Application of Functional Link Artificial Neural Network for Prediction of Machinery Noise in Opencast Mines

Abstract

Functional link-based neural network models were applied to predict opencast mining machineries noise. The paper analyzes the prediction capabilities of functional link neural network based noise prediction models vis-à-vis existing statistical models. In order to find the actual noise status in opencast mines, some of the popular noise prediction models, for example, ISO-9613-2, CONCAWE, VDI, and ENM, have been applied in mining and allied industries to predict the machineries noise by considering various attenuation factors. Functional link artificial neural network (FLANN), polynomial perceptron network (PPN), and Legendre neural network (LeNN) were used to predict the machinery noise in opencast mines. The case study is based on data collected from an opencast coal mine of Orissa, India. From the present investigations, it could be concluded that the FLANN model give better noise prediction than the PPN and LeNN model.

Prediction of Rainfall in India using Artificial Neural Network (ANN) Models

“…The algorith m consists of two steps. In the forward pass, the predicted outputs corresponding to the given inputs are evaluated as in Equation (18). In the backward pass, partial derivatives of the cost function with respect to the different parameters are propagated back through the network.…”

“…Generally, these models have high computational cost due to the availability of h idden layer. To min imize the computational cost, structures like, functional link art ificial neural network (FLANN) [16] and Legendre Neural Net work (LeNN) [17][18] were proposed. Three types of functional based artificial neural networks were applied to estimate rain fall.…”

“…FLANN structureXVII.Legendre Polynomial Equation in ANNStructure of the Legendre Neural Network[16][17][18] (LeNN) (Fig.17)is similar to FLANN.In contrast to FLANN, in wh ich trigonomet ric functions are used in the functional expansion, LeNN uses Legendre orthogonal functions. LeNN offers faster training compared to FLANN.…”

Hybrid Neuro-fuzzy Legendre-based Adaptive Control Algorithm for Static Synchronous Series Compensator

“…& D OE& 1 & 2 & n is the output of the Legendre-polynomial-based functional NN such that [16] &`D tanh…”

A Smart Amalgamation of Spectral Neural Algorithm for Nonlinear Lane-Emden Equations with Simulated Annealing

“…Legendre neural network has already been implemented successfully on nonlinear channel equalization for wireless communication [27], for prediction of machinery noise in open cast mines [28] and for nonlinear active noise control [29] but here we developed the network for the numerical simulation of nonlinear ordinary differential equations with singularity while training of network adaptive coefficients is performed by simulated annealing. Simulated annealing is a probabilistic form of the gradient descent optimization method that can escape from local optima and go on to find the global optimum in a large search space un like other methods.…”