ANFIS to Quantify Maintenance Cost of IT Services in Telecommunication Company

Abstract

The maintenance cost predication of information technology (IT) regarding their important role and well-time availability in organization is valuable for IT managers. Therefore their decision originated from the predication might be great effect on organizational budgeting, planning, and strategy management. In this regard, having enough knowledge of IT system behavior and their cost forecasting may help IT managers to develop their organization. In this chapter, adaptive neuro-fuzzy inference system (ANFIS) with capability of modeling and predication is introduced, respectively, for quantifying information technology services and their maintenance cost in one of the telecommunication companies in Iran. Because of easy accessibility in finding parameters and also prevention from the complexity of information resulting from some available services in case study organization, automation services are selected by author as kind of user-involved and widely used in finding and studying on the variable data for implementation of the model.

Compensatory Adaptive Neural Fuzzy Inference System

“…In the near past, ANFIS (Adaptive Neural Fuzzy Inference System) models have become very popular for two reasons: the first reason is that in calibrating of non-linear relationships they offer more advantages over conventional modeling techniques, namely the ability to handle large amounts of noisy data from dynamic and non-linear systems, particularly when the underlying physical relationships are not fully understood. The second reason is that they facilitate the solving of linear systems which include the interpolation modeling such as time series [5].…”