Reorganizing Neural Network System for Two Spirals and Linear Low-Density Polyethylene Copolymer Problems by G. M. Behery, A. A. El-Harby, Mostafa Y. El-Bakry

“…This paper presents an automatic system of neural networks (NNs) that has the ability to simulate and predict many of applied problems. …”
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Prosthetic Hand Based on Human Hand Anatomy Controlled by Surface Electromyography and Artificial Neural Network by Larisa Dunai, Isabel Seguí Verdú, Dinu Turcanu, Viorel Bostan

“…In this paper, we present a method based on real-time surface electroencephalography hand-based gesture recognition using a multilayer neural network. For this purpose, the sEMG signals have been amplified, filtered and sampled; then, the data have been segmented, feature extracted and classified for each gesture. …”
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Combinatorial intrusion detection model based on deep recurrent neural network and improved SMOTE algorithm by Binghao YAN, Guodong HAN

“…Existing intrusion detection models generally only analyze the static characteristics of network intrusion actions,resulting in low detection rate and high false positive rate,and cannot effectively detect low-frequency attacks.Therefore,a novel combinatorial intrusion detection model (DRRS) based on deep recurrent neural network (DRNN) and region adaptive synthetic minority oversampling technique algorithm (RA-SMOTE) was proposed.Firstly,RA-SMOTE divided the low frequency attack samples into different regions adaptively and improved the number of low-frequency attack samples with different methods from the data level.Secondly,the multi-stage classification features were learned by using the level feedback units in DRNN,at the same time,the multi-layer network structure achieved the optimal non-linear fitting of the original data distribution.Finally,the intrusion detection was completed by trained DRRS.The empirical results show that compared with the traditional intrusion detection models,DRRS significantly improves the detection rate of low-frequency attacks and overall detection efficiency.Besides,DRRS has a certain detection rate for unknown new attacks.So DRRS model is effective and suitable for the actual network environment.…”
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Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints by Shu-Min Lu, Dong-Juan Li

“…An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. …”
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Asymptotical Stability of Riemann-Liouville Nonlinear Fractional Neutral Neural Networks with Time-Varying Delays by Erdal Korkmaz, Abdulhamit Ozdemir, Kenan Yildirim

“…In this paper, the asymptotic stability of solutions is investigated for a class of nonlinear fractional neutral neural networks with time-dependent delays which are unbounded. …”
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MULTI-OBJECTIVE OPTIMIZATION OF VEHICLE/TRACK PARAMETERS BASED ON RBF NEURAL NETWORK SURROGATE MODEL by XIAO Qian, LUO Chao, OUYANG ZhiXu, CHANG Chao, LUO JiaWen

“…The RBF（ Radial Basis Function） neural network surrogate model that employed to explore the multi-objective optimization problems of vehicle and track parameters is to improve the dynamic performance of vehicles. …”
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A Short-Term Load Forecasting Model of LSTM Neural Network considering Demand Response by Xifeng Guo, Qiannan Zhao, Shoujin Wang, Dan Shan, Wei Gong

“…In order to solve the problem of rough feature engineering processing and low prediction accuracy, a short-term load forecasting model of LSTM neural network considering demand response is proposed. …”
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A Fall Risk Detection Model for Infants While Sleeping based on Convolutional Neural Networks by Acep Hendra, Handoko Supeno

“…As an alternative, computer vision techniques have shown rapid advancements in recent years, with Convolutional Neural Networks (CNNs) proving to be highly effective in recognizing visual patterns, including human motion and posture detection. …”
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Local and Deep Features Based Convolutional Neural Network Frameworks for Brain MRI Anomaly Detection by Sajad Einy, Hasan Saygin, Hemrah Hivehch, Yahya Dorostkar Navaei

“…To explore the effects of mixture of local and deep extracted feature on accuracy of classification of brain anomaly, a multibranch convolutional neural network approach is proposed. This approach is designed according to combination of DBP-DAE and DSRCN in an end-to-end manner. …”
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Unified Quantile Regression Deep Neural Network with Time-Cognition for Probabilistic Residential Load Forecasting by Zhuofu Deng, Binbin Wang, Heng Guo, Chengwei Chai, Yanze Wang, Zhiliang Zhu

“…In this paper, we propose a unified quantile regression deep neural network with time-cognition for tackling this challenging issue. …”
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Research on PMF Model Based on BP Neural Network Ensemble Learning Bagging and Fuzzy Clustering by Zhengjin Zhang, Guilin Huang, Yong Zhang, Siwei Wei, Baojin Shi, Jiabao Jiang, Baohua Liang

“…Therefore, this paper proposes a probabilistic matrix factorization model based on BP neural network ensemble learning, bagging, and fuzzy clustering. …”
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Artificial Neural Networks as Digital Twins for Whispering Gallery Mode Optical Sensors in Robotics Applications by Amir R. Ali, Mohamed W. A. Ramadan

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Operation of Hydroelectric Power Plants, Dam Reservoirs, and Energy Trade Using Artificial Neural Networks by Sibel Akkaya Oy, Serkan İnal, Ali Ekber Özdemir

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Prediction of Concrete Compressive Strength Based on the BP Neural Network Optimized by Random Forest and ISSA by Gang Chen, Donglin Zhu, Xiao Wang, Changjun Zhou, Xiangyu Chen

“…In modern engineering construction, the compressive strength of concrete determines the safety of engineering structure. BP neural network (BPNN) tends to converge to different local minimum points, and the prediction accuracy is not high in the prediction of the compressive strength of concrete. …”
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Multi‐Hour‐Ahead Dst Index Prediction Using Multi‐Fidelity Boosted Neural Networks by A. Hu, E. Camporeale, B. Swiger

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The impact of preschool children’s physical fitness evaluation under self organizing maps neural network by Lili Wang, Wenjun Zou, Yuxuan Wang, Denise Koh, Wan Ahmad Munsif Bin Wan Pa, Rujiu Gao

Subjects: “…SOM neural network…”
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Research of Hybrid Hysteresis Modeling of Harmonic Reducer based on SDH Model and Neural Network in Series by Xuanju Dang, Kaili Wang, Hui Jiang, Xiru Wu, Xiangwen Zhang, Shijie Tang

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A Lightweight Convolutional Neural Network for Classification of Brain Tumors Using Magnetic Resonance Imaging by Mahir Kaya, Alper Özatılgan

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UniAMP: enhancing AMP prediction using deep neural networks with inferred information of peptides by Zixin Chen, Chengming Ji, Wenwen Xu, Jianfeng Gao, Ji Huang, Huanliang Xu, Guoliang Qian, Junxian Huang

“…Specifically, we use a feature vector with 2924 values inferred by two deep learning models, UniRep and ProtT5, to demonstrate that such inferred information of peptides suffice for the task, with the help of our proposed deep neural network model composed of fully connected layers and transformer encoders for predicting the antibacterial activity of peptides. …”
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Artificial Neural Network Modeling for Spatial and Temporal Variations of Pore-Water Pressure Responses to Rainfall by M. R. Mustafa, R. B. Rezaur, H. Rahardjo, M. H. Isa, A. Arif

“…A multilayer perceptron neural network model was constructed using Levenberg-Marquardt training algorithm for prediction of soil pore-water pressure variations. …”
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