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Showing 20 of 3,783 academic articles

A Complex Network Epidemiological Approach for Infectious Disease Spread Control with Time-Varying Connections

Alma Y. Alanis, Gustavo Munoz-Gomez, Nancy F. Ramirez, Oscar D. Sanchez et al. • Algorithms (2024)

This work introduces an impulsive neural control algorithm designed to mitigate the spread of epidemic diseases. The objective of this paper is the development of a vaccination strategy based on a PIN-type impulsive controller based on an o...

DOAJ Open Access (DOAJ) DOI: 10.3390/a17120577

Neural Network Acceptability Judgments

Alex Warstadt, Amanpreet Singh, Samuel R. Bowman • Transactions of the Association for Computational Linguistics (2019)

This paper investigates the ability of artificial neural networks to judge the grammatical acceptability of a sentence, with the goal of testing their linguistic competence. We introduce the Corpus of Linguistic Acceptability (CoLA), a set ...

OPENALEX cc-by DOI: https://doi.org/10.1162/tacl_a_00290

Artificial Neural Networks

Ajith Abraham • Wiley eBooks (2005)

Abstract Artificial neural networks are useful tools that have been applied successfully in a broad range of signal‐processing problems. From a signal‐processing perspective, their ability to adapt continuously to new data allows them to tr...

OPENALEX DOI: https://doi.org/10.1002/0471497398.mm421

An Introduction to Convolutional Neural Networks

Keiron O’Shea, Ryan Nash • arXiv (Cornell University) (2015)

The field of machine learning has taken a dramatic twist in recent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models are able to far exceed the performance of previous forms of art...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1511.08458

Artificial Neural Networks

Hojjat Adeli, Xiaomo Jiang • CRC Press eBooks (2008)

An artificial neural network (ANN) is a functional abstraction of the biologic neural structures of the central nervous system (Aleksander and Morton 1993; Rudomin et al. 1993; Arbib 1995; Anderson 1995). It is essentially a simple mathemat...

OPENALEX DOI: https://doi.org/10.1201/9781482281767-9

On Calibration of Modern Neural Networks

Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger • arXiv (Cornell University) (2017)

Confidence calibration -- the problem of predicting probability estimates representative of the true correctness likelihood -- is important for classification models in many applications. We discover that modern neural networks, unlike thos...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1706.04599

Tailoring Mission Effectiveness and Efficiency of a Ground Vehicle Using Exergy-Based Model Predictive Control (MPC)

Robert Jane, Tae Young Kim, Emily Glass, Emilee Mossman et al. • Energies (2021)

To ensure dominance over a multi-domain battlespace, energy and power utilization must be accurately characterized for the dissimilar operational conditions. Using MATLAB/Simulink in combination with multiple neural networks, we created a m...

DOAJ Open Access (DOAJ) DOI: 10.3390/en14196049

Monthly Evapotranspiration Modeling in the Absence of Climatic Data Using the Soft Computing Methods in West and Northwest of Iran

Saman Maroufpour, Eisa Maroufpoor, Hadi Sanikhani • مهندسی منابع آب (2017)

Evapotranspiration (ET0), a major component of the hydrologic cycle, is important in water resources development and irrigation planning. The ET0 for west and northwest of Iran was estimated using the FAO Penman-Montieth method (FAO-56) as ...

DOAJ Open Access (DOAJ)

Spatial analysis and risk mapping of Fasciola hepatica infection in dairy cattle at the Peruvian central highlands

Daniel Alexis Zárate-Rendón, David Godoy Padilla, Samuel Pizarro Carcausto, Alberto del Águila et al. • Parasite Epidemiology and Control (2023)

This study aimed to develop maps for Fasciola hepatica infection occurrence in dairy cattle in the districts of Matahuasi and Baños in the Peruvian central highlands. For this, a model based on the correlation between environmental variable...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.parepi.2023.e00329

Application of Artificial Neural Networks for Corrosion Behavior of Ni–Zn Electrophosphate Coating on Galvanized Steel and Gene Expression Programming Models

Malihe Zeraati, Hossein Abbasi, Parvin Ghaffarzadeh, Narendra Pal Singh Chauhan et al. • Frontiers in Materials (2022)

Zn–Ni electrophosphate coating is one of the most commonly used materials in industrial applications. The corrosion resistance of this coating is very important in order to achieve the minimum corrosion current of the Zn–Ni electrophosphate...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmats.2022.823155

Fallback Variable History NNLMs: Efficient NNLMs by precomputation and stochastic training.

Francisco J Zamora-Martínez, Salvador España-Boquera, Maria Jose Castro-Bleda, Adrian Palacios-Corella • PLoS ONE (2018)

This paper presents a new method to reduce the computational cost when using Neural Networks as Language Models, during recognition, in some particular scenarios. It is based on a Neural Network that considers input contexts of different le...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0200884

Artificial neural networks

Judith E. Dayhoff, James M. DeLeo • Cancer (2001)

Artificial neural networks now are used in many fields. They have become well established as viable, multipurpose, robust computational methodologies with solid theoretic support and with strong potential to be effective in any discipline, ...

OPENALEX Open Access DOI: https://doi.org/10.1002/1097-0142(20010415)91:8+<1615::aid-cncr1175>3.0.co;2-l

Neural Network Learning

Martin Anthony, Peter L. Bartlett • Cambridge University Press eBooks (1999)

First published in 1999, this book describes theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. R...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511624216

An Introduction to Neural Networks

James A. Anderson • The MIT Press eBooks (1995)

An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain funct...

OPENALEX DOI: https://doi.org/10.7551/mitpress/3905.001.0001

Neural networks and their applications

Chris M. Bishop • Review of Scientific Instruments (1994)

Neural networks provide a range of powerful new techniques for solving problems in pattern recognition, data analysis, and control. They have several notable features including high processing speeds and the ability to learn the solution to...

OPENALEX DOI: https://doi.org/10.1063/1.1144830

On neural networks.

Jiří Beneš • Czech digital mathematics library (1990)

JIŘÍ BENEŠTypical neural network models representing a broad survey of actual trends are considered in an unifying way as Complexes subject to specific control systems, called Formators which may have a two-level arrangement and incorporate...

OPENALEX Open Access