ponian Li, Guodong Xiao, Chuanqi Sun, Yusen Zhang

“…Our method utilizes two graph neural network algorithms on protein-protein interaction (PPI) networks to extract feature vector representations for each gene. …”
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Analysis of Noise Pollution during Dussehra Festival in Bhubaneswar Smart City in India: A Study Using Machine Intelligence Models by Sourav Kumar Bhoi, Chittaranjan Mallick, Chitta Ranjan Mohanty, Ranjan Soumya Nayak

“…The supervised ML models taken in this work are Decision Tree (DT), Neural Network (NN), k-Nearest Neighbor (k-NN), Naïve Bayes (NB), Support Vector Machine (SVM), and Random Forest (RF). …”
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A New Approach to Estimate Concentration Levels with Filtered Neural Nets for Online Learning by Woodo Lee, Junhyoung Oh, Jaekwoun Shim

“…This research aims to estimate more subtle levels as specified states by using a minimum amount of body movement data. The deep neural network is used to continuously recognize the human concentration model, and the concentration levels can be predicted and estimated by the Kalman filter. …”
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Evaluation of the Risk of Recurrence in Patients with Local Advanced Rectal Tumours by Different Radiomic Analysis Approaches by Alaa Khadidos, Adil Khadidos, Olfat M. Mirza, Tawfiq Hasanin, Wegayehu Enbeyle, Abdulsattar Abdullah Hamad

“…In deep learning, we built a 16-layer convolutional neural network model, driven by a 2D MRI image database comprising both the native images and the bounding box corresponding to each image.…”
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Re-locative guided search optimized self-sparse attention enabled deep learning decoder for quantum error correction by Umesh Uttamrao Shinde, Ravikumar Bandaru

“…Therefore, this research proposes a Re-locative Guided Search optimized self-sparse attention-enabled convolutional Neural Network with Long Short-Term Memory (RlGS2-DCNTM) for performing effective error correction in quantum codes. …”
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Study on Water Quality Inversion Model of Dianchi Lake Based on Landsat 8 Data by Jiaju Cao, Xingping Wen, Dayou Luo, Yinlong Tan

“…The results show that the relative errors of permanganate index (COD) in neural network and multiple regression are 9.68% and 17.48%, respectively; 3.81% and 3.36% in dissolved oxygen (DO); 1.25% and 1.58% in hydrogen ion (pH); in ammonia nitrogen (NH3-N), it is 15.39% and 24.97%, respectively. …”
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Estimating Network Flowing over Edges by Recursive Network Embedding by Liqun Yu, Hongqi Wang, Haoran Mo

“…We propose to embed the nodes to a continuous vector space so that the embedding vector of each node can be reconstructed from its neighbors by a recursive neural network model, linear normalized long short-term memory. …”
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