The fuzzy time series approaches, which recently are intensively considered by the researchers, consist of three stages of fuzzification, determination of fuzzy relations and defuzzification. Several studies using different approaches in these steps have been conducted in literature. In most of the studies related fuzzy time series, the membership degrees of belonging to every fuzzy set of each...

This paper proposes an adaptive neuro-fuzzy inference system (ANFIS) and a KERNEL System to solve the problem of predicting rush orders for regulating the capacity reservation mechanism in advance. The adopted approaches generalize the association rules among rush orders, as well as to forecast product items, quantities and the occasion of the contingent rush orders via learning from the sales ...

One of the most promising areas scientific research in field analysis, forecasting and modelling economic phenomena processes is fuzzy logic. In article with use logic apparatus (Fuzzy Logic toolkit MATLAB software package) a model for assessing development manufacturing indicators developed. Key evaluating activities energy enterprises are analysed. The based on microeconomic enterprises’ effi...

Semiconductor wafer fabrication is a very complex manufacturing process. Many semiconductor processes are not very well understood. The control of semiconductor manufacturing processes is, thus, an active research area. Even though various algorithms have been developed for process control and optimization, the scope of application of these algorithms is not very well-characterized due to the c...

background: automobile manufacturing industries are considered among the main sites where accidents are likely to happen. from a cognitive point of view, stress can cause problems such as poor concentration, absent-mindedness, and hesitancy while making decisions. this study examines the relationship between job stress and occupational accidents in an automobile manufacturing company. methods: ...

In this study, a fuzzy probability-based Markov chain model is developed for forecasting regional long-term electric power demand. The model can deal with the uncertainties in electric power system and reflect the vague and ambiguous during the process of power load forecasting through allowing uncertainties expressed as fuzzy parameters and discrete intervals. The developed model is applied to...

Several supply chain and production planning models in the literature assume the demands are fuzzy but most of them do not offer a specific technique to derive the fuzzy demands. In this study, we propose a methodology to obtain a fuzzy-demand forecast that is represented by a possibilistic distribution. The fuzzy-demand forecast is found by aggregating forecasts based on different sources; nam...

This study proposes design concepts for a comprehensive home financial learning environment that individual investors can use as a reference in establishing web-based learning and investment platforms. This study also introduces a hybrid approach that demonstrates a data mining function of the financial learning environment. Known as Fuzzy BPN, this approach is comprised of backpropagation neur...