background : drivers are vulnerable to musculoskeletal and psychological disorders because of substantially harmful agents in this stressful occupation. this study aims to investigate the influence of driver’s physical and psychological health on the risk of road accidents using fuzzy logic approach. methods : two input variables including musculoskeletal disorders (msds) and mental health, alo...

In this paper a Distributed Adaptive Neuro-Fuzzy Architecture (DANFA) model with a second order Takagi-Sugeno inference mechanism is presented. The proposed approach is based on the simple idea to reduce the number of the fuzzy rules and the computational load, when modeling nonlinear systems. As a learning procedure for the designed structure a two-step gradient descent algorithm with a fixed ...

In context-aware computing environment, some context is characterized by a single event, but many other contexts are determined by a sequence of events which occur with some timing constraints. Therefore, context inference should be conducted by monitoring the sequence of event occurrence along with checking their conformance with timing constraints. Some context could be described with fuzzy w...

A widely used fuzzy reasoning algorithm was modified and implemented via an expert system to assess the potential risk of employee repetitive strain injury in the workplace. This fuzzy relational model, known as the Priority First Cover Algorithm (PFC), was adapted to describe the relationship between 12 cumulative trauma disorders (CTDs) of the upper extremity, and 29 identified risk factors. ...

An adaptive truss structure with self-learning active vibration control system is developed. A fuzzy-neural network (FNN) controller with adaptive membership functions is presented. The experimental setup of a two-bay truss structure with active members is constructed, and the FNN controller is applied to vibration suppression of the truss. The controller first senses the output of the accelero...

Proper models for prediction of time series data can be an advantage in making important decisions. In this study, we tried with the comparison between one of the most useful classic models of economic evaluation, auto-regressive integrated moving average model and one of the most useful artificial intelligence models, adaptive neuro-fuzzy inference system (ANFIS), investigate modeling procedur...

Quantitative assessment is the most important means to identify hazard potential and manage risk for an industrial process. The implement of quantitative assessment in the early stage will help to develop inherently safer process, eliminating the hazard and reduce the possibility of accidental chain events and the magnitude of consequences. In this paper, after reviewing the presently available...

This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle swarm optimization (PSO). Two different fuzzy classifiers are considered and optimized. The first classifier is based on Mamdani fuzzy inference system (M_PSO fuzzy classifier). The second classifier is based on TakagiSugeno fuzzy inference system (TS_PSO fuzzy classifier). The parameters of the ...