Acoustic Model with Multiple Lexicon Types for Indonesian Speech Recognition by Taufik Fuadi Abidin, Alim Misbullah, Ridha Ferdhiana, Laina Farsiah, Muammar Zikri Aksana, Hammam Riza

“…The quality of the dataset was evaluated using a deep neural network. The time delay neural network (TDNN) was used to build the acoustic model by applying the alignment data from the Gaussian mixture model-hidden Markov model (GMM-HMM). …”
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A New Strategy for Short-Term Load Forecasting by Yi Yang, Jie Wu, Yanhua Chen, Caihong Li

“…Considering that an individual forecasting model usually cannot work very well for STLF, a hybrid model based on the seasonal ARIMA model and BP neural network is presented in this paper to improve the forecasting accuracy. …”
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Hydraulic Fracturing Breakdown Pressure and Prediction of Maximum Horizontal In Situ Stress by Ali Lakirouhani, Somaie Jolfaei

“…Using the numerical model, 1,456 datasets were prepared to train an artificial neural network to predict the maximum horizontal stress. …”
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Vessel Navigation Behavior Analysis and Multiple-Trajectory Prediction Model Based on AIS Data by He Ma, Yi Zuo, Tieshan Li

“…Second, we design an integrated model for simultaneous prediction of multiple trajectories using the proposed features and employ the long short-term memory (LSTM)-based neural network and recurrent neural network (RNN) to pursue this time series task. …”
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A parallel spatiotemporal deep learning network for highway traffic flow forecasting by Dongxiao Han, Juan Chen, Jian Sun

“…The parallel-connected structure of convolutional neural network and long short-term memory reflects much powerful performance in traffic flow prediction. …”
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Prediction of Metro Train-Induced Tunnel Vibrations Using Machine Learning Method by Zhuosheng Xu, Meng Ma, Zikai Zhou, Xintong Xie, Haoxiang Xie, Bolong Jiang, Zhongshuai Zhang

“…Two types of method, back propagation neural network (BPNN) and generalised regression neural network (GRNN) were employed, which can make full use of characteristics of measured samples and reduce the data noise. …”
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Adaptive and Resilient Flight Control System for a Small Unmanned Aerial System by Gonzalo Garcia, Shahriar Keshmiri

“…The real-time artificial neural network parameter identification is done using the sliding mode learning concept and a modified version of the self-adaptive Levenberg algorithm. …”
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Color imaging using a system based on 3 diffractive lenses by S. Stepanenko, V. Evdokimova, M. Petrov, R. Skidanov, A. Nikonorov

“…The study proposes a false edge level criterion (FEL) for evaluating the neural network-aided reconstruction.…”
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A Simultaneous Fault Diagnosis Method Based on Cohesion Evaluation and Improved BP-MLL for Rotating Machinery by Yixuan Zhang, Rui Yang, Mengjie Huang, Yu Han, Yiqi Wang, Yun Di, Dongke Su, Qidong Lu

“…An effective global error function is proposed in BP-MLL neural network by modifying distance function to improve both generalization ability and fault diagnostic ability of full-labeled and nonlabeled situations. …”
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Performance Prediction for Higher Education Students Using Deep Learning by Shuping Li, Taotang Liu

“…The proposed method used deep neural network in prediction by extracting informative data as a feature with corresponding weights. …”
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Image Reconstruction for High-Performance Electrical Capacitance Tomography System Using Deep Learning by Yanpeng Zhang, Deyun Chen

“…Therefore, an artificial neural network of the capacitance (ANNoC) system is introduced to estimate capacitance measurements.…”
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Labiodentals /r/ here to stay: Deep learning shows us why by Hannah King, Emmanuel Ferragne

“…Our results suggest that there is a recognisable difference between the lip postures for /r/ and /w/, which a convolutional neural network is able to detect with a very high degree of accuracy. …”
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Research and Model Prediction on the Performance of Recycled Brick Powder Foam Concrete by Hongyang Xie, Jianjun Dong, Yong Deng, Yiwen Dai

“…Five machine learning models, namely, back propagation neural network improved by particle swarm optimization (PSO-BP), support vector machine (SVM), multiple linear regression (MLR), random forest (RF), and back propagation neural network (BP), were used to predict the compressive strength of recycled brick powder foam concrete, and the PSO-BP model was found to have obvious advantages in terms of prediction accuracy and model stability. …”
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Quantitative Detection of Financial Fraud Based on Deep Learning with Combination of E-Commerce Big Data by Jian Liu, Xin Gu, Chao Shang

“…This method builds a deep neural network model with multiple hidden layers, learns the characteristic expression of the data, and fully depicts the rich internal information of the data, thereby improving the accuracy of financial fraud detection. …”
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Hyperspectral Image Classification Based on Attentional Residual Networks by Ning Wang, Xin Pan, Xiaoling Luo, Xiaojing Gao

“…Aiming at the problem that the features extracted by the existing convolutional neural Network model are insufficient and the more important information lacks key Attention in the process of hyperspectral image classification, this paper designs an Attention Residual Network (ARN). …”
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EMIKNet: Expanding Multiple-Instance Inverse Kinematics Network for Multiple End-Effector and Multiple Solutions by Youn-Jae Go, Jun Moon

“…In this letter, we propose a neural network-based IK approach to efficiently address the IK challenges in complex robotic systems with multiple end-effectors and methods for obtaining multiple solutions. …”
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The Co-Movement between International and Emerging Stock Markets Using ANN and Stepwise Models: Evidence from Selected Indices by Dania Al-Najjar

“…To validate the availability of the linkage between the indices, the author includes various tests of a correlation coefficient, stepwise regression analysis, and artificial neural network (ANN). Despite the results indicating that the ANN is more efficient than linear regression in investigating the availability of the relationship between ASEI and international indices, stepwise regression and neural network support this relationship. …”
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Enhancing fingerprint identification using Fuzzy-ANN minutiae matching by S.P. Singh, Dinesh Kumar Nishad, Saifullah Khalid

“…‘Based on Minutiae and Neural Networks,’ this paper introduces a robust fingerprint identification system that significantly enhances the accuracy of matching fingerprints, especially those altered due to various reasons such as scars or mutilations. …”
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Structured Dynamics in the Algorithmic Agent by Giulio Ruffini, Francesca Castaldo, Jakub Vohryzek

“…Then, adopting a generic neural network as a proxy for the agent dynamical system and drawing parallels to Noether’s theorem in physics, we demonstrate that data tracking forces the agent to mirror the symmetry properties of the generative world model. …”
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Computer Vision with Error Estimation for Reduced Order Modeling of Macroscopic Mechanical Tests by Franck Nguyen, Selim M. Barhli, Daniel Pino Muñoz, David Ryckelynck

“…The output of the convolutional neural network being a model, an error estimator, is proposed to assess the accuracy of this output. …”
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