Thermal errors can have significant effects on CNC machine tool accuracy. The errors come from thermal deformations of the machine elements caused by heat sources within the machine structure or from ambient temperature change. The effect of temperature can be reduced by error avoidance or numerical compensation. The performance of a thermal error compensation system essentially depends upon th...

This paper presents a comparative study between three versions of adaptive neuro-fuzzy inference system (ANFIS) algorithms and a pseudo-forward equation (PFE) to characterize the North Sea reservoir (F3 block) based on seismic data. According to the statistical studies, four attributes (energy, envelope, spectral decomposition and similarity) are known to be useful as fundamental attributes in ...

This paper presents an optimum network structure based on a BBO tuned adaptive neuro-fuzzy inference system (ANFIS) to control active suspension (ASS). The unsupervised learning via Biogeography-Based Optimization (BBO) algorithm is used train the ANFIS network. optimal proportional-integral-derivative controller LQR method generate training data set. base Fuzzy c-means (FCM) clustering applied...

Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some k...

The development of an excavation damaged zone (EDZ) around an underground excavation can change the physical, mechanical and hydraulic behaviors of the rock mass near an underground space. This might result in endangering safety, achievement of costs and excavation planed. This paper presents an approach to build a prediction model for the assessment of EDZ, based upon rock mass characteristics...

Churn prediction is a useful tool to predict customer at churn risk. By accurate prediction of churners and non-churners, a company can use the limited marketing resource efficiently to target the churner customers in a retention marketing campaign. Accuracy is not the only important aspect in evaluating a churn prediction models. Churn prediction models should be both accurate and comprehensib...

Three Neuro-Fuzzy Inference Systems (ANFIS) including Grid Partitioning (GP), Subtractive Clustering (SCM) and Fuzzy C-means clustering Methods (FCM) have been used to predict the groutability of granular soil samples with cement-based grouts. Laboratory data from related available in litterature was used for the tests. Several parameters were taken into account in the proposed models: water:ce...

Thermal errors are often quoted as being the largest contributor to CNC machine tool errors, but they can be effectively reduced using error compensation. The performance of a thermal error compensation system depends on the accuracy and robustness of the thermal error model and the quality of the inputs to the model. The location of temperature measurement must provide a representative measure...

Methods for supervised and unsupervised clustering and machine learning were studied in order to automatically model relationships between gene expression data and gene functions of the microorganism Escherichia coli. From a pre-selected subset of 265 genes (belonging to 3 functional groups) the function has been predicted with an accuracy of 63-71 % by various data mining methods described in ...