New parameter reduction of soft sets / (Record no. 4365)

MARC details
000 -LEADER
fixed length control field 04009nam a2200277 a 4500
001 - CONTROL NUMBER
control field vtls000078317
003 - CONTROL NUMBER IDENTIFIER
control field KUKTEM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251114204555.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140519t2012 my da f m 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE0001891(Local)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201905131517
Level of effort used to assign nonsubject heading access points yusri
Level of effort used to assign subject headings 201710091624
Level of effort used to assign classification aishah
-- 201405191353
-- Fida
040 ## - CATALOGING SOURCE
Original cataloging agency UMP
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) QA76.76.E95 M39 2012 rs Thesis
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Ma, Xiuqin
245 10 - TITLE STATEMENT
Title New parameter reduction of soft sets /
Statement of responsibility, etc. Ma Xiuqin
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Kuantan, Pahang :
Name of publisher, distributor, etc. Universiti Malaysia Pahang,
Date of publication, distribution, etc. 2012
300 ## - PHYSICAL DESCRIPTION
Extent xxii, 197 p. :
Other physical details ill. ;
Dimensions 30 cm. +
Accompanying material 1 CD-ROM
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Doctor of Philosophy (Computer Science)) -- Universiti Malaysia Pahang - 2012
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Bibliography : p. 189-195
520 3# - SUMMARY, ETC.
Summary, etc. Several algorithms exist to address the issues concerning parameter reduction of soft sets. The most recent concept of Normal Parameter Reduction (NPR) is introduced, which overcomes the problem of suboptimal choice and added parameter set of soft sets. However, the algorithm involves a great amount of computation. In this thesis, a New Efficient Normal Parameter Reduction algorithm (NENPR) of soft sets is proposed based on the new theorems, which have been proved and presented. The proposed technique can be carried out without parameter important degree and decision partition. As a result, it can involve relatively less computation, compared with the algorithm of NPR. The experimental results are analyzed and comparisons are done with three real-life datasets and ten synthetic generated datasets. The computational complexity is described in terms of the number of entry access, the number of parameter importance degree access and oriented-parameter access, and the number of candidate parameter reduction set. From these experimental results, some conclusions can be drawn that NENPR improves the number of entry access, the number of parameter importance degree access and oriented-parameter access, the number of candidate parameter reduction set and the executing time of NPR averagely up to 95.21%, 52.45%, 53.58% and 60.02% through three real-life datasets and ten synthetic generated datasets, respectively. Sum up, NENPR provides the better solutions for capturing the normal parameter reduction compared with NPR. An interval-valued fuzzy soft set is a special case of a soft set by combining the interval-valued fuzzy set and soft set. However, up to the present, the previous work has not involved parameter reduction of the interval-valued fuzzy soft sets. In this thesis, four new parameter reductions of the interval-valued fuzzy soft sets are proposed: Optimal Choice Considered Parameter Reduction (OCCPR), Invariable Rank of Decision Choice Considered Parameter Reduction (IRDCCPR), Standard Parameter Reduction (SPR) and Approximate Standard Parameter Reduction (ASPR). The related heuristic algorithms are given. In order to show the high efficiency of the proposed four algorithms, comparisons and analysis for decision making between OCCPR, IRDCCPR, ASPR, SPR and directly Interval-Valued Fuzzy Soft Sets based Fuzzy Decision Making algorithm (IVFSS-FDM) with three real-life datasets and ten synthetic generated datasets are made. Average percent of improvement of four proposed algorithms compared with IVFSS-FDM on the executing time concerning all of datasets are 80.28%, 56.37%, 47.44%, 10%, respectively. From these experimental results, conclusions can be drawn that our four proposed algorithms have much higher efficiency compared with directly IVFSS-FDM for decision making and four approaches have the respective merits and demerits. Therefore these proposed methods can be applied into the different situations.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Expert systems (Computer science)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Fuzzy sets
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Neural networks (Computer science)
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://ecollib.ump.edu.my/3688/">http://ecollib.ump.edu.my/3688/</a>
Public note Library access only
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
  Not lost Library of Congress Classification   Not for loan UMPLIB GAMBANG UMPLIB GAMBANG 04/09/2019   CD 6697 | QA76.76.E95 M39 2012 rs Thesis 0000071416 04/09/2019 1 04/09/2019 Thesis
  Not lost Library of Congress Classification   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   QA76.76.E95 M39 2012 rs Thesis 0000071415 04/09/2019 1 04/09/2019 Thesis

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