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Neural Network Applications [PDF]
, 1995 Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in ...
Jain, L.C., Veelenturf, L.P.J., Vonk, E.
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Prediction of Free Swell Index for the Expansive Soil Using Artificial Neural Networks [PDF]
Journal of Soft Computing in Civil Engineering, 2019 Prediction of the free swell index of the expansive soil using artificial neural network has been presented in this paper. Input parameters for the artificial neural network model were plasticity index and shrinkage index, while the output was the free ...
Rakesh Dutta +2 more
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Artificial Neural Networks [PDF]
, 2015 Polynomial classifiers can model decision surfaces of any shape; and yet their practical utility is limited because of the easiness with which they overfit noisy training data, and because of the sometimes impractically high number of trainable parameters.
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Optimal Artificial Neural Network Type Selection Method for Usage in Smart House Systems
Sensors, 2020 In the process of the “smart” house systems work, there is a need to process fuzzy input data. The models based on the artificial neural networks are used to process fuzzy input data from the sensors. However, each artificial neural network has a certain
Vasyl Teslyuk +3 more
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Neural Networks: Implementations and Applications [PDF]
, 1996 Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in ...
Jain, L.C., Veelenturf, L.P.J., Vonk, E.
core +2 more sources
Nature Precedings, 2011 In the postgenomic era, computational methods are being used in diverse areas like drug discovery, robotics, weather forecasting etc. Computational methods are incorporated with various programmes that are further instructed with complex algorithms based on different logistic approaches.
Smrita Singh, Smrita Singh
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Implementation of Backpropagation Artificial Network Methods for Early Children’s Intelligence Prediction [PDF]
E3S Web of Conferences, 2021 Intelligence is the ability to process certain types of information derived from human biological and psychological factors. This study aims to implement a Backpropagation artificial neural network for prediction of early childhood intelligence and how ...
Budiman I +4 more
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The High Time Resolution Universe Survey VI: An Artificial Neural Network and Timing of 75 Pulsars [PDF]
, 2012 We present 75 pulsars discovered in the mid-latitude portion of the High Time Resolution Universe survey, 54 of which have full timing solutions. All the pulsars have spin periods greater than 100 ms, and none of those with timing solutions are in ...
A Jameson +69 more
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SIR: A New Wireless Sensor Network Routing Protocol Based on Artificial Intelligence [PDF]
, 2006 Currently, Wireless Sensor Networks (WSNs) are formed by hundreds of low energy and low cost micro-electro-mechanical systems. Routing and low power consumption have become important research issues to interconnect this kind of networks.
Barbancho Concejero, Antonio +3 more
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Estimation of soil properties by an artificial neural network
Magazine of Civil Engineering, 2022 Empirical dependencies are often used in various fields of geotechnics and civil engineering. The existing empirical formulas are mainly developed with the use of regression and multiple regression.
Ofrikhter Ian +3 more
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