Loading

Requirements of ERP Vendors using Hybrid Hierarchy Process with Artificial Neural Network (Hahp-Ann) Method
S. Hameed Ibrahim1, S. Seetha Raman2, M. Gowtham3

1S. Hameed Ibrahim, Assistant Professor (SRG), Department of Computer Applications, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India. 

2S. Seetha Raman, PG Scholar, Department of Computer Applications, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India. 

3M. Gowtham, PG Scholar, Department of Computer Applications, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India. 

Manuscript received on 09 September 2019 | Revised Manuscript received on 18 September 2019 | Manuscript Published on 11 October 2019 | PP: 142-147 | Volume-8 Issue-11S September 2019 | Retrieval Number: K103109811S19/2019©BEIESP | DOI: 10.35940/ijitee.K1031.09811S19

Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The Enterprise Resource Planning framework (ERP) has been called attention to as special data frameworks paradigm. In any case, accomplishing an appropriate degree of ERP achievement depends on an assortment of factors that are identified with an association or venture condition.Those ERP projects should be satisfied by the customers and vendors in terms of ease of accessibility, flexibility, efficiency and reliability. In our existing work, AHP-RCF method uses requirements in the rank based priority level. However, it has not been discussed about the decision criteria of the customers. In our paper ,a mix approach between the AHP and ANN has been created to assess and choose the good degree of customization that is the requirements that can perform customization in a well efficient manner. The proposed method HAHP-ANN is used to measure the weight of customization and various structures of multi-layer neural networks have been analysed for the optimization. Also the learning of project information gathering is done by using mix SVM classification approach based on which dynamic updation about the project needs can be provided to the user customization. The general valuation of the research strategy is led in the java model back ground condition from which it is demonstrated that the proposed research procedure prompts give the ideal result than the current research systems.

Keywords: Hybrid Analytic Hierarchy Process-Artificial Neural Network (HAHP-ANN), Enterprise Resource Planning System (ERP), Mix SVM.
Scope of the Article: Artificial Intelligence