Graphic Design is the process of creating graphics to meet specific commercial needs based on knowledge of layout principles and esthetic concepts. This is usually an iterative trial and error process which requires a lot of time even for expert designers. This expert knowledge can be modelled, represented and used by a computer to perform design activities. This paper describes a novel approac...

In this article the design and development of a hierarchical fuzzy logic system is investigated. A new method using an evolutionary algorithm for design of hierarchical fuzzy logic system for prediction and modelling of interest rates in Australia is developed. The hierarchical system is developed to model and predict three months (quarterly) interest rate fluctuations. This research study is u...

Fuzzy CoCo is a methodology, combining fuzzy logic and evolutionary computation, for constructing systems able to accurately predict the outcome of a human decision-making process, while providing an understandable explanation of the underlying reasoning. Fuzzy logic provides a formal framework for constructing systems exhibiting both good numeric performance (accuracy) and linguistic represent...

Evolutionary Fuzzy Systems (EFSs) are fuzzy systems augmented by a learning process based on evolutionary computation such as evolutionary algorithms (EAs). These systems contribute with several advantages in the development of algorithms, and specifically in the development of subgroup discovery (SD) approaches. SD is a descriptive data mining technique using supervised learning in order to de...

This paper proposes a new selection mechanism in evolutionary algorithm for fuzzy systems that can be applied to robot learning of shooting ability in robot soccer. In generic evolutionary algorithms, evaluation and selection are performed on the chromosome level, where a selected chromosome may include non-effective or bad genes. This may lead to an increase in the uncertainty of the solutions...

The conceptual estimate plays an essential role in project feasibility study. In practice, it is performed based on estimators’ experiences. However, due to the inaccuracy of cost estimate, budgeting and cost control are planned inefficiently. In order to increase the estimate accuracy, this study employed the Evolutionary Fuzzy Neural Inference Model (EFNIM) to develop an Evolutionary Construc...

The use of evolutionary algorithms for designing fuzzy systems provides them with learning and adaptation capabilities, resulting on what is known as Evolutionary Fuzzy Systems. These types of systems have been successfully applied in several areas of Data Mining, including standard classification, regression problems and frequent pattern mining. This is due to their ability to adapt their work...

This paper describes the application of evolutionary fuzzy systems for subgroup discovery to a medical problem, the study on the type of patients who tend to visit the psychiatric emergency department in a given period of time of the day. In this problem, the objective is to characterise subgroups of patients according to their time of arrival at the emergency department. To solve this problem,...

This paper proposes a new selection mechanism in evolutionary learning for fuzzy systems, which is applied to the learning of shooting action for robot soccer. In generic evolutionary algorithm, since the evaluation and the selection are performed on the level of chromosome, selected chromosome may include non-effective or bad genes, which increase the uncertainty of the solutions. To solve thi...