Active Noise Control Using a Functional Link Artificial Neural Network with the Simultaneous Perturbation Learning Rule by Ya-li Zhou, Qi-zhi Zhang, Tao Zhang, Xiao-dong Li, Woon-seng Gan

“…A linear controller under such situations yields poor performance. A novel functional link artificial neural network (FLANN)-based simultaneous perturbation stochastic approximation (SPSA) algorithm, which functions as a nonlinear mode-free (MF) controller, is proposed in this paper. …”
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Nonlinear Compensation of the Linear Variable Differential Transducer Using an Advanced Snake Optimization Integrated with Tangential Functional Link Artificial Neural Network by Qiuxia Fan, Xinqi Zhang, Zhuang Wen, Lei Xu, Qianqian Zhang

Subjects: “…functional link artificial neural network…”
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Cat Swarm Optimization Based Functional Link Artificial Neural Network Filter for Gaussian Noise Removal from Computed Tomography Images by M. Kumar, S. K. Mishra, S. S. Sahu

“…This paper proposes an evolutionary nonlinear adaptive filter approach, using Cat Swarm Functional Link Artificial Neural Network (CS-FLANN) to remove the unwanted noise. …”
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Sinusoidal Neural Networks: Towards ANN that Learns Faster by Tekin Evrim Ozmermer

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A novel committee machine and reviews of neural network and statistical models for currency exchange rate prediction: An experimental analysis by Trilok Nath Pandey, Alok Kumar Jagadev, Satchidananda Dehuri, Sung-Bae Cho

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Determination of vibration characteristic in automatic tapping operations based on artificial neural networks by Emir Esim, Muhammed Demirel

“…Unpredictable vibrations significantly affect threading accuracy, reducing precision and shortening tool life. This study investigates the prediction of vibration characteristics during automatic tapping operations using artificial neural networks (ANN). …”
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Multi-Functional Optical Spectrum Analysis Using Multi-Task Cascaded Neural Networks by Haoyu Wang, Sheng Cui, Changjian Ke, Chenglong Yu, Zi Liang, Deming Liu

“…We demonstrate that, compared with the multi-task artificial neural network (MT-ANN) and convolutional neural network (MT-CNN), the proposed multi-task cascaded ANNs (CANN) and cascaded CNNs (CCNN) can greatly improve the OSA performance and accelerate the training process by exploiting specific features and loss functions for different tasks. …”
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Analysis of Four-Species Diffusive and Non-Diffusive Food Chains Using Artificial Neural Networking by Muhammad Shoaib Arif, Ateeq Ur Rehman, Asad Ejaz

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Comparison of Univariate and Multivariate Applications of GBLUP and Artificial Neural Network for Genomic Prediction of Growth and Carcass Traits in the Brangus Heifer Population by Sunday O. Peters, Kadir Kızılkaya, Mahmut Sinecen, Milt G. Thomas

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Prediction of dust storm using artificial neural networks in Kermanshah by Toba Alizadeheh, Majid rezaie banafsh, Gholamreza Goodarzi, Hashem Rostamzadeh

“…First, the dust data were normalized, and then Artificial Neural Network (ANN) models were used to predict dust concentration, while the Adaptive Neuro-Fuzzy Inference System (ANFIS) was employed to analyze and predict the time series of dust occurrence in MATLAB software. …”
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UHVDC Transmission Line Fault Identification Method Based on Generalized Regression Neural Network by XIE Jia, LIU Feng, KE Yanguo, YIN Zhen, RUAN Wei, YAO Jinming

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The Potential of Unsupervised Induction of Harmonic Syntax for Jazz by Ruben Cartuyvels, John Koslovsky, Marie-Francine Moens

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BPFun: a deep learning framework for bioactive peptide function prediction using multi-label strategy by transformer-driven and sequence rich intrinsic information by Lun Zhu, Hao Sun, Sen Yang

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The neural basis underlying the association between parents’ socioeconomic status and depressive symptoms among college students by Yao Xiao, Xinting Jiang, Yuan Li, Yu Mao, Duyi Zhou

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A comparative study of forecasting methods using real-life econometric series data by Cláudia Eliane da Matta, Natália Maria Puggina Bianchesi, Milena Silva de Oliveira, Pedro Paulo Balestrassi, Fabiano Leal

“…Abstract Paper aims This paper presents a comparative evaluation of different forecasting methods using two artificial neural networks (Multilayer Perceptron network and Radial Basis Functions Neural Network) and the Gaussian process regression. …”
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Artificial Neural Network Modeling of NixMnxOx based Thermistor for Predicative Synthesis and Characterization by T.D. Dongale, K.G. Kharade, N.B. Mullani, G.M. Naik, R.K. Kamat

“…In view of the above, we report an Artificial Neural Network (ANN) technique to accomplish the synthesis with predictable results saving valuable resources. …”
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Performance evaluation, prediction analysis and optimization of experimental ORC using artificial neural networks (ANN) by Diki Ismail Permana, Federico Fagioli, Maurizio De Lucia, Dani Rusirawan, Istvan Farkas

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Conjugate Gradient Algorithm Based on Aitken's Process for Training Neural Networks by Khalil Abbo, Hind Mohammed

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Development of artificial neural network model for predicting the rapid maxillary expansion technique in children with cleft lip and palate by Mohamed Zahoor Ul Huqh, Johari Yap Abdullah, Johari Yap Abdullah, Adam Husein, Adam Husein, Matheel AL-Rawas, Wan Muhamad Amir W. Ahmad, Nafij Bin Jamayet, Mohammad Khursheed Alam, Mohd Rosli Bin Yahya, Siddharthan Selvaraj, Siddharthan Selvaraj, Abedelmalek Kalefh Tabnjh, Abedelmalek Kalefh Tabnjh, Abedelmalek Kalefh Tabnjh

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Newly synthesized 1-butyl-3-methylimidazolium p-toluenesulfonate ionic liquid for acid corrosion of API 5L X70 steel: Experimental, DFT/MD-simulation, statistical and machine learn... by Daniel Iheanacho Udunwa, Okechukwu Dominic Onukwuli, Simeon Chukwudozie Nwanonenyi, Callistus Nonso Ude, Innocent Okechi Arukalam, Remy Uche

“…Statistical technique (response surface methodology (RSM)), artificial neural network-genetic algorithm (ANN-GA), and adaptive neural fuzzy inference system-genetic algorithm (ANFIS-GA) were deployed as an optimization instrument to forecast the percentage inhibition efficiency (% η). …”
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