The classical analysis of real time systems tries to ensure that the instance of every task finishes before its absolute deadline (strict guarantee). The probabilistic approach tends to estimate the probability that it will happen. The deterministic timed behavior is an important parameter for analysing the robustness of the system. Most of related works are mainly based on the determinism of t...

labyrinth spillway is an appropriate option to pass pmf discharge. the most advantages of this type of spillway are higher discharge capacity, easy aeration as well as low fluctuations of flow surface. it is essential to find the optimum geometry considering the maximum passing discharge under specific hydraulic conditions with minimum construction cost. in this study, fuzzy inference system (f...

Original scientific paper This paper proposes a Neuro-fuzzy system for quantitative assessment of the effects of intelligent transportation systems and technologies on road fatalities. The basic idea in developing Neuro-fuzzy system is the fact that intelligent transportation systems and technologies activate some safety mechanisms and in turn the activation of safety mechanisms will have a pos...

The Fusion of Artificial Neural Networks (ANN) and Fuzzy Inference System (FIS) has attracted a growing interest of researchers in various scientific and engineering areas due to the growing need for adaptive intelligent systems to solve real world problems. ANN learns by adjusting the interconnections between layers. FIS is a popular computing framework based on the concept of fuzzy set theory...

A Fuzzy Inference System (FIS) typically implements a function f : R → T, where the domain set R denotes the totally-ordered set of real numbers, whereas the range set T may be either T = R (i.e. FIS regressor) or T may be a set of labels (i.e. FIS classifier), etc. This work considers the complete lattice (F,1) of Type-1 Intervals’ Numbers, or INs for short, where an IN F can be interpreted as...

Worms spread by scanning for vulnerable hosts across the Internet. In this paper we report a comparative study of three classification schemes for automated portscan detection. These schemes include a simple Fuzzy Inference System (FIS) that uses classical inductive learning, a Neural Network that uses back propagation algorithm and an Adaptive Neuro Fuzzy Inference System (ANFIS) that also emp...

The quantification and prediction of inter-agent dependency requirements is one of the main concerns in Agent Oriented Requirements Engineering. To evaluate exertion load of an agent within resource constraints, this work provides a comparative analysis of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). ANN is widely known due to its capability of learning the...

The Chiu’s method which generates a Takagi-Sugeno Fuzzy Inference System (FIS) is a method of fuzzy rules extraction. The rules output is a linear function of inputs. In addition, these rules are not explicit for the expert. In this paper, we develop a method which generates Mamdani FIS, where the rules output is fuzzy. The method proceeds in two steps: first, it uses the subtractive clustering...

This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods: a factor weighting method (WM) and a fuzzy inference system (FIS). By consulting an expert pan...

Bio-inspired algorithms like Genetic Algorithms and Fuzzy Inference Systems (FIS) are nowadays widely adopted as hybrid techniques in commercial and industrial environment. In this paper we present an interesting application of the fuzzy-GA paradigm to Smart Grids. The main aim consists in performing decision making for power flow management tasks in the proposed microgrid model equipped by ren...