An Application of Artificial Neural Network (ANN) Process to Assess Risk in Cement Industries in Bangladesh

摘要

Today large and mid-size companies have more complex operations which involve different types of risk and arediffcult to identify the risk. To extract these risks and analyze it scientifcally, a professional risk assessment tool namelyANN is most appropriate and ?exible network technology. This paper brie?y presents Artifcial Neural Networks (ANNs),universal and highly ?exible functions, approximations for any data as an application to assess risk in cement industriesfor instance HOLCIM CEMENT BANGLADESH LIMITED has been selected to assess risks. To assess the risks a threelayer feed forward architecture of 10 risk factors which are independent and their strength of relationship was used asrelative weight of input variables. Six neurons of hidden layer and two neurons of output layer with back propagationalgorithm were designed using Neural Network Toolbox of MATLAB. The input data normalized to the range 0–0.9 andinitial weights were randomly selected. The algorithm propagates the weights backwards and then controls the weights.The factors were inputted to a MATLAB-based application program and the numbers of iterations were set 9000. Afterimplementation the overall process the adjustment weights were trained and by using adjusted weights actual outputwas found 0.63 in which predicted value was 0.66with 95.45% prediction success, the results very promising.