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- W1595846175 abstract "The Explosion Locator using Artificial Neural Network (ANN) has emerged asan important research area because it can increase situational awareness in differentscenarios. Network of sensors with artificial intelligence such as artificial neuralnetwork shows a promising approach towards efficient system response. In this study,network of sensors was carefully placed in a location to efficiently gather needed data.The data gathered from these three sensors were fed to ANN for training. A twolayerfeed-forward back-propagation neural networks were designed to implementthe functional relationship. A training algorithm based on Levenberg-Marquardt wasused. During the training, important parameters such as number of epochs, networkweights and biases, number of hidden neurons, number of vectors, number of inputsand training algorithm were varied. The training stopped at cross validation and testerror increased for 30 iterations, which occurred at iteration 36. The fit is almostperfect for train, testing and cross-validation data over 0.9999 for the total response of accuracy through % error with the maximum of 0.067731 were achieved. Theresult showed that the network is trained. Lastly, it confirmed the superiority of feedforwardback-propagation with trainlm architecture with a low MSE values. Keywords: Technology, computer application, computer engineering, artificial neuralnetwork, network sensor, levenberg-marquardt, descriptive design, Philippines" @default.
- W1595846175 created "2016-06-24" @default.
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- W1595846175 date "2013-11-25" @default.
- W1595846175 modified "2023-09-24" @default.
- W1595846175 title "Explosion Locator using Artificial Neural Network" @default.
- W1595846175 doi "https://doi.org/10.7718/iamure.ijmet.v7i1.595" @default.
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