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Academic Articles & Research Papers
Showing 20 of 1,656 academic articles
Frauke Günther, Stefan Gerd Fritsch • The R Journal
(2010)
Artificial neural networks are applied in many situations.neuralnet is built to train multi-layer perceptrons in the context of regression analyses, i.e. to approximate functional relationships between covariates and response variables.Thus...
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Open Access
DOI: https://doi.org/10.32614/rj-2010-006
Kishan G. Mehrotra, Chilukuri Krishna Mohan, Sanjay Ranka • The MIT Press eBooks
(1996)
Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them. The authors, who have ...
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DOI: https://doi.org/10.7551/mitpress/2687.001.0001
Su-Hsin Huang, Joon-Khim Loh, Jinn-Tsong Tsai, Ming-Feng Houg et al. • Chinese Journal of Cancer
(2017)
Abstract Background Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years. This study aimed to validate the use of the artificial neural network (ANN) model to predict the 5-year mortality of breast...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s40880-017-0192-9
Zhiquan He, Meshari Alazmi, Jingfen Zhang, Dong Xu • PLoS ONE
(2013)
Quality assessment (QA) for predicted protein structural models is an important and challenging research problem in protein structure prediction. Consensus Global Distance Test (CGDT) methods assess each decoy (predicted structural model) b...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0074006
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 ...
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DOI: https://doi.org/10.1162/tacl_a_00290
Christoph Bergmeir, José M. Benítez • Journal of Statistical Software
(2012)
Neural networks are important standard machine learning procedures for classification and regression. We describe the R package RSNNS that provides a convenient interface to the popular Stuttgart Neural Network Simulator SNNS. The main feat...
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DOI: https://doi.org/10.18637/jss.v046.i07
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...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1511.08458
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...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1706.04599
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)
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
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
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, ...
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Open Access
DOI: https://doi.org/10.1002/1097-0142(20010415)91:8+<1615::aid-cncr1175>3.0.co;2-l
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...
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DOI: https://doi.org/10.1017/cbo9780511624216
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...
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DOI: https://doi.org/10.7551/mitpress/3905.001.0001
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...
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DOI: https://doi.org/10.1063/1.1144830
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...
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Open Access
Chao Wang, Jun-Feng Hao, He Huang, Wang Zou et al. • IEEE Access
(2025)
Traffic flow forecasting is a critical and essential technology in the field of Intelligent Transportation Systems (ITS), as it plays a pivotal role in optimizing traffic management, improving road safety, and enhancing the overall efficien...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3553535
Fathaddin Muhammad Taufiq, Sari Alvita Kumala, Sutansyah Daddy, Ulfah Baiq Maulinda et al. • E3S Web of Conferences
(2024)
Relative permeability is a substantial parameter for estimating multi-phase fluid flow in porous rocks. It is a complex physical property that is influenced by the behavior and interactions between the fluid and rock phases. Relative permea...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/e3sconf/202450003019
Enrique González-Plaza, David García, Jesús-Ignacio Prieto • Inventions
(2023)
Stirling engines are currently of interest due to their adaptability to a wide range of energy sources. Since simple tools are needed to guide the sizing of prototypes in preliminary studies, this paper proposes two groups of simple models ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/inventions8040088
Wu Huiyong, Zunlong Wang • PLoS ONE
(2025)
With the increasing complexity and prosperity of global financial markets, stock market forecasting plays a critical role in investment decision-making, market regulation, and economic planning. This study proposes a hybrid prediction model...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0330324