Nature inspired metaheuristic algorithms provide derivative-free solution to optimize complex problems. Cuckoo Search (CS) algorithm is one of the most modern addition to the group of nature inspired optimization metaheuristics. The Simple Recurrent Networks (SRN) were initially trained by Elman with the standard back propagation (SBP) learning algorithm which is less capable and often takes en...

RNNs have local feedback loops within the network which allows them to shop earlier accessible patterns. This network can be educated with gradient descent back propagation and optimization technique such as second-order methods; conjugate gradient, quasi-Newton, Levenberg-Marquardt have also been used for networks training [14, 15]. But still this algorithm is not definite to find the global m...

Abstract Capacity prediction of surface mount production lines is important for improving productivity, dynamic scheduling, and optimizing structure. An integrated mutual information-cuckoo search-extreme learning machine (MI-CS-ELM) model proposed the impact nonlinear high-dimensional features surface-mounted on capacity. Firstly, affecting capacity are ranked based information method, predict...