Designing an Adaptive Nuero-Fuzzy Inference System for Evaluating the Business Intelligence System Implementation in Software Industry

Document Type: Research Paper

Authors

1 Assistant Prof., Industrial Management, Allameh Tabataba’i University, Management and Accounting College ,Tehran, Iran

2 MSc., Information Technology Management, University of Tehran, Management College, Tehran, Iran

Abstract

The main goal of research is designing an adaptive nuero-fuzzy inference system for evaluating the implementation of business intelligence systems in software industry. Iranian software development organizations have been facing a lot of problems in case of implementing business intelligence systems. This system would be helpful in recognizing the conditions and prerequisites of success or failure. Organizations can recalculate the neuro-fuzzy system outputs with some considerations on various inputs to figure out which inputs have the most effect on the implementation outputs. By resolving the problems on inputs, organizations can achieve a better level of implementation success. The designed system has been trained by a data set and afterwards, it has been evaluated. The trained system has reached the error value of 0.08. Eventually, some recommendations have been provided for software development firms on the areas that might need more considerations and improvements.

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Main Subjects


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