Top

Soft Computing

Published in:

13-06-2020 | Foundations

Granulation of ecological networks under fuzzy soft environment

Authors: Muhammad Akram, Anam Luqman

Published in: Soft Computing | Issue 16/2020

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

The main idea of this work is the exploration of granular structures by applying the hybrid models of fuzzy soft sets and fuzzy soft graphs to discuss the indiscernibility partition of set of universe. The information granulation is examined by applying fuzzy soft theory, and the corresponding behavior of granules is reviewed. This article proposes a novel technique of formation of granular structures using fuzzy soft graphs and defines the fuzzy soft granules. Two degree-based models are introduced to explore the abstraction of these granular structure. Then, we use these two degree-based models to granulate the certain relationships between different species in an ecological system. Further, we develop and implement some algorithms of our proposed models to granulate the underconsideration networks. Finally, a comprehensive comparison of our proposed model with other existing techniques is presented to prove the applicability and effectiveness of fuzzy soft granulation.

previous article Global optimization method with dual Lipschitz constant estimates for problems with non-convex constraints

next article A comprehensive study of PAPR reduction techniques: design of DSLM-CT joint reduction technique for advanced waveform

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Akram M, Luqman A (2020) Fuzzy hypergraphs and related extensions. Stud Fuzziness Soft Comput. https://doi.org/10.1007/978-981-15-2403-5 CrossRefMATH

Akram M, Zafar F (2020) Hybrid soft computing models applied to graph theory. Stud Fuzziness Soft Comput. https://doi.org/10.1007/978-3-030-16020-3 CrossRefMATH

Akram M, Adeel A, Alcantud JCR (2018) Fuzzy \(N\)-soft sets: a novel model with applications. J Intell Fuzzy Syst 35(4):4757–4771

Akram M, Adeel A, Alcantud JCR (2019a) Group decision-making methods based on hesitant \(N\)-soft sets. Expert Syst Appl 115:95–105

Akram M, Adeel A, Alcantud JCR (2019b) Hesitant fuzzy \(N\)-soft sets: a new model with applications in decision-making. J Intell Fuzzy Syst 36(6):6113–6127

Akram M, Ilyas F, Garg H (2020) Multi-criteria group decision making based on ELECTRE I method in pythagorean fuzzy information. Soft Comput 24:3425–3453

Ali MI (2012) Another view on reduction of parameters in soft sets. Appl Soft Comput 12(6):1814–1821

Ali SH (2013) Novel approach for generating the key of stream cipher system using random forest data mining algorithm. In: 2013 6th international conference on developments in E-systems engineering. IEEE, New York, pp 259–269

Ali MI, Feng F, Liu XY, Min WK, Shabir M (2009) On some new operations in soft set theory. Comput Math Appl 57(9):1547–1553MathSciNetMATH

Al-Janabi S, Alkaim AF (2019) A nifty collaborative analysis to predicting a novel tool (DRFLLS) for missing values estimation. J Soft Comput. https://doi.org/10.1007/s00500-019-03972-x CrossRef

Al-Janabi S, Patel A, Fatlawi H, Kalajdzic K, Al Shourbaji I (2014) Empirical rapid and accurate prediction model for data mining tasks in cloud computing environments. In: 2014 international congress on technology, communication and knowledge (ICTCK). IEEE, New York, pp 1–8

Al-Janabi S, Mohammad M, Al-Sultan A (2019) A new method for prediction of air pollution based on intelligent computation. Soft Comput. https://doi.org/10.1007/s00500-019-04495-1 CrossRef

Alkaim AF, Al-Janabi S (2019) Multi objectives optimization to gas flaring reduction from oil production. In: International conference on big data and networks technologies. Springer, Cham, pp 117–139

Berge C (1973) Graphs and hypergraphs. North-Holland Publishing Company, AmsterdamMATH

Bianchi FM, Livi L, Rizzi A, Sadeghian A (2014) A Granular computing approach to the design of optimized graph classifcation systems. Soft Comput 18:393–412

Bisi C, Chiaselotti G, Ciucci D, Gentile T, Infusino FG (2017) Micro and macro models of granular computing induced by the indiscernibility relation. Inf Sci 388:247–273MathSciNet

Chen G, Zhong N (2011) Granular structures in graphs. In: International conference on rough sets and knowledge technology. Springer, Berlin, pp 649–658

Chen G, Zhong N, Yao Y (2008) A hypergraph model of granular computing. In: IEEE international conference on granular computing, pp 130–135

Chiaselotti G, Ciucci D, Gentile T (2016) Simple graphs in granular computing. Inf Sci 340:279–304MathSciNetMATH

Feng F, Jun YB, Liu XY, Li LF (2010a) An adjustable approach to fuzzy soft set based decision making. J Comput Appl Math 234:10–20MathSciNetMATH

Feng F, Li CX, Davvaz B, Irfan AM (2010b) Soft sets combined with fuzzy sets and rough sets: a tentative approach. Soft Comput 14:899–911MATH

Feng F, Fujita H, Ali MI, Yager RR, Liu X (2019) Another view on generalized intuitionistic fuzzy soft sets and related multiattribute decision making methods. IEEE Trans Fuzzy Syst 27(3):474–488

Gong Z, Wang Q (2017) On the connection of fuzzy hypergraph with fuzzy information system. J Intell Fuzzy Syst 33(3):1665–1676 MATH

Gu K, Wang L, Yin B (2019) Social community detection and message propagation scheme based on personal willingness in social network. Soft Comput 23(15):6267–6285

Guan X, Li Y, Feng F (2013) A new order relation on fuzzy soft sets and its application. Soft Comput 17(1):63–70MATH

Kalajdzic K, Ali SH, Patel A (2015) Rapid lossless compression of short text messages. Comput Stand Interfaces 37:53–59

Kaur C, Kumar R (2019) A fuzzy hierarchy-based pattern matching technique for melody classification. Soft Comput 2(1):7375–7392

Khameneh ZA, Kiliçman A (2019) Multi-attribute decision-making based on soft set theory: a systematic review. Soft Comput 23(16):6899–6920

Lin TY (1997) Granular computing. In: Announcement of the BISC special interest group on granular computing

Luqman A, Akram M, Koam AN (2019a) An \(m\)-polar fuzzy hypergraph model of granular computing. Symmetry 11(4):483

Luqman A, Akram M, Koam AN (2019b) Granulation of hypernetwork models under the q-rung picture fuzzy environment. Mathematics 7(6):496

Maji PK, Roy AR, Biswas R (2001) Fuzzy soft sets. J Fuzzy Math 9(3):589–602MathSciNetMATH

Maji PK, Biswas R, Roy AR (2003) Soft set theory. Comput Math Appl 45(4–5):555–562MathSciNetMATH

Molodtsov DA (1999) Soft set theory-first results. Comput Math Appl 37:19–31MathSciNetMATH

Molodtsov DA (2004) The theory of soft sets. URSS Publishers, Moscow (in Russian)

Mordeson JN, Nair PS (1998) Fuzzy graphs and fuzzy hypergraphs, 2nd edn. Physica Verlag, HeidelbergMATH

Patel A, Al-Janabi S, AlShourbaji I, Pedersen J (2015) A novel methodology towards a trusted environment in mashup web applications. Comput Secur 49:107–122

Pawlak Z (1991) Rough sets. Theoretical aspects of reasoning about data. Kluwer Academic Publisher, LondonMATH

Radha K, Kumaravel N (2013) The degree of an edge in Cartesian product and composition of two fuzzy graphs. Int J Appl Math Stat Sci 2(2):65–78

Rosenfeld A (1975) Fuzzy graphs. In fuzzy sets and their applications to cognitive and decision processes. Academic Press, New York, pp 77–95

Roy AR, Maji PK (2007) A fuzzy soft set theoretic approach to decision making problems. J Comput Appl Math 203:412–418MATH

Singh PK, Kumar AC, Li J (2016) Knowledge representation using interval-valued fuzzy formal concept lattice. Soft Comput 20(4):1485–1502MATH

Song Y, Li G (2019) Handling group decision-making model with incomplete hesitant fuzzy preference relations and its application in medical decision. Soft Comput 23(15):6657–6666MATH

Stell JG (1999) Granulation for graphs. In: International conference on spatial information theory. Springer, Berlin, pp 417–432

Stell JG (2010) Relational granularity for hypergraphs. In: International conference on rough sets and current trends in computing. Springer, Berlin, pp 267–276

Wang Q, Gong Z (2018) An application of fuzzy hypergraphs and hypergraphs in granular computing. Inf Sci 429:296–314MathSciNet

William-West TO, Singh D (2018) Information granulation for rough fuzzy hypergraphs. Granul Comput 3(1):75–92

Yang J, Wang G, Zhang Q (2018) Knowledge distance measure in multigranulation spaces of fuzzy equivalence relation. Inf Sci 448:18–35MathSciNet

Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353MATH

Zadeh LA (1979) Fuzzy sets and information granularity. In: Gupta N, Ragade R, Yager R (eds) Advances in fuzzy set theory and applications. North-Holland, Amsterdam, pp 3–18

Zadeh LA (1997) Towards a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst 19:111–127MathSciNetMATH

Zhan J, Akram M, Sitara M (2018) Novel decision-making method based on bipolar neutrosophic information. Soft Comput 23(20):9955–9977

Zhang H, Li Q (2019) Intuitionistic fuzzy filter theory on residuated lattices. Soft Comput 23(16):6777–6783MATH

Title: Granulation of ecological networks under fuzzy soft environment
Authors: Muhammad Akram
Anam Luqman
Publication date: 13-06-2020
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 16/2020
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-020-05083-4

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Other articles of this Issue 16/2020

Development and evaluation of the cascade correlation neural network and the random forest models for river stage and river flow prediction in Australia

UAV tracking based on saliency detection

Bio-inspired predictive models for shear strength of reinforced concrete beams having steel stirrups

Multiple criteria decision making based on weighted Archimedean power partitioned Bonferroni aggregation operators of generalised orthopair membership grades

Some new basic operations of probabilistic linguistic term sets and their application in multi-criteria decision making

Enhanced crow search algorithm for AVR optimization

Premium Partner