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Achieving Efficient Decision Making Through Hybrid Reduction in Soft Set Theory

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@article{IJASEIT1610,
   author = {Ahmad Nazari Mohd Rose and Mohd Isa Awang and Fadhilah Ahmad and Nurnadiah Zamri and Mohamad Afendee Mohamed and Mustafa Mat Deris},
   title = {Achieving Efficient Decision Making Through Hybrid Reduction in Soft Set Theory},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {7},
   number = {3},
   year = {2017},
   pages = {1032--1037},
   keywords = {soft set theory; hybrid reduction; parameter reduction; normal reduction; object reduction; decision making},
   abstract = {

The main intention of proposing an alternative technique is to ensure consistency is been upheld besides successfully reducing the file. Of all the reduction techniques available currently, only normal parameter reduction has managed to address the issue of consistency at optimal and suboptimal level. In this paper, we initiated another form of reduction known as hybrid reduction by complementing the normal parameter reduction with object reduction. It has already demonstrated that the proposed hybrid reduction has successfully reduced data by 55% with the sample used, thus proving that it as a good alternative for the process of decision making using less amount of data.

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1610},    doi = {10.18517/ijaseit.7.3.1610} }

EndNote

%A Mohd Rose, Ahmad Nazari
%A Awang, Mohd Isa
%A Ahmad, Fadhilah
%A Zamri, Nurnadiah
%A Mohamed, Mohamad Afendee
%A Mat Deris, Mustafa
%D 2017
%T Achieving Efficient Decision Making Through Hybrid Reduction in Soft Set Theory
%B 2017
%9 soft set theory; hybrid reduction; parameter reduction; normal reduction; object reduction; decision making
%! Achieving Efficient Decision Making Through Hybrid Reduction in Soft Set Theory
%K soft set theory; hybrid reduction; parameter reduction; normal reduction; object reduction; decision making
%X 

The main intention of proposing an alternative technique is to ensure consistency is been upheld besides successfully reducing the file. Of all the reduction techniques available currently, only normal parameter reduction has managed to address the issue of consistency at optimal and suboptimal level. In this paper, we initiated another form of reduction known as hybrid reduction by complementing the normal parameter reduction with object reduction. It has already demonstrated that the proposed hybrid reduction has successfully reduced data by 55% with the sample used, thus proving that it as a good alternative for the process of decision making using less amount of data.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1610 %R doi:10.18517/ijaseit.7.3.1610 %J International Journal on Advanced Science, Engineering and Information Technology %V 7 %N 3 %@ 2088-5334

IEEE

Ahmad Nazari Mohd Rose,Mohd Isa Awang,Fadhilah Ahmad,Nurnadiah Zamri,Mohamad Afendee Mohamed and Mustafa Mat Deris,"Achieving Efficient Decision Making Through Hybrid Reduction in Soft Set Theory," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 3, pp. 1032-1037, 2017. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.7.3.1610.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Mohd Rose, Ahmad Nazari
AU  - Awang, Mohd Isa
AU  - Ahmad, Fadhilah
AU  - Zamri, Nurnadiah
AU  - Mohamed, Mohamad Afendee
AU  - Mat Deris, Mustafa
PY  - 2017
TI  - Achieving Efficient Decision Making Through Hybrid Reduction in Soft Set Theory
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 7 (2017) No. 3
Y2  - 2017
SP  - 1032
EP  - 1037
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - soft set theory; hybrid reduction; parameter reduction; normal reduction; object reduction; decision making
N2  - 

The main intention of proposing an alternative technique is to ensure consistency is been upheld besides successfully reducing the file. Of all the reduction techniques available currently, only normal parameter reduction has managed to address the issue of consistency at optimal and suboptimal level. In this paper, we initiated another form of reduction known as hybrid reduction by complementing the normal parameter reduction with object reduction. It has already demonstrated that the proposed hybrid reduction has successfully reduced data by 55% with the sample used, thus proving that it as a good alternative for the process of decision making using less amount of data.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1610 DO - 10.18517/ijaseit.7.3.1610

RefWorks

RT Journal Article
ID 1610
A1 Mohd Rose, Ahmad Nazari
A1 Awang, Mohd Isa
A1 Ahmad, Fadhilah
A1 Zamri, Nurnadiah
A1 Mohamed, Mohamad Afendee
A1 Mat Deris, Mustafa
T1 Achieving Efficient Decision Making Through Hybrid Reduction in Soft Set Theory
JF International Journal on Advanced Science, Engineering and Information Technology
VO 7
IS 3
YR 2017
SP 1032
OP 1037
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 soft set theory; hybrid reduction; parameter reduction; normal reduction; object reduction; decision making
AB 

The main intention of proposing an alternative technique is to ensure consistency is been upheld besides successfully reducing the file. Of all the reduction techniques available currently, only normal parameter reduction has managed to address the issue of consistency at optimal and suboptimal level. In this paper, we initiated another form of reduction known as hybrid reduction by complementing the normal parameter reduction with object reduction. It has already demonstrated that the proposed hybrid reduction has successfully reduced data by 55% with the sample used, thus proving that it as a good alternative for the process of decision making using less amount of data.

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1610 DO - 10.18517/ijaseit.7.3.1610