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Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification
Published 2013“…Traditional training algorithms have some drawbacks such as local minima and its slowness.Therefore, evolutionary algorithms are utilized to train neural networks to overcome these issues.This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm.The proposed method tested and verified by training an ANN with well-known benchmarking problems.Two criteria used to evaluate the proposed method were overall training time and classification accuracy.The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time.…”
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Adapting and enhancing mussels wandering optimization algorithm for supervised training of neural networks
Published 2015“…In addition, training NN is still highly-time consuming. The Mussels Wandering Optimization (MWO) is a recent metaheuristic optimization algorithm inspired ecologically by mussels movement behavior. …”
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The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
Published 2001“…Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. …”
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Electrocardiogram based heart disease diagnosis using artificial intelligence
Published 2015“…Accordingly, the first step is an image segmentation method using proposed thresholding algorithms has been used to locate objects and boundaries of the ECG signal and background grid lines in the ECG images. …”
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Discriminative feature representation for Malay children’s speech recognition / Seyedmostafa Mirhassani
Published 2015“…In case of multiple filterbanks the cepstral features are used in different experts for performing classification based on different representation of speeches. …”
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