Segmentation and Classification of Vowel Phonemes of Assamese Speech Using a Hybrid Neural Framework by Mousmita Sarma, Kandarpa Kumar Sarma

“…This paper describes an Artificial Neural Network (ANN) based algorithm developed for the segmentation and recognition of the vowel phonemes of Assamese language from some words containing those vowels. …”
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An Improved Recursive ARIMA Method with Recurrent Process for Remaining Useful Life Estimation of Bearings by Zeyu Luo, Xian-Bo Wang, Zhi-Xin Yang

“…The autoregressive neural network (ARNN) is an early idea to combine the artificial neural network (ANN) and the autoregressive (AR) model for forecasting, but the model is limited to linear terms. …”
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Stock Price Prediction in the Financial Market Using Machine Learning Models by Diogo M. Teixeira, Ramiro S. Barbosa

“…Fundamental concepts of technical analysis are explored, such as exponential and simple averages, and various global indices are analyzed to be used as inputs for machine learning models, including Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Convolutional Neural Network (CNN), and XGBoost. …”
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Single Parameter Adaptive Control of Unknown Nonlinear Systems with Tracking Error Constraints by Hongjun Yang, Zhijie Liu, Shuang Zhang

“…This paper investigates a single parameter adaptive neural network control method for unknown nonlinear systems with bounded external disturbances. …”
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Investigation on the Displacement Ductility Coefficient of Reinforced Concrete Columns Strengthened with Textile-Reinforced Concrete by Boxue Wang, Shiping Yin, Ming Liu

“…Then, according to FEM data, a neural network prediction model was established for the displacement ductility coefficients of TRC-strengthened columns, and a formula was proposed for calculating the displacement ductility coefficient. …”
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Bearing Fault Diagnosis of End-to-End Model Design Based on 1DCNN-GRU Network by Liu Zhiwei

“…An end-to-end fault diagnosis is proposed. A convolutional neural network (CNN) is good at mining spatial features of samples and has the advantage of “end-to-end.” …”
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Assessing Deep Learning Techniques for the Recognition of Tropical Disease in Images from Parasitological Exams by Ammar Akram Abdulrazzaq, Asaad T. Al-Douri, Abdulsattar Abdullah Hamad, Mustafa Musa Jaber, Zelalem Meraf

“…In order to automate this process, it is proposed in this work the application of deep learning methods for the detection of schistosomiasis eggs, and a comparison is made between two deep learning techniques, convolutional neural network (CNN) and structured pyramidal neural network (SPNN). …”
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Remaining Useful Life Prediction of Bearing with Vibration Signals Based on a Novel Indicator by Bo Wu, Wei Li, Ming-quan Qiu

“…In this paper, a method combining the generalized Weibull failure rate function (WFRF) and radial basis function (RBF) neural network is developed to deal with the RUL prediction of bearings. …”
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Neural Behavior Chain Learning of Mobile Robot Actions by Lejla Banjanovic-Mehmedovic, Dzenisan Golic, Fahrudin Mehmedovic, Jasna Havic

“…This paper presents a visual/motor behavior learning approach, based on neural networks. We propose Behavior Chain Model (BCM) in order to create a way of behavior learning. …”
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An Improved Image Processing Based on Deep Learning Backpropagation Technique by Yang Gao, Yue Tian

“…The use of more than one layer in the neural network improves the performance of the algorithm. …”
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Intelligent Method for Identifying Driving Risk Based on V2V Multisource Big Data by Jinshuan Peng, Yiming Shao

“…The results obtained indicated a successful identification rate of 83.6% when the neural network model was solely used to identify risky driving behavior, but this could be increased to 92.46% once corrected by the Bayesian filter. …”
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Aeroservoelastic Pitch Control of Stall-Induced Flap/Lag Flutter of Wind Turbine Blade Section by Tingrui Liu

“…A single neuron PID control strategy with improved Hebb learning algorithm and a radial basic function neural network PID algorithm are applied and performed well in the range of extreme wind speeds.…”
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Dynamic Modeling and Parameters Optimization of Large Vibrating Screen with Full Degree of Freedom by Xiaodong Yang, Jida Wu, Haishen Jiang, Wenqiang Qiu, Chusheng Liu

“…Further, the genetic algorithm is used to optimize the established neural network model, and the optimal design parameters are obtained.…”
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Intelligent model for forecasting fluctuations in the gold price by Mahdieh Tavassoli, Mahnaz Rabeei, Kiamars Fathi Hafshejani

“…The study also employed Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Multi-Layer Perceptron (MLP) neural network models in deep learning mode to predict gold price fluctuations. …”
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Analisis Perbandingan Algoritma SVM, KNN, dan CNN untuk Klasifikasi Citra Cuaca by Mohammad Farid Naufal

“…Terdapat beberapa algoritma klasifikasi citra populer yaitu K-Nearest Neighbors (KNN), Support Vector Machine (SVM), dan Convolutional Neural Network (CNN). KNN dan SVM merupakan algoritma klasifikasi dari Machine Learning sedangkan CNN merupakan algoritma klasifikasi dari Deep Neural Network. …”
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Application of Big Data Technology to Assessments of Female Ovarian Reserve Dysfunction by Xia Ji'An, Ma YunFei, Wu YiYun, Zhao YouLin, Ni HaoRang, Liu XinYan

“…In the big data platform, the random forest algorithm achieved the highest classification accuracy (89.47%), followed by the neural network (81.06%) and support vector machine (72.91%) methods. …”
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Power Forecasting of Combined Heating and Cooling Systems Based on Chaotic Time Series by Liu Hai, Song Yong, Du Qingfu

“…The neural network model will approximate the curve of output power adequately. …”
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Machine learning and AI for advancing Parkinson's disease diagnosis: exploring promising applications by Shohreh Abdollahi, Ramin Safa

“…The analysis reveals that Artificial Neural Network achieves the highest accuracy of 92.4%, surpassing Logistic Regression and Support Vector Machine. …”
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The Efficacy of Predictive Methods in Financial Statement Fraud by Mahdi Omidi, Qingfei Min, Vahab Moradinaftchali, Muhammad Piri

“…Additionally, this study examined the properties of five widely used supervised approaches, namely, multi-layer feed forward neural network (MFFNN), probabilistic neural network (PNN), support vector machine (SVM), multinomial log-linear model (MLM), and discriminant analysis (DA), applied in different real-life situations. …”
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Integrating Machine Learning for Predictive Maintenance on Resource-Constrained PLCs: A Feasibility Study by Riccardo Mennilli, Luigi Mazza, Andrea Mura

“…This study investigates the potential of deploying a neural network model on an advanced programmable logic controller (PLC), specifically the Finder Opta™, for real-time inference within the predictive maintenance framework. …”
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