There are a growing number of aerospace applications demonstrating the effectiveness of emulating human decision making using fuzzy logic. In this effort, a previously created MATLAB simulation of the classic arcade game PONG is utilized in which a fuzzy logic system that uses real-time fuzzy reasoning and awareness to represent a two-player team is able to play against various opponents. The o...

Fuzzy logic systems are promising for efficient obstacle avoidance. However, it is difficult to maintain the correctness, consistency, and completeness of a fuzzy rule base constructed and tuned by a human expert. A reinforcement learning method is capable of learning the fuzzy rules automatically. However, it incurs a heavy learning phase and may result in an insufficiently learned rule base d...

There are two main approaches to design a neural fuzzy system; namely, through expert knowledge, and through numerical data. While the computational structure of a system is manually crafted by human experts in the former case, self-organizing neural fuzzy systems that are able to automatically extract generalized knowledge from batches of numerical training data are proposed for the latter. Ne...

The fuzzy set is one of the powerful tools used to describe an uncertain environment. As well as quantifying any potential return and risk, portfolio liquidity is taken into account and a linear programming model for portfolio rebalancing with transaction costs is proposed. The level of return that an investor might aspire to, the risk and the liquidity of portfolio are vague in an uncertain fi...

Abstract --In this paper, we developed an EOQ model for Weibull deteriorating items with linear demand rate in fuzzy environment. Shortages are allowed and partially backlogged. Holding cost, deterioration cost, ordering cost, shortage cost and opportunity cost are assumed as a triangular fuzzy numbers. The purpose of this paper is to minimize the total cost function in fuzzy environment. Grade...

In this paper we describe a fuzzy logic based approach for providing biologically based motivations to be used in evolutionary mobile robot learning. Takagi-Sugeno-Kang (TSK) fuzzy logic is used to motivate a small mobile robot to acquire complex behaviors and to perform environment recognition. This method is implemented and tested in behavior based navigation and action sequence based environ...

Generally, it is very difficult to determine the medicine supply in hospital under uncertain environment. Here, the medical supply decision problem in uncertain environment is modeled as a fuzzy multi-objective linear programming model. First, the medicine supply in hospital management system is analyzed and the uncertainties in medicine supply are modeled as fuzzy numbers. Second, a fuzzy medi...

Nowadays, the problem of the flexibility in any organization has essential importance and the associated investigation with the organizational efficiency and performance is considered. In real-world situation, the process of decision making is often based on linguistic and mental data, so applying fuzzy logic in modeling at this point of view is convenient. In this paper, a fuzzy approach is ap...

Fuzzy linear regression models are used to obtain an appropriate linear relation between a dependent variable and several independent variables in a fuzzy environment. Several methods for evaluating fuzzy coefficients in linear regression models have been proposed. The first attempts at estimating the parameters of a fuzzy regression model used mathematical programming methods. In this the...