The concept of (fuzzy) probability density function of fuzzy random variable is proposed in this paper. Due to the "resolution identity", we can construct a closed fuzzy number from a family of closed intervals. Using the same technique, we can construct the (fuzzy) probability density function of fuzzy random variable from the known probability density function. The basic idea of the new metho...

Morphology has a special place in any language, including written and spoken applications. Markov method is used to labeingl and determine the role of words.emergence in software sciences has eliminated 0 and 1 computations, putting them within an infinite space of between 0,1. This characteristic of fuzzy logic has resolved ambiguity in numerous previous problems. The sentence roles in Persian...

Fuzzy logic is achieved by formulating a rule base which is based on experience gathered by human operators. Those systems which cannot be modeled mathematically benefit most from Fuzzy control strategy since the imprecise data can be captured by using linguistic data in the rule-base. Fuzzy logic has certain disadvantages. The number of computations required for arriving at a certain output fo...

In this paper, we deal with fuzzy random variables for inputs andoutputs in Data Envelopment Analysis (DEA). These variables are considered as fuzzyrandom flat LR numbers with known distribution. The problem is to find a method forconverting the imprecise chance-constrained DEA model into a crisp one. This can bedone by first, defuzzification of imprecise probability by constructing a suitablem...

<span>Hazardous gases such as carbon monoxide (CO) and sulfur dioxide (SO<sub>2</sub>) not only emerge in the outdoor environment but also inside house or factory which will endanger occupants workers. The detection devices are mainly found on public roads since detected gas mostly consists of CO SO<sub>2</sub>. design air quality monitoring is proposed with applie...

Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System). This L-System models the plants growth by following the production rules, which are the combination of grammar and mathematic formulae. In this paper, we propose the use of fuzzy mamdani, to model the plant growth based on the current environment condition. The varied amount of fertilizer, both o...

Mamdani systems can incorporate expert knowledge about an input-output relation in the form of IF-THEN rules expressed in natural language. This is a particularly attractive feature for modeling and simulation, but is also one that can be easily misused. Focusing on applied modeling and simulation, this paper discusses why Mamdani systems are not a useful tool to explore the logical consequence...

Deriving the analytical structure of fuzzy controllers is very important as it creates a solid foundation for better understanding, insightful analysis, and more e1ective design of fuzzy control systems. We previously developed a technique for deriving the analytical structure of the fuzzy controllers that use Zadeh fuzzy AND operator and the symmetric, identical trapezoidal or triangular input...

In this paper, analytical structures of TITO (two-input two-output) Mamdani fuzzy PI/PD controllers are investigated with respect to conventional PI/PD control and variable gain control. Components of the fuzzy controllers include two input fuzzy sets for each input variable, five singleton output fuzzy sets for each output variable, 16 fuzzy rules, product AND fuzzy logic operator, the Mamdani...