Imprecise inference models the ability to infer sets of values or information chunks. Imprecise database inference is just as important as precise inference. In fact, it is more prevalent than its precise counterpart even in precise databases. Analyzing the extent of imprecise inference is important in knowledge discovery and database security. Imprecise inference analysis can be used to \mine"...

Fuzzy inference systems and neural networks are complementary technologies in the design of adaptive intelligent systems. Artificial Neural Network (ANN) learns from scratch by adjusting the interconnections between layers. Fuzzy Inference System (FIS) is a popular computing framework based on the concept of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. A neuro-fuzzy system is sim...

This paper deals with the prediction of chaotic time series by using the multi-stage fuzzy inference system and its application to the analysis of operating flexibility. Multi-national corporation obtained by shifting manufacturing plants located in different countries is denoted as operating flexibility. Even though the operating flexibility is optimized by the stochastic dynamic programming u...

The single input rule modules (SIRMs) based type-1 fuzzy inference systems (SIRM-T1FISs), which assign each input item with a rule module, can greatly reduce the number of fuzzy rules and have found lots of applications. This paper extends SIRMT1FISs to the interval type-2 case to achieve better performance. Furthermore, the properties of the SIRMs based interval type-2 fuzzy inference systems ...

The paper presents the design of municipal creditworthiness parameters. Municipal creditworthiness modelling is realized by fuzzy logic based systems. Therefore, current designs of hierarchical structures of Mamdanitype fuzzy inference systems and their analysis are introduced. Key-Words: Municipal creditworthiness, Mamdani-type fuzzy inference systems, hierarchical structures of fuzzy inferenc...

Problems in construction management are complex, full of uncertainty, and vary with environment. Fuzzy logic (FL), neural networks (NNs), and genetic algorithms (GAs) have been successfully applied in construction management to solve various kinds of problems. Considering the characteristics and merits of each method, this paper combines the above three techniques to develop an Evolutionary Fuz...

Cloud detection and analysis from satellite images has been a topic of research in many atmospheric and environmental studies; however, it still is a challenging task for many reasons. In this paper, we propose a new method for cloud-type classification using fuzzy logic. Knowing that visible-light images of clouds contain thickness related information, while infrared images haves height-relate...

Most information discovery processes need to understand the reasons of the success of the inference methods or the usability of the new information, which can sometimes be somehow explained with a few useful measures on the premises or on the chosen relations, logics and implications. This chapter presents a state of art on the latest concepts of measure, from the additive measures, to monotone...