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Determining amount IT budgeting for each year is heavily complicated. IT creates a lot of cost for organization if IT managers do not have enough knowledge about cost management. Therefore, right recognition of cost factors can be helpful to cost prediction in the area to support enterprise for cost-effectiveness. In this regard, maintenance system cost predication of IT considering to their important role and well-time availability of the system in organization is valuable for IT managers. In the study, ANFIS (adoptive Neuro-Fuzzy Inference system) with capability of modeling and predication…mehr

Produktbeschreibung
Determining amount IT budgeting for each year is heavily complicated. IT creates a lot of cost for organization if IT managers do not have enough knowledge about cost management. Therefore, right recognition of cost factors can be helpful to cost prediction in the area to support enterprise for cost-effectiveness. In this regard, maintenance system cost predication of IT considering to their important role and well-time availability of the system in organization is valuable for IT managers. In the study, ANFIS (adoptive Neuro-Fuzzy Inference system) with capability of modeling and predication is selected respectively for quantifying IT services and their maintenance cost. ANFIS is suggested as a new model and technique for cost forecasting tool. To show capability of the model operation, it is experienced on Automation services of one of the organization in Iran. Because of easily accessibility to finding parameters, Automation services is selected as kind of user-involved and widely -used studying on the variables data to develop model. This research can be useful for IT managers in organization to estimate the intangible costs of IT depend on type of system of their organization
Autorenporträt
Leila Moradi, M.Sc., Information Technology Management & Advanced Information System, Forscherin und Ausgebildete, Abteilung für IT, Wirtschaft, Management, Universität für Wissenschaft und Forschung, Teheran, Iran, IT-Managerin bei einem internationalen Straßenbauunternehmen.