Ensemble of feature augmented convolutional neural network and deep autoencoder for efficient detection of network attacks by Selvakumar B, Sivaanandh M, Muneeswaran K, Lakshmanan B

“…The proposed work consists of three phases: (i) Feature Augmented Convolutional Neural Network (FA-CNN) (ii) Deep Autoencoder (iii) Ensemble of FA-CNN and Deep Autoencoder. …”
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Sorting Data via a Look-Up-Table Neural Network and Self-Regulating Index by Ying Zhao, Dongli Hu, Dongxia Huang, You Liu, Zitong Yang, Lei Mao, Chao Liu, Fangfang Zhou

“…We integrate a back propagation neural network with the technique of look-up-table in LS to guarantee the monotonicity and boundedness of the predicted placement positions. …”
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A Novel Classification Approach through Integration of Rough Sets and Back-Propagation Neural Network by Lei Si, Xin-hua Liu, Chao Tan, Zhong-bin Wang

“…Classification is an important theme in data mining. Rough sets and neural networks are the most common techniques applied in data mining problems. …”
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Retracted: The Construction of Smart Chinese Medicine Cloud Health Platform Based on Deep Neural Networks by International Transactions on Electrical Energy Systems

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Prediction of Ammunition Storage Reliability Based on Improved Ant Colony Algorithm and BP Neural Network by Fang Liu, Hua Gong, Ligang Cai, Ke Xu

“…A new improved algorithm based on three-stage ant colony optimization (IACO) and BP neural network algorithm is proposed to predict ammunition failure numbers. …”
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Screw Performance Degradation Assessment Based on Quantum Genetic Algorithm and Dynamic Fuzzy Neural Network by Xiaochen Zhang, Hongli Gao, Haifeng Huang

“…To evaluate the performance of ball screw, screw performance degradation assessment technology based on quantum genetic algorithm (QGA) and dynamic fuzzy neural network (DFNN) is studied. The ball screw of the CINCINNATIV5-3000 machining center is treated as the study object. …”
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Discovering and Characterizing Hidden Variables Using a Novel Neural Network Architecture: LO-Net by Soumi Ray, Tim Oates

“…We claim that theoretical entities, or hidden variables, are important for the development of concepts within the lifetime of an individual and present a novel neural network architecture that solves three problems related to theoretical entities: (1) discovering that they exist, (2) determining their number, and (3) computing their values. …”
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Vibration Reliability Analysis of Drum Brake Using the Artificial Neural Network and Important Sampling Method by Zhou Yang, Unsong Pak, Cholu Kwon

“…Two types of ANNs used in this study are the radial basis function neural network (RBF) and back propagation neural network (BP). …”
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Evaluation the efficiency of using Artificial Neural Networks in predicting meteorological droughts in north-west of Iran by Arash malekian, mahro dehbozorgi, Amir hoshang ehsani

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Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approaches by Manjunath Patel Gowdru Chandrashekarappa, Prasad Krishna, Mahesh B. Parappagoudar

“…An attempt is also made to meet the industrial requirements of developing the reverse model to predict the recommended squeeze cast parameters for the desired density and SDAS. Two different neural network based approaches have been proposed to carry out the said task, namely, back propagation neural network (BPNN) and genetic algorithm neural network (GA-NN). …”
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Precise and interpretable neural networks reveal epigenetic signatures of aging across youth in health and disease by David Martínez-Enguita, Thomas Hillerton, Julia Åkesson, Daniel Kling, Maria Lerm, Mika Gustafsson

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Generalization of artificial neural network for predicting methane production in laboratory-scale anaerobic bioreactor landfills by M.J. Zoqi

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Boundedness and Stability for Discrete-Time Delayed Neural Network with Complex-Valued Linear Threshold Neurons by Chengjun Duan, Qiankun Song

“…The discrete-time delayed neural network with complex-valued linear threshold neurons is considered. …”
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Learning deep forest for face anti-spoofing: An alternative to the neural network against adversarial attacks by Rizhao Cai, Liepiao Zhang, Changsheng Chen, Yongjian Hu, Alex Kot

“…Face anti-spoofing (FAS) is significant for the security of face recognition systems. neural networks (NNs), including convolutional neural network (CNN) and vision transformer (ViT), have been dominating the field of the FAS. …”
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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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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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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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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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