An enhanced soft set data reduction using decision partition order technique / (Record no. 7192)

MARC details
000 -LEADER
fixed length control field 04452ntm a2200373 i 4500
001 - CONTROL NUMBER
control field vtls000103100
003 - CONTROL NUMBER IDENTIFIER
control field KUKTEM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251117113341.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180312s2017 my da f am 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE0001063(Local)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201905311456
Level of effort used to assign nonsubject heading access points nazirah
-- 201803121237
-- saini
040 ## - CATALOGING SOURCE
Original cataloging agency UMP
Language of cataloging eng
Transcribing agency UMP
Description conventions rda
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) FSKKP .A33 2017 r Thesis
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Mohammed, Mohammed Adam Taheir,
Relator term author.
245 13 - TITLE STATEMENT
Title An enhanced soft set data reduction using decision partition order technique /
Statement of responsibility, etc. Mohammed Adam Taheir Mohammed
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Kuantan, Pahang :
Name of producer, publisher, distributor, manufacturer UMP,
Date of production, publication, distribution, manufacture, or copyright notice 2017
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice © 2017
300 ## - PHYSICAL DESCRIPTION
Extent xi, 128 pages :
Other physical details illustrations (some color), chart ;
Dimensions 30 cm. +
Accompanying material 1 CD-ROM
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Source rdamedia
337 ## - MEDIA TYPE
Media type term computer
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Source rdacarrier
338 ## - CARRIER TYPE
Carrier type term computer disc
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
500 ## - GENERAL NOTE
General note Faculty of Computer Systems and Software Engineering
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Doctor of Philosophy in Computer Science) -- Universiti Malaysia Pahang – 2017
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references
520 3# - SUMMARY, ETC.
Summary, etc. Nowadays, redundant data is one of the open issues due to the rapid development of technologies. This issue is more visible especially in decision-making as the behaviour of such data is more complex and due to the uncertainty during a process of decision making. Besides, the need of extra memory is essential as redundant data makes use of storage and produce redundant copies due to its widespread use. Hence, the soft-set reduction techniques are introduced to assist in reducing storage space by facilitating less number of copies with minimum cost per line or per storage. The benefit of soft-set reduction is to foster the decision making process as well as to enhance the decision’s quality. Classification techniques that were previously proposed for eliminating inconsistency could not achieve an efficient soft-set reduction, which affects the obtained solutions; thus producing imprecise result. Furthermore, the decomposition based on previous algorithms could not achieve better parameter reduction in available domain space. The decomposition computational cost made during combination generation can cause machine infinite state as Nondeterministic Polynomial time (NP). The decomposition scenario in Rose’s and Kumar’s algorithms detects the reduction, but could not obtain the optimal decision. The contributions of this research are mainly focused on minimizing choices costs through adjusting the original classifications by decision partition order. Moreover, this research proposes a decision partition order technique to maintain the original classification consistency. The second contribution is enhancing the probability of search domain of Markov chain model. Furthermore, this research proposes an efficient Soft-Set Reduction accuracy based on Binary Particle Swarm optimized by Biogeography-Based Optimizer (SSR-BPSO-BBO) algorithm that can generate accurate decision for optimal and sub-optimal results. The results show that the decision partition order technique performs up to 50% in parameter reduction, while some algorithms could not obtain any reduction. On the other hand, the proposed Markov chain model could significantly represent the robustness of the proposed reduction technique in making the optimal decision and minimising the search domain by up to 33%. In terms of accuracy, the proposed SSR-BPSO-BBO algorithm outperforms other optimization algorithms by up to 100% in achieving high accuracy percentage of a given soft dataset. In addition, the proposed decision partition order technique has reduced the choices costs and thus improves the original classification consistency. Hence, the proposed technique could efficiently enhance the decision quality. Also, the accuracy of original soft-set optimal and sub-optimal results have been improved using an intelligent SSR-BPSO-BBO algorithm. The computational cost of search domain (space) has been enhanced using proposed Markov Chain Model.
610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Faculty of Computer Systems and Software Engineering
General subdivision Dissertations
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Universities and colleges
General subdivision Disertations
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Theses
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 PEKAN UMPLIB PEKAN 04/09/2019   FSKKP .A33 2017 r Thesis 0000122538 04/09/2019 1 04/09/2019 Thesis
  Not lost Library of Congress Classification   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   CD 11219 | FSKKP .A33 2017 r Thesis 0000122539 04/09/2019 1 04/09/2019 Thesis

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