Fuzzy support model for long pipelines by using db2 approach

SCImago Journal Rank
2024: SJR=0.300

CWTS Journal Indicators
2024: SNIP=0.77

Vol.2, No.2, 2017: pp.76-83

FUZZY SUPPORT MODEL FOR LONG PIPELINES BY USING DB2 APPROACH

Authors:

Djordje Dihovicni¹

, Miroslav Medenica¹

¹Technical College, Bulevar Zorana Djindjica 152a, Belgrade, Republic of Serbia

Received: 28.04.2017.
Accepted: 31.05.2017.
Available: 30.06.2017.

Abstract:

Transient in long pneumatic lines is analyzed from time delay and construction view of point. After presented mathematical model of pneumatic system, there are shown stability issues, and it is calculated length of the pneumatic pipeline for which the system is stable. The paper’s main contribution is the application of decision and fuzzy logic in determination the stability of long pipeline from construction perspective by using DB2 database approach, and proposal of possible applications of knowledge database and fuzzy logic in making diagnostics conclusions about the states of the safe operation and reliability of the system.

Keywords:

Fuzzy logic, decision model,knowledge database , stability,long pipelines, mathematicalmodel, diagnostic, reliability

References:

[1] Dj. Dihovicni, N. Nedic, Stability of Distributed Parameter Systems on Finite Space Interval, 32-nd Yupiter Conference, Zlatibor 2006, pp.317-320.
[2] Dj. Dihovicni, M. Medenica, Fundamental Matrix Approach in Solving Practical Stability for Distributed Parameter Systems, Computationall Intelligence in Business and Economics, Proceedings of the MS’10 International Conference, 15–17 July 2010, Barcelona, Spain, Vol.3, pp.703-711.
[3] A. Hmamed, Further results on the delay independent asymptotic stability of linear systems, Int J. System. Sci., 22(6), 1991: pp.1127-1132.
[4] Dj. Dihovicni, Pole Assignment for Glass Capilary Tube Drawing Process by using Matlab and Maple Language, Applied Engineering Letters, 1(3), 2016: pp.67-71.
[5] Z.L. Nenadic, D.L. Debeljkovic, S.A. Milinkovic, On practical stability of time delay systems, Proceedings of the 1997 American Control Conference, Vol.5, No.4-6, America, 1997, pp.3225-3236.
[6] Dj. Dihovicni, M. Medenica, Mathematical Modelling and Simulation of Pneumatic Systems, Advances in Computer Science and Engineering, Chapter 9, 2011: pp.161-186. DOI: 10.5772/15313
[7] Dj. Dihovicni, Contructing knowledge database in stability of pneumatic pipelines, Technical diagnostics, 14(1), 2015: pp.7-14.
[8] E. Tissir, A. Hmamed, Sufficient stability conditions of interval time delay systems, Adv Modelling Anal., C45, 1996: pp.1-16.
[9] R.E. Jaeger A.D. Pearson, J.C. Wiliams, H.M. Presby, Fiber Drawing and Control in Optical Fiber Telecommunications, Academic Press, New York, 1980, pp.263-298.
[10] A. Kaufmann, J. Gilaluja, Introduction to the theory of fuzzy subsets in business management, International Conference on Intelligent Technologies in Human related Sciences Leon, Spain, Vol.2, 1996: pp.217-223.
[11] Z. Adamovic, N. Jevtic B. Ilic, Application method of artificial intelligence in reaching conclusions of the situation diagnostic machine in process industry, Technical Diagnostics, 3(1), 2012: pp.33-40.
[12] J. Bergmans, S. Gutnikov, V. Krasnoproshin, S. Popok, H. Vissia, Computer-Base Support to Decision-Making in Orthopaedics, International Conference on Intelligent Technologies in Human related Sciences Leon, Spain, Vol.2, 1996: pp.217-223.
[13] F. Herrera, E. Herrera-Viedma, E. Lopez, Computer-Base Support to Decision-Making in Orthopaedics, International Conference on Intelligent Technologies in Human related Sciences, Leon, Spain, Vol.2, 1996: pp.205-213.
[14] J. Merigo, A. Gil-Lafuente, Decision making techniques in a unified model between the weighted average and the Owa operator, Computational Intelligence in Business and Economics, 2010: pp.181-188.
[15] H. Monga, S. Baghla, Approach to security in wireless sensors networks, Applied Engineering Letters, 1(3), 2016: pp.80-84.
[16] D. Perez, J. Batista, Decision Support Model for Information Systems Integration in Supply Chains: a Fuzzy Approach, Computational Intelligence in Business and Economics, 2010: pp.281-288.
[17] Raman, S. Baghla, H. Monga, Method & Implementation of Data Flow, Applied Engineering Letters, 1(4), 2016: pp.105-110.
[18] A. Sharma, A. GoswamI, D. Gupta, Fts-Sql: A query Language for Fuzzy Multidatabases, Proceedings of the World Congress on Engineering – WCE 2009, Vol.1, London U.K, 2009: pp.69-74.
[19] J. Walker, Cyber security concerns for emergency management, Emergency Management, Chapter 3, 2012: pp.39-60. DOI:10.5772/34104

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)

Volume 10
Number 3
September 2025

Fuzzy support model for long pipelines by using db2 approach

How to Cite

Dj. Dihovični, M. Medenica, Fuzzy Support Model for Long Pipelines by Using DB2 Approach. Applied Engineering Letters, 2(2), 2017: 76-83.

More Citation Formats

APA

Dihovični, Dj., & Medenica, M. (2017). Fuzzy Support Model for Long Pipelines by Using DB2 Approach. Applied Engineering Letters, 2(2), 76-83.

MLA

Dihovicni, Djordje, and Miroslav Medenica “Fuzzy Support Model for Long Pipelines by Using DB2 Approach.“ Applied Engineering Letters, vol. 2, no. 2, 2017, pp. 76-83.

Chicago

Dihovicni, Djordje, and Miroslav Medenica. 2017 “Fuzzy Support Model for Long Pipelines by Using DB2 Approach.“ Applied Engineering Letters, 2 (2): 76-83.

Harvard

Dihovični, Dj. and Medenica, M. (2017). Fuzzy Support Model for Long Pipelines by Using DB2 Approach. Applied Engineering Letters, 2(2), pp.76-83.