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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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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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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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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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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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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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

“…This study compares the effectiveness of a Decision Tree Classifier and an Artificial Neural Network (ANN) in predicting Diabetes Mellitus. …”
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Convolutional neural network approach for fault detection and characterization in medium voltage distribution networks by Atefeh Pour Shafei, J.Fernando A. Silva, J. Monteiro

“…Therefore, this paper introduces a novel method for detecting, classifying, and locating faults in power systems through voltage waveform analysis using a convolutional neural network (CNN) integrated with the Piecewise Function Put Together (PFPT) algorithm for fault detection and fault zone localization in a power distribution network. …”
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Fused-MemBrain: a spiking processor combining CMOS and self-assembled memristive networks by Davide Cipollini, Hugh Greatorex, Michele Mastella, Elisabetta Chicca, Lambert Schomaker

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Detection of structural-functional coupling abnormalities using multimodal brain networks in Alzheimer’s disease: A comparison of three computational models by Yinping Lu, Luyao Wang, Toshiya Murai, Jinglong Wu, Dong Liang, Zhilin Zhang

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AIpollen: An Analytic Website for Pollen Identification Through Convolutional Neural Networks by Xingchen Yu, Jiawen Zhao, Zhenxiu Xu, Junrong Wei, Qi Wang, Feng Shen, Xiaozeng Yang, Zhonglong Guo

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Nonreciprocal surface plasmonic neural network for decoupled bidirectional analogue computing by Xiaomeng Li, Haochen Yang, Enzong Wu, Xincheng Yao, Ying Li, Fei Gao, Hongsheng Chen, Zuojia Wang

“…Abstract To address the burgeoning demand for computing capacity in artificial intelligence, researchers have explored optical neural networks that show advantages of ultrafast speed, low power consumption, ultra-high bandwidth, and high parallelism. …”
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Numerical Assessment of Automotive Mufflers Using FEM, Neural Networks, and a Genetic Algorithm by Ying-Chun CHANG, Min-Chie CHIU, Meng-Ru WU

“…Here, the objective function can be established by using Artificial Neural Networks (ANNs) in conjunction with the muffler’s design parameters and related TLs (simulated by FEM). …”
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Noise Elimination of Reciprocating Compressors Using FEM, Neural Networks Method, and the GA Method by Ying-Chun CHANG, Min-Chie CHIU, Ji-Lin XIE

“…Additionally, to facilitate the shape optimization of the muffler, a polynomial neural network model is adopted to serve as an objective function; also, a Genetic Algorithm (GA) is linked to the OBJ function. …”
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