The mountain car problem is a well-known task, often used for testing reinforcement learning algorithms. It is a problem with real valued state variables, which means that some kind of function approximation is required. In this paper, three reinforcement learning architectures are compared on the mountain car problem. Comparison results are presented, indicating the potentials of the actor-onl...

In this paper, a novel method, called the fuzzy-based approach, for mesh simplification is presented. We first propose the fuzzy position uncertainty function and the fuzzy curvature uncertainty function for, respectively, measuring the variation of the surface position and the variation of the surface curvature while meshes are simplified. We then utilize the TSK fuzzy inference model, which i...

The parallel-distributed compensation (PDC) together with Takagi-Sugeno-Kang (TSK) fuzzy modelling proved to be a modern model-based systematic approach for the design of fuzzy nonlinear controllers from stability and robustness requirements. The usual local linear controllers comprise a state feedback. This requires measurements of the state variables or an observer design. The aim of the pres...

In this paper, the idea of fertilizing fuzzy neural networks with wavelets is borrowed and enhanced to introduce a novel neural network named Auto Regressive eXogenous Local Model (ARXLM) network. The enhanced network has a set of notable features compared with previous published fertilized networks. These features can be summarized as follows. First, the proposed network has a simple and plast...

PURPOSE The aim of this study is to explore differences between male and female patients entering a rehabilitation program at a pain clinic in order to gain a greater understanding of different approaches to be used in rehabilitation. METHOD 1371 patients referred to a specialty pain rehabilitation clinic, completed sociodemographic and pain related questionnaires. They rated their pain accep...

In this paper, we propose a new learning algorithm that can be used to design TSK-type neuro-fuzzy networks. Though there has been a great deal of interest in the use of immune algorithms (IAs) for computer science and engineering, in terms of fundamental methodologies, they are not dramatically different from other algorithms. In order to enhance the IA performance, we propose the immune-based...

This study aims to measure the level of accuracy health Islamic banks in Indonesia using RGEC (Risk Profile, Good Corporate Governance, Earning, and Capital) method Takagi-Sugeno-Kang (TSK) Fuzzy Inference System. System is an Artificial Intelligence that can well. The application assessing 12 begins by dividing data into 40 for training 20 testing. inputs used are NPL, LDR, ROA, ROE, NIM CAR. ...

This paper presents a novel personal verification system with thermal facial patterns using fuzzy neural network techniques. In contrast to traditional biometrics, the use of thermal technology removes two concerns in existing verification systems; they are: 1) the hygiene issue for verification systems that require physical contact (e.g., fingerprints) and, 2) variation in ambient illumination...

The indoor human comfort, working efficiency and health are dependent on the control of the quality of air in a heating-ventilation and air-conditioning (HVAC) system. The aim of present paper is to improve this control considering the most important variables – the air temperature, relative humidity and concentration of carbon dioxide by applying fuzzy logic and genetic algorithms (GAs) for co...

This paper proposes an enhanced ant colony optimization with dynamic mutation and ad hoc initialization, ACODM-I, for improving the accuracy of Takagi-Sugeno-Kang- (TSK-) type fuzzy systems design. Instead of the generic initialization usually used in most population-based algorithms, ACODM-I proposes an ad hoc application-specific initialization for generating the initial ant solutions to impr...