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Xingkui Xu, Chunfeng Wu, Qingyu Hou and Zhigang Fan
As an important angle sensor of the opto-electric platform, gyro output accuracy plays a vital role in the stabilization and track accuracy of the whole system. It is known that the generally used fixed-bandwidth filters, single neural network models, or...
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Xingkui Xu, Chunfeng Wu, Qingyu Hou and Zhigang Fan
As an important angle sensor of the opto-electric platform, gyro output accuracy plays a vital role in the stabilization and track accuracy of the whole system. It is known that the generally used fixed-bandwidth filters, single neural network models, or...
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Amine Bensaid,Bouchra Bouqata,Ralph Palliam
AbstractThere are numerous methods for estimating forward interest rates as well as many studies testing the accuracy of these methods. The approach proposed in this study is similar to the one in previous works in two respects: firstly, a Monte Carlo si...
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Amine Bensaid,Bouchra Bouqata,Ralph Palliam
AbstractThere are numerous methods for estimating forward interest rates as well as many studies testing the accuracy of these methods. The approach proposed in this study is similar to the one in previous works in two respects: firstly, a Monte Carlo si...
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Nikita Andriyanov
The problem solved in the article is connected with the increase in the efficiency of phraseological radio exchange message recognition, which sometimes takes place in conditions of increased tension for the pilot. For high-quality recognition, signal pr...
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Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah and Malak EL-Amir
Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as...
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Mohammad Mustafa Taye
In recent years, deep learning (DL) has been the most popular computational approach in the field of machine learning (ML), achieving exceptional results on a variety of complex cognitive tasks, matching or even surpassing human performance. Deep learnin...
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Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc...
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Ishaani Priyadarshini
Autism spectrum disorder (ASD) has been associated with conditions like depression, anxiety, epilepsy, etc., due to its impact on an individual?s educational, social, and employment. Since diagnosis is challenging and there is no cure, the goal is to max...
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Bing Long, Kunping Wu, Pengcheng Li and Meng Li
The remaining useful life (RUL) prediction for hydrogen fuel cells is an important part of its prognostics and health management (PHM). Artificial neural networks (ANNs) are proven to be very effective in RUL prediction, as they do not need to understand...
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Andrea Menapace, Ariele Zanfei and Maurizio Righetti
The evolution of smart water grids leads to new Big Data challenges boosting the development and application of Machine Learning techniques to support efficient and sustainable drinking water management. These powerful techniques rely on hyperparameters ...
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Fabio Massimo Zanzotto, Giorgio Satta and Giordano Cristini
Parsing is a key task in computer science, with applications in compilers, natural language processing, syntactic pattern matching, and formal language theory. With the recent development of deep learning techniques, several artificial intelligence appli...
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Andrea Maria N. C. Ribeiro, Pedro Rafael X. do Carmo, Iago Richard Rodrigues, Djamel Sadok, Theo Lynn and Patricia Takako Endo
To minimise environmental impact, to avoid regulatory penalties, and to improve competitiveness, energy-intensive manufacturing firms require accurate forecasts of their energy consumption so that precautionary and mitigation measures can be taken. Deep ...
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Alessandra Caggiano, Giulio Mattera and Luigi Nele
The drilling of carbon fiber-reinforced plastic (CFRP) materials is a key process in the aerospace industry, where ensuring high product quality is a critical issue. Low-quality of final products may be caused by the occurrence of drilling-induced defect...
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Christos Bormpotsis, Mohamed Sedky and Asma Patel
In the realm of foreign exchange (Forex) market predictions, Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) have been commonly employed. However, these models often exhibit instability due to vulnerability to data perturbations...
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Theofani Psomouli, Ioannis Kansizoglou and Antonios Gasteratos
The increase in the concentration of geological gas emissions in the atmosphere and particularly the increase of methane is considered by the majority of the scientific community as the main cause of global climate change. The main reasons that place met...
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Samkele S. Tfwala, Yu-Min Wang
Pág. 1 - 15
Sediment in river is usually transported during extreme events related to intense rainfall and high river flows. The conventional means of collecting data in such events are risky and costly compared to water discharge measurements. Hence, the lack of se...
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Mohammed Saïd Kasttet, Abdelouahid Lyhyaoui, Douae Zbakh, Adil Aramja and Abderazzek Kachkari
Recently, artificial intelligence and data science have witnessed dramatic progress and rapid growth, especially Automatic Speech Recognition (ASR) technology based on Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs). Consequently, new end-to-...
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Nasser Alenezi, Abdalrahman Alsulaili and Mohamad Alkhalidi
Creating an efficient model for predicting sea level fluctuations is essential for climate change research. This study examined the effectiveness of utilizing Artificial Neural Networks (ANNs), particularly the recurrent network approach. ANNs were chose...
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Anne Fischer, Alexandre Beiderwellen Bedrikow, Iris D. Tommelein, Konrad Nübel and Johannes Fottner
As in manufacturing with its Industry 4.0 transformation, the enormous potential of artificial intelligence (AI) is also being recognized in the construction industry. Specifically, the equipment-intensive construction industry can benefit from using AI....
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