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Academic Articles & Research Papers
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David M. Skapura (1995)
Foundations. Motivation. Neural-Network Fundamentals. Single Neuron Computations. Network Computations. Network Simulation. Foundations Summary. Suggested Readings. Bibliography. Paradigms. The Backpropagation Network. The Counterpropagatio...
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Engin Derya Gezer, Abdullah Uğur Birinci, Aydın Demir, Hasan Öztürk et al. • BioResources
(2024)
The primary aim of this work was to determine the effects of production parameters, such as wood species and timber strength classes, on some mechanical properties of cross-laminated timber (CLT) panels using artificial neural network (ANN)...
DOAJ
Open Access (DOAJ)
Timothée Corchia, Bertrand Bonan, Nemesio Rodríguez-Fernández, Gabriel Colas et al. • Remote Sensing
(2023)
In this work, Advanced SCATterometer (ASCAT) backscatter data are directly assimilated into the interactions between soil, biosphere, and atmosphere (ISBA) land surface model using Meteo-France’s global Land Data Assimilation System (LDAS-M...
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Open Access (DOAJ)
DOI: 10.3390/rs15174258
Chunxu Qin, Yiran Ma, Huijuan Liang, Zhifan Wang et al. • Modelling
(2026)
The end-winding insulation structure of stator windings in pumped-storage generator units is complex, with pronounced electric field concentration under out-of-phase conditions, making them critical concerns in insulation design and conditi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/modelling7050190
Kevin M. Swingler (1996)
Techniques for building neural networks: introduction what are neural networks? how does neural computing differ from traditional programming? how are neural networks built? how do neural networks learn? what do I need to build an MLP? the ...
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Qi‐Jun Zhang, K.C. Gupta • Artech House, Inc. eBooks
(2000)
From the Publisher:
Discover the new, unconventional alternatives for conquering RF and microwave design and modeling problems using neural networks information processing systems that can learn, generalize, and even allow model developm...
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Marcus D. Odom, Ramesh Sharda • International Joint Conference on Neural Networks (IJCNN)
(1990)
A neural network model is developed for prediction of bankruptcy, and it is tested using financial data from various companies. The same set of data is analyzed using a more traditional method of bankruptcy prediction, multivariate discrimi...
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DOI: https://doi.org/10.1109/ijcnn.1990.137710
Jake Ryan, Meng-Jang Lin, Risto P Miikkulainen (1997)
With the rapid expansion of computer networks during the past few years, security has become a crucial issue for modern computer systems. A good way to detect illegitimate use is through monitoring unusual user activity. Methods of intrusio...
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Juan F. Saldarriaga, Fabio Freire, Jose Freire • Chemical Engineering Transactions
(2018)
The minimum spouting velocity is one of the fundamental parameters in the application of the conical spouted bed pyrolysis, gasification and combustion, therefore it is necessary the adequate calculation and the use of a correlation with go...
DOAJ
Open Access (DOAJ)
DOI: 10.3303/CET1870208
Ye Yuan, Yongtong Zhu, Jiaqi Wang, Ruoshi Li et al. • Frontiers in Neuroscience
(2023)
IntroductionSpiking neural networks (SNNs), inspired by biological neural networks, have received a surge of interest due to its temporal encoding. Biological neural networks are driven by multiple plasticities, including spike timing-depen...
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Open Access (DOAJ)
DOI: 10.3389/fnins.2023.1224752
P. Jagadesh, J. Harshini, D. Arul, Solomon Oyebisi et al. • Discover Civil Engineering
(2026)
Abstract This study predicts the Air Quality Index (AQI) in the Coimbatore region using Artificial Neural Networks (ANN) to enhance air quality management and environmental science. The researchers measured six input variables over a two-ye...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44290-026-00423-z
Qingyang Xiao, Kaiyuan Liu, Yuhui Hong, Haixu Tang • ACS in focus
(2024)
In recent years, breakthroughs in artificial intelligence (AI) have dramatically transformed many fields. Developments in neural networks primarily drive the advances. These powerful models have demonstrated unprecedented capabilities in le...
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DOI: https://doi.org/10.1021/acsinfocus.7e8012
Mikhail Fedotov, Viktor Korotitsky, Sergei Koveshnikov • Nanomaterials
(2024)
Resistive random-access memory (RRAM) is a crucial element for next-generation large-scale memory arrays, analogue neuromorphic computing and energy-efficient System-on-Chip applications. For these applications, RRAM elements are arranged i...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/nano14080668
Xianfa Shi, Miao Su, Keun-sik Park • Journal of Theoretical and Applied Electronic Commerce Research
(2026)
Cross-border e-commerce offers consumers broader product access, yet uncertainty surrounding returns continues to suppress online purchase decisions. This study conceptualizes digital local return services as a digital assurance mechanism i...
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Open Access (DOAJ)
DOI: 10.3390/jtaer21060165
RT Pramod, Michael A Cohen, Joshua B Tenenbaum, Nancy Kanwisher • eLife
(2022)
Successful engagement with the world requires the ability to predict what will happen next. Here, we investigate how the brain makes a fundamental prediction about the physical world: whether the situation in front of us is stable, and henc...
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Open Access (DOAJ)
DOI: 10.7554/eLife.71736
Sudheesh Parathakkatt, Vaisakh Kizhuveetil, Gokul G. K., Rajashree Ajay Markandewar • eXPRESS Polymer Letters
(2026)
Worm-like micelles (WLMs) are dynamic, self-assembling supramolecular structures that exhibit complex viscoelastic behaviour due to their ability to undergo reversible scission, fusion, branching, and sequence rearrangement. This review pro...
DOAJ
Open Access (DOAJ)
DOI: 10.3144/expresspolymlett.2026.36
Johann Gasteiger, Jure Zupan • Angewandte Chemie International Edition in English
(1993)
Abstract The capabilities of the human brain have always fascinated scientists and led them to investigate its inner workings. Over the past 50 years a number of models have been developed which have attempted to replicate the brain's vario...
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DOI: https://doi.org/10.1002/anie.199305031
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
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...
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DOI: https://doi.org/10.1201/9781482281767-9