Two Mamdani type fuzzy models (three inputs–one output and two inputs–one output) were developed to predict the permeability of compounds through human skin. The models were derived from multiple data sources including laboratory data, published data bases, published statistical models, and expert opinion. The inputs to the model include information about the compound (molecular weight and octo...

In this paper, we present our work in the field of computational intelligence and discrete event systems. Knowledge representation and the inclusion of imperfect knowledge is a key step in an effort to optimally incorporate artificial intelligence methods in a modeling and simulation framework. Fuzzy Inference Systems (FIS) are one of the most used applications of Fuzzy Logic and Fuzzy Sets The...

This paper presents a time control liquids mixing system in the tanks as an application of fuzzy time control discrete model. The system is designed for a wide range of industrial applications. The simulation design of control system has three inputs: volume, viscosity, and selection of product, along with the three external control adjustments for the system calibration or to take over the con...

Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...

In this paper, a novel approach termed Dynamic Self-Generated Fuzzy Q-Learning (DSGFQL) for automatically generating Fuzzy Neural Networks (FNNs) is presented. The structure and premises of FNNs are to be generated through the reward evaluation and unsupervised approaches while the consequents are trained via a Fuzzy Q-Learning (FQL) approach. The proposed DSGFQL methodology can automatically c...

Traditional stochastic discrete event simulation method requires the users to fit the task duration data with an empirical probability function or a theoretical probability density function. This has limited the application of discrete event simulation techniques from research stage to construction practice due to the tedious data fitting tasks required for the construction operation planners l...