Innovative Approaches of Optimization Methods Used in Geothermal Power Plants: Artificial Neural Networks and Genetic Algorithms by Özgür Özer, Harun Kemal Öztürk

“…Heuristic methods, particularly the widely used artificial neural networks and genetic algorithms, are explained in general terms. …”
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Email Spam Detection Using a Hybrid Approach of Feedforward Neural Network and Penguin Optimization Algorithm by Layth Al-busultan

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Research on Food Security Risk Assessment and Early Warning in China Based on BP Neural Network Model by Yuke Hou, Xin Liang

“…This paper constructs a food security evaluation system from the perspective of data, breaks through the limitations of existing research, and improves the completeness of food security early warning indicators. Because the BP neural network is a multilayer feedforward neural network with strong adaptability, it is one of the most widely used and successful neural network models at present. …”
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Stability Analysis of Discrete Hopfield Neural Networks with the Nonnegative Definite Monotone Increasing Weight Function Matrix by Jun Li, Yongfeng Diao, Mingdong Li, Xing Yin

“…The original Hopfield neural networks model is adapted so that the weights of the resulting network are time varying. …”
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Sentiment analysis of Algerian Arabic dialect on social media Using Bi-LSTM recurrent neural networks by Abdelghani BOUZIANE, Benamar BOUOUGADA, Djelloul BOUCHIHA, Noureddine DOUMI

“… This paper presents a sentiment analysis approach using Bidirectional Long Short-Term Memory (Bi-LSTM) Recurrent Neural Networks to train predictive models for sentiment analysis on social media, particularly focusing on Algerian Arabic Dialect. …”
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Seismic Response Analysis and Evaluation of Laminated Rubber Bearing Supported Bridge Based on the Artificial Neural Network by Bingzhe Zhang, Kehai Wang, Guanya Lu, Weizuo Guo

“…A new constitutive model of bearing based on the artificial neural network (ANN) technique is established through the static cyclic test of laminated rubber bearings, considering the bearing initial stiffness, friction coefficient, and other parameters such as the bearing sectional area, height, loading velocity, vertical load, and aging time. …”
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Hybridizing Evolutionary Computation and Deep Neural Networks: An Approach to Handwriting Recognition Using Committees and Transfer Learning by Alejandro Baldominos, Yago Saez, Pedro Isasi

“…Neuroevolution is the field of study that uses evolutionary computation in order to optimize certain aspect of the design of neural networks, most often its topology and hyperparameters. …”
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Application of physics-informed neural networks (PINNs) solution to coupled thermal and hydraulic processes in silty sands by Yuan Feng, Jongwan Eun, Seunghee Kim, Yong-Rak Kim

Subjects: “…Physics-informed neural networks…”
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Sistem Isyarat Bahasa Indonesia (SIBI) Metode Convolutional Neural Network Sequential secara Real Time by Oky Dwi Nurhayati, Dania Eridani, Muhammad Hafiz Tsalavin

“…The convolutional neural network (CNN) method is then used as a learning feature and hand signals classifier on an object. …”
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Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks by Dede Sutarya, Benyamin Kusumoputro

“…Among the different nonlinear identification techniques, methods based on neural network model are gradually becoming established not only in the academia, but also in industrial application. …”
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Research on Neural Network Prediction Model of Whole Process Risk Management Based on Building Information Model by Shihong Huang, Chengye Liang, Jiao Liu

“…The international large public sports center project is used as a case study to establish a BIM model, while the BP neural network risk management model is used for prediction and calculation. …”
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A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

Subjects: “…Particle Swarm Optimization, Neural Networks, Logistic Regression, Nave Bayes Classifier, Multilayer Perceptron, Support Vector Machine, BF Tree, Bayesian Networks.…”
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Predicting the Direction Movement of Financial Time Series Using Artificial Neural Network and Support Vector Machine by Muhammad Ali, Dost Muhammad Khan, Muhammad Aamir, Amjad Ali, Zubair Ahmad

“…The main objective of this research work is to predict the direction movement of the daily stock prices index using the artificial neural network (ANN) and support vector machine (SVM). …”
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Rag‐bull rider optimisation with deep recurrent neural network for epileptic seizure detection using electroencephalogram by Prabin Jose Johnrose, Sundaram Muniasamy, Jaffino Georgepeter

“…A novel method, namely, a rag‐Rider optimisation algorithm (rag‐ROA) is devised for training a deep recurrent neural network (Deep RNN) to discover epileptic seizures. …”
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Multimedia Tasks-Oriented Edge Computing Offloading Scheme Based on Graph Neural Network in Vehicular Networks by Yong Huang

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Finite-Time Projective Synchronization of Fractional-Order Memristive Neural Networks with Mixed Time-Varying Delays by Meng Hui, Chen Wei, Jiao Zhang, Herbert Ho-Ching Iu, Ni Luo, Rui Yao, Lin Bai

“…This paper is concerned with the finite-time projective synchronization problem of fractional-order memristive neural networks (FMNNs) with mixed time-varying delays. …”
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Delay-Dependent Guaranteed Cost Controller Design for Uncertain Neural Networks with Interval Time-Varying Delay by M. Rajchakit, P. Niamsup, T. Rojsiraphisal, G. Rajchakit

“…This paper studies the problem of guaranteed cost control for a class of uncertain delayed neural networks. The time delay is a continuous function belonging to a given interval but not necessary to be differentiable. …”
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Strength Investigation of the Silt-Based Cemented Paste Backfill Using Lab Experiments and Deep Neural Network by Chongchun Xiao, Xinmin Wang, Qiusong Chen, Feng Bin, Yihan Wang, Wei Wei

“…After the discussion of the experimental results, a dataset was prepared after data collection and processing. Deep neural network (DNN) was employed to predict the UCS of CPB from its influencing variables, namely, the proportion of OPC, CG, CFA, and YS, the solids content, and the curing time. …”
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3D Automatic Segmentation of Brain Tumor Based on Deep Neural Network and Multimodal MRI Images by Zhuliang Qian, Lifeng Xie, Yisheng Xu

“…In addition, this paper constructs an automatic diagnosis system for brain tumors, uses GLCM and discrete wavelet transform (DWT) to extract features from MRI images, and then uses a convolutional neural network (CNN) for final diagnosis; finally, through four. …”
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New Results for Periodic Solution of High-Order BAM Neural Networks with Continuously Distributed Delays and Impulses by Chang-Bo Yang, Ting-Zhu Huang, Jin-Liang Shao

“…By M-matrix theory, inequality techniques, and Lyapunov functional method, certain sufficient conditions are obtained to ensure the existence, uniqueness, and global exponential stability of periodic solution for a new type of high-order BAM neural networks with continuously distributed delays and impulses. …”
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