Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
FUZZY DYNAMIC-PROGRAMMING
Date
1994-04-14
Author
ALKAN, M
Erkmen, Aydan Müşerref
Erkmen, İsmet
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
110
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/53629
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
FUZZY CELL-TO-CELL MAPPING
AYDIN, H; Erkmen, Aydan Müşerref (1993-08-27)
Fuzzy project scheduling with motivation considerations
Oktay, Mesture; Sepil, Canan; Department of Industrial Engineering (2000)
Fuzzy Multiobjective Decision Making Approach for Groundwater Resources Management
Kentel Erdoğan, Elçin (2007-01-01)
A conventional simulation-optimization model with constraint on drawdown at an area of interest is used to optimize additional groundwater withdrawal at multiple demand locations in a coastal aquifer. After obtaining the optimal solution, a decision-making analysis is conducted using fuzzy logic concepts. The goal is to evaluate multiple objectives and select the best management strategy. This methodology is applied to a hypothetical case consisting of six groundwater demand locations in Savannah, Ga. The o...
Fuzzy association rule mining from spatio-temporal data
Calargun, Seda Unal; Yazıcı, Adnan (2008-07-03)
The use of fuzzy sets in mining association rules from spatio-temporal databases is useful since fuzzy sets are able to model the uncertainty embedded in the meaning of data. There are several fuzzy association rule mining techniques that can work on spatio-temporal data. Their ability to mine fuzzy association rules has to be compared on a realistic scenario. Besides the performance criteria, other criteria that can express the quality of an association rule discovered shall be specified. In this paper, fu...
Fuzzy model tuning using simulated annealing
Yanar, Tahsin Alp; Akyürek, Sevda Zuhal (Elsevier BV, 2011-07-01)
This paper presents the use of simulated annealing metaheuristic for tuning Mamdani type fuzzy models. Structure of the Mamdani fuzzy model is learned from input-output data pairs using Wang and Mendel's method and fuzzy c-means clustering algorithm. Then, parameters of the fuzzy system are tuned through simulated annealing. In this paper, we perform experiments to examine effects of (a) initial solution generated by Wang and Mendel's method and fuzzy c-means clustering method, (b) membership function updat...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. ALKAN, A. M. Erkmen, and İ. Erkmen, “FUZZY DYNAMIC-PROGRAMMING,” 1994, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53629.