the classification and regression trees (cart) possess the advantage of being able to handlelarge data sets and yield readily interpretable models. in spite to these advantages, they are alsorecognized as highly unstable classifiers with respect to minor perturbations in the training data.in the other words methods present high variance. fuzzy logic brings in an improvement in theseaspects due ...

non-invasive fetal electrocardiogram (FECG) signal extraction from signals recorded at abdominal area of mother is a challenging problem for the biomedical and signal processing communities. In this paper, we improve the FECG extraction approaches which consist to find the relation-ships between the cardiac potentials generated at the heart level of mother and the potentials recorded on the abd...

In the present study, the energetic and economic modeling of lentil and chickpea production in Esfahan province of Iran was conducted using adaptive neuro-fuzzy inference system (ANFIS) and linear regression. Data were taken by interviewing and visiting of 140 lentil farms and 110 chickpea farms during 2014-2015 production period. The results showed that the yield and total energy consumpti...

This paper first analyzes the soft-sensor technology and temperature measurement technology used in recent soft measurements, focuses on the accuracy and efficiency requirements of soft measurement in slab surface temperature detection. In this paper, we collects images noise processes of continuous casting slabs, and uses component-based OTSU segmentation method to extract the slab area and th...

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 ...

Addressing crime detection, cyber security and multi-modal gaze estimation in biometric information recognition is challenging. Thus, trained artificial intelligence (AI) algorithms such as Support vector machine (SVM) adaptive neuro-fuzzy inference system (ANFIS) have been proposed to recognize distinct discriminant features of (intrinsic hand demographic cues) with good classification accurac...

In the mechanical pulping process, some process state and product quality variables are difficult to measure on-line. In this paper, soft sensors were used to estimate Canadian Standard Freeness (CSF) and outlet consistency (Cout) after the high consistency refining stage of the alkaline peroxide mechanical pulping (APMP) process. After the secondary variables for modeling that are readily avai...

In the present study, the energetic and economic modeling of lentil and chickpea production in Esfahan province of Iran was conducted using adaptive neuro-fuzzy inference system (ANFIS) and linear regression. Data were taken by interviewing and visiting of 140 lentil farms and 110 chickpea farms during 2014-2015 production period. The results showed that the yield and total energy consumpti...

Interest in system identification especially for nonlinear systems has significantly increased in the past few decades. Soft-computing methods which concern computation in an imprecise environment have gained significant attention amid widening studies of explicit mathematical modelling. In this research, an adaptive neuro-fuzzy inference system (ANFIS) network design is deployed and used for m...

Imaging plays an important role in medical field like medical diagnosis, treatment planning and patient follow up. Image segmentation is the backbone process to accomplish these tasks by dividing an image in to meaningful parts which share similar properties. Medical Resonance Imaging (MRI) is primary diagnostic technique to do image segmentation. There are several techniques proposed for image...