This paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. The output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (LLNF) model, is useful for assessing a project status at different time horizons. Being trained by a locally linear model tree (LOLIMOT) learning algorithm, the model is int...

In the safety-critical systems, potential hazard may jeopardize the safety of system, which can even lead to catastrophic accident. The occurrence of accident contains deterministic and non-deterministic causal logic relationships. The former refers to technical aspects, where event tree and fault tree could be applied to analyze. The latter mainly refers to operational aspects. Due to uncertai...

In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...

This work focuses on the formalization of a Fuzzy Cognitive Map based decision support system using fuzzy If-Then rules (extracted from data) accompanied with the available experts’ knowledge. The proposed approach is applied to build a Fuzzy Cognitive Map (FCM) grading tool, an advanced FCM-based model used for prediction. The FCM is a modeling methodology based on exploiting knowledge and exp...

In the realm of computer security, biometrics refers to authentication technique that relies on the measurement of physiological and individual characteristics that can be automatically verified. In our proposed biometric system is a combo of modeling and quantification of different human cognitive factors and fuzzy decision tree. In our novel biometric system we use visual search and short ter...

A technique for the modeling of nonlinear control processes using fuzzy modeling approach based on the Takagi–Sugeno fuzzy model with a combination of genetic algorithm and recursive least square is proposed. This paper discusses the identification of the parameters at the antecedent and consequent parts of the fuzzy model. For the antecedent fuzzy parameters, genetic algorithm is used to tune ...

monitoring and forecasting of air quality parameters in urban areas is considered as one of the challenges of the human environment. it depends on several factors such as topography, climate, population and transport network which the interaction of these spatial factors has been as a dynamic phenomenon, non-linear and ambiguous. in this study, two models suggested to predict and modeling conce...