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Register a new userDeveloping a New Methodology For Optimal Facility Site Selection Analysis Based On Fuzzy Logic In GIS Environment, Study Area: Tartous-Syria
تطوير منهجية جديدة في تحليل اختيار الموقع الأمثل لمنشأة ما باستخدام المنطق الضبابي ضمن بيئة أنظمة المعلومات الجغرافية منطقة الدراسة: طرطوس - سورية
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حنان كامل درويش( باحث )
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يهدف البحث المقدم إلى تطوير طريقة للتراكب الضبابي بين الطبقات على أساس المنطق الضبابي، و إعادة تصنيف الكائنات ضمن مجموعات ضبابية، و دراسة إمكانية استخدام مثل هذه الطريقة في دمج البيانات المتعلقة بدراسة ظاهرة محددة للمساعدة في اتخاذ قرارات أمثلية.
This research aims to develop overlay functions methodology based on fuzzy logic, reclassify the objects into fuzzy classes, and study the usability of this method to integrate data of specific phenomenon to help make optimal decisions.
References used
L. A. Zadeh, «Probability measures of fuzzy events,» Journal of mathematical analysis and applications, vol. 23, n° 12, pp. 421-427, 1968
J. Jantzen, «Tutorial on fuzzy logic,» Technical University of Denmark, Dept. of Automation, Technical Report, 1998
A. M. Ibrahim, Fuzzy logic for embedded systems applications, Elsevier Science, 2004, p. 312
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One of the principal applications of fuzzy logic is in control system design. Fuzzy logic controllers (FLC) can be used to control
systems where the use of conventional control techniques may be Problematic. The tuning of fuzzy controllers has tende
d to rely on human expert knowledge, but where the number of rules and fuzzy sets is large. The Problem of generation desirable fuzzy rule is very important in the development of fuzzy systems. The purpose of this paper is to present a generation method of fuzzy control rules by learning from examples using genetic algorithms (GA). We propose real coded genetic algorithms (RCGA) for learning fuzzy rules, and an iterative process for obtaining set of rules which covers the examples set with a covering value previously defined.
This research work presents fuzzy pitch controller design of wind turbine to get the maximum power in
addition to decrease the losses caused by acceleration and deceleration in turbine rotation. And thus
optimize power coefficient of turbine throug
h artificial intelligence and in particular fuzzy logic, because
the fuzzy controller doesn’t need a complex mathematical pattern of the controlled system.
A fuzzy controller is designed and compared with conventional controller for the same purpose in a wind
turbine system described by its transfer function and membership function has been chosen for error and
accumulation errors signals by using MATLAB. Results have been compared and showed better response
by using the fuzzy controller.
Fuzzy logic control is used to connect a photovoltaic system to the electrical grid by using three phase fully
controlled converter (inverter), This controller is going to track the maximum power point and inject the
maximum available power from th
e PV system to the grid by determining the trigger angle that must be
applied on the switches: Linguistic variables are going to be chosen to determine the amount of change in
the trigger angle of the inverter to track the maximum power.
Environment is the atmosphere where mankind lives and interact
with its component, whereas the growth of human's requirements
has made great changes of the environmental system .So the
environmental evaluation become one of the most important tool
to reduce the impact of enhancement projects .Concrete works impact seems to be complicated and massive but some of them has lately effects which never appear soon. Nevertheless, the environmental evaluation considered very necessary and has such a big importance as a tool to make a decision, so that the concrete equipments are the serious element in environmental evaluation of concrete projects.
Environmental evaluation to Huge concrete works will directly
focus on the concrete equipments which have the clear effects on
environment so the Environmental evaluation purpose is to reduce
or prevent the negative effects which is expected in such as works,
also it can be used as a tool in management and planning projects
through inserting the environmental consideration in projects
planning. In order to discuss this problem we used the fuzzy logic theory.
The overlay functions in Geographic Information Systems (GIS) are considered as one of the basic functions of these systems, and often, a variety of data stored in layers may be integrated together to generate new layers that contain useful informati
on for decision-makers. All geographic objects are stored in layers and usually rely on crisp set theory, whether, stored in a vector or raster format. In many cases, boundaries of classes or objects are not clearly defined, or when we perform classification of features into classes, the geographic objects located in the boundaries of classes could be classified into the wrong class. This research aims to develop overlay functions methodology based on fuzzy logic, reclassify the objects into fuzzy classes, and study the usability of this method to integrate data of specific phenomenon to help make optimal decisions. To implement and examine this idea, a set of Fuzzy Membership Functions was developed using the Python programming language embedded within the ArcGIS environment. Through this Fuzzy Membership Functions, the user can generate fuzzy sets and combine with each other according to one of fuzzy operations, and thus the generation of fuzzy sets allows supporting the right and reliable decision. To test the proposed fuzzy model capabilities, it has been applied in Tartous governorate to select suitable tourist facility sites in accordance with groups of factors. In summary, data integration using proposed fuzzy overlay functions can improve the reliability of data representation and thus the reliability of make the best decisions.
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