2013
DOI: 10.19026/rjaset.6.3545
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Developing Agent Based Modeling for Reverse Analysis Method

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Cited by 9 publications
(20 citation statements)
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“…Discrete Hopfield neural network is a class of recurrent auto-associative network [11,15]. The units in Hopfield models are mostly binary threshold unit.…”
Section: A Hopfield Modelmentioning
confidence: 99%
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“…Discrete Hopfield neural network is a class of recurrent auto-associative network [11,15]. The units in Hopfield models are mostly binary threshold unit.…”
Section: A Hopfield Modelmentioning
confidence: 99%
“…Hyperbolic tangent activation function is proven as the most commanding and robust activation function in neural network [11,15]. Therefore , we want to explore whether the robustness of this function will apply to the 3-SAT logic programming in Pattern-SAT.…”
Section: Hyperbolic Tangent Activation Functionmentioning
confidence: 99%
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“…Theoretically, the model comprises of interconnected unit called neurons, forming a network. Computation in Hopfield network is executed by collections of interconnected neurons [4,11]. Most of the literature suggest Hopfield network contains good properties including parallel execution for fast solutions to computationally intensive optimization problems with exceptionally good accuracy [9].…”
Section: A the Hopfield Neural Networkmentioning
confidence: 99%