This present paper is an efficient solution to control the basis weight of paper in pulp and paper industry using a fuzzy logic controller. The traditional systems are based on operator’s experience and data provided by the mill. The decision of the operator is not exact but good enough or appropriate. Fuzzy Logic offers a promising solution to this conceptual design through fuzzy modeling. Fuz...

Human-based quality control reduces the accuracy of this process. Also, the speed of decision making in some industries is very important. For removing these limitations in human-based quality control, in this paper, the design of an expert system for automatic and intelligent quality control is investigated. In fact, using an intelligent system, the accuracy in quality control is increased. It...

Controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. Interval type-2 fuzzy logic systems (IT2FLS) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. In contrast, adaptive sliding modecontrol (ASMC) provides...

The use of fuzzy logic to describe abstract concepts and when designing decision making systems to make decisions that are much closer to the way a human does is an interesting and useful area to explore. To effectively implement these types of systems expert knowledge is required in the application area. This can be a problem if the people designing a system of this nature are not experts in t...

Moved by the need increased for modeling of the fuzzy data, the success of the systems of exact generation of summary of data, we propose in this paper, a new approach of generation of summary from fuzzy data called “FuzzySaintEtiQ”. This approach is an extension of the SaintEtiQ model to support the fuzzy data. It presents the following optimizations such as 1) the minimization of the expert r...

Generation expansion planning is a challenging problem due to its large-scale, long-term, non-linear, and discrete nature of generation unit size. Since the computation revolution, there are several emerging techniques proposed to solve large scale optimization problem. Many of these techniques have been reported to use in generation expansion planning. This paper will describe these emerging o...

In this paper we introduce an application of intervalvalued systems to the segmentation of prostate ultrasound images. The system classifies each pixel as prostate or background. The input variables are the values of each pixel in different processed images as proximity, edginess and enhanced image. The system has 20 rules and is trained with ideal images segmented by an expert. Interval-valued...

This paper reports on the conceptual development of an architecture for building intelligent fuzzy decision support systems (IFDSS). The changing nature of decision making today’s fast paced environment calls for new techniques for dealing with both quantitative and qualitative components of decision making. Soft computing tools like fuzzy reasoning offer much promise in this area. After review...

I T IS a well-recognized fact that the theory of fuzzy sets and systems, for the last four decades after the seminal paper by Professor Zadeh [1], has demonstrated its remarkable ability to go beyond conventional information representation. It resulted in a wide range of new formulations of practical problems, such as fuzzy control, fuzzy clustering and classification , fuzzy modeling, and fuzz...

Full type-2 fuzzy techniques provide a more adequate representation of expert knowledge. However, such techniques also require additional computational efforts, so we should only use them if we expect a reasonable improvement in the result of the corresponding data processing. It is therefore important to come up with a practically useful criterion for deciding when we should stay with interval...