Designing a DSS to explore cement mines using fuzzy neural networks
Elham Soleimani Vostakolaee, Bita Amirshahi · 2015
Cement industry is one of the most important manufacturing industries. Exploration of cement materials requires equipment and highly qualified manpower. In addition, the design of road construction for the extraction of minerals is time-consuming and costly. Therefore, designing a decision support system to predict areas that have the potential to lay the foundation of this useful material can bring profitability for many stakeholders. In this study, we design a DSS to explore cement mines by fuzzy neural networks. At first all parts of Bushehr province were visited and 72 samples were taken from various units. Then the number of samples that are economically justified, and can be used with each other as a complement for cement production, considered as a single region and cement calculations have been done for them. Finally the results of chemical analysis of suitable and unsuitable zones was used as training and test data in MATLAB. The simulation results show that RMSC for two basic materials of cement are 0.32 and 0.22, which indicate a high precision in comparison with same works.