Abstract
A Meta-Heuristic Algorithms Optimization (MAHO) is inspired by nature. The Artificial neural network (ANN) has been shown to be successful in a variety of applications, including machine learning. ANNs were optimized using meta-optimization methods to enhance classification performance and predictions. The fundamental objective of combining a meta-heuristic algorithm (MHAO) with an artificial neural network (ANN) is to train the network to update the weights. The training would be speedier than with a standard ANN since it will use a meta-heuristic method with global optimal searching capability to avoid local minimum and will also optimize difficult problems. will discuss some of these meta-heuristic algorithms using ANN as they are applied to common data sets, as well as real-time specific classification and prediction experiences. In order to give researchers motivational insights into their own fields of application.
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