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Alessandro Massaro
In the proposed paper, an artificial neural network (ANN) algorithm is applied to predict the electronic circuit outputs of voltage signals in Industry 4.0/5.0 scenarios. This approach is suitable to predict possible uncorrected behavior of control circu...
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Sepideh Molaei, Stefano Cirillo and Giandomenico Solimando
MicroRNAs (miRNAs) play a crucial role in cancer development, but not all miRNAs are equally significant in cancer detection. Traditional methods face challenges in effectively identifying cancer-associated miRNAs due to data complexity and volume. This ...
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Ioannis G. Tsoulos and V. N. Stavrou
In the current research, we consider the solution of dispersion relations addressed to solid state physics by using artificial neural networks (ANNs). Most specifically, in a double semiconductor heterostructure, we theoretically investigate the dispersi...
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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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Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai and Yen-Jen Chang
Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybri...
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Seda Sahin and Ayse Torun
This study was primarily conducted to investigate the potential use of pumpkin seed oil in biodiesel production. Initially, the fatty acid composition of oils extracted from discarded pumpkin seeds was determined. Then, biodiesel produced from discarded ...
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Ahmed Skhiri, Ali Ferhi, Anis Bousselmi, Slaheddine Khlifi and Mohamed A. Mattar
A correct determination of irrigation water requirements necessitates an adequate estimation of reference evapotranspiration (ETo). In this study, monthly ETo is estimated using artificial neural network (ANN) models. Eleven combinations of long-term ave...
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Stanislav Letkovský, Sylvia Jencová and Petra Va?anicová
Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial in...
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Dthenifer Cordeiro Santana, Gustavo de Faria Theodoro, Ricardo Gava, João Lucas Gouveia de Oliveira, Larissa Pereira Ribeiro Teodoro, Izabela Cristina de Oliveira, Fábio Henrique Rojo Baio, Carlos Antonio da Silva Junior, Job Teixeira de Oliveira and Paulo Eduardo Teodoro
Using multispectral sensors attached to unmanned aerial vehicles (UAVs) can assist in the collection of morphological and physiological information from several crops. This approach, also known as high-throughput phenotyping, combined with data processin...
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Andreas G. Savva, Theocharis Theocharides and Chrysostomos Nicopoulos
Nowadays, due to their excellent prediction capabilities, the use of artificial neural networks (ANNs) in software has significantly increased. One of the most important aspects of ANNs is robustness. Most existing studies on robustness focus on adversar...
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