International Journal of Technology Enhancements and Emerging Engineering Research (ISSN 2347-4289)

IJTEEE >> Volume 3 - Issue 1, January 2015 Edition

International Journal of Technology Enhancements and Emerging Engineering Research  
International Journal of Technology Enhancements and Emerging Engineering Research

Website: http://www.ijteee.org

ISSN 2347-4289

Business Model With Virtual Linearity Using Statistical Inference Tool (VL-SIT)

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Abdul Mannan, Nasir Uddin Khan, Mushtaq Hussain, Asif Mansoor, Mujtaba Hussain



Keywords: Business Process Design, Structural Complications, cross-confliction, relational business process data, statistical inference tool, Rule-based selective inference, simulated linearity.



ABSTRACT: Business Model is an approach to resolve structural complications encountered during business process design or during modification to remove typical business-process problems in terms of process hierarchy or execution hierarchy or any other design related business rule implementation hierarchy Such problems are normally unresolvable by simple methods or through mathematical methods or even statistical analysis or Relational Database systems with statistical analysis tools But there is a need to resolve every such complication before the model is implemented for practical use or at least some optimization to reduce the effects of natural non-linearity on actual process due to multi-dimensional cross-linkage between the process parameters and liquefiable numeric weight values Although the structural fabric of Business Process design involve many cross conflictions in terms of Commercial parameters such as process profitability or profit-credentials or any value-added subentity in the context of business statement language when converted into model language such as Mathematical relation or statistical declaration or an approximate probability proposition So a workable concept is adopted to select the virtual linearity as simulated representation of a articular business process using statistical inference based on existing data model fitted on some running processes which has relations from Mathematical inference as a solution to common business problems. The tool is a direct rule based selective inference linked with virtual parameters assigned to simulate linearity keeping actual data affectivity on main process as to minimize the non-linear behavior as par as null or even void in certain short turned around processes loops A business model with simulate able virtual linearity may represent an easy and workable process to be able to repeat the process cycle multiple times without any noticeable drift of factor responsible for process outcome due to (VL-SIT)



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