A semi-mechanistic fuzzy modeling technique is proposed to obtain compact and transparent process models based on small data-sets. Semi-mechanistic models are hybrid models that consist of a white box structure based on mechanistic relationships and black-box substructures to model less defined parts. First, it is shown that certain type of white-box models can be efficiently incorporated into ...

Job scheduling is an important but difficult task to wafer fabrication factories. To further improve the performance of job scheduling in a wafer fabrication factory, a fuzzy-neural dynamic-bottleneck-detection (DBD) approach is proposed in this study. The fuzzy-neural DBD approach is modified from the traditional DBD approach after incorporating some major changes. First, taking into account t...

Unit commitment optimization for the scheduling of units and effective load sharing among thermal units is extensively used in electrical power system planning. The target of unit commitment optimization will be economical when the criteria is to test the best combination of thermal units to serve the load with the optimium load sharing among units satisfying various constraints like load deman...

The present paper describes the development of a simple yet effective gain scheduling type fuzzy PID controller algorithm that can employ fuzzy adaptation to dynamically vary conventional PID controller gain(s). While one scheme can dynamically vary the reset rate only, an even improved scheme can effectively vary both proportional gain and reset rate of a PID controller simultaneously, employi...

We present a unified logical framework for representing and reasoning about both quantitative and qualitative preferences in fuzzy answer set programming [Saad, 2010; Saad, 2009; Subrahmanian, 1994], called fuzzy answer set optimization programs. The proposed framework is vital to allow defining quantitative preferences over the possible outcomes of qualitative preferences. We show the applicat...

The task of finding the crisp critical path has received researcher’s attention over the past two decades which has wide range of applications in planning and scheduling the large projects. In most cases of our life, the data obtained for decision makers are only approximate, which gives rise to fuzzy critical path problem. In this paper, new ranking methods are introduced to identify the fuzzy...

Classical automata theory cannot deal with the system uncertainty. To deal with the system uncertainty the concept of fuzzy finite automata was proposed. Fuzzy automata can be used in diverse applications such as fault detection, pattern matching, measuring the fuzziness between strings, description of natural languages, neural network, lexical analysis, image processing, scheduling problem and...

Imprecise input data imposes special challenges to grid scheduling. This paper introduces a novel scheduler based on fuzzy optimization called IP-FULL-FUZZY which considers uncertainties of both application demands and of resource availability. The effectiveness of the proposed scheduler is compared to that of three non-fuzzy schedulers, as well as to that of a fuzzy scheduler which considers o...

Cloud computing is an Information Technology deployment model established on virtualization. Task scheduling states the set of rules for task allocations to exact virtual machine in cloud environment. However, challenges such as optimal performance solutions, are addressed computing. First, due improved by proposing a Dynamic Weighted Round-Robin algorithm. This recommended DWRR algorithm impro...