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 ...

A new generation of Oxide Dispersion Strengthened (ODS) alloys called Precipitation Hardened (OPH) alloys, has recently been developed by the authors. The excellent mechanical properties can be improved optimizing chemical composition in combination with heat treatment. However, behavior such materials requires consideration a large number variables, nonlinearities, and uncertainties analyses, ...

This paper presents clustering techniques (K-means, Fuzzy K-means, Subtractive) applied on specific databases (Flower Classification and Mackey-Glass time series) , to automatically process large volumes of raw data, to identify the most relevant and significative patterns in pattern recognition, to extract production rules using Mamdani and Takagi-SugenoKang fuzzy logic inference system types.

A new algorithm for training radial basis function neural networks is presented in this paper. The algorithm, which is based on the subtractive clustering technique, has a number of advantages compared to the traditional learning algorithms, including faster training times and more accurate predictions. Due to these advantages the method proves suitable for developing discrete-time models for c...

Radioactivity is the spontaneous emission of energy from unstable atoms. Radioactive sources have radionuclides. Radionuclide undergoes radioactive decay and emits gamma rays and subatomic particles, constituting the ionizing radiation. The gamma ray energy of a radionuclide is used to determine the identity of gamma emitters present in the source. This paper describes the hardware implementati...

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...

Two neural network models, called clustering-RBFNN and clustering-BPNN models, are created for estimating the work zone capacity in a freeway work zone as a function of seventeen different factors through judicious integration of the subtractive clustering approach with the radial basis function (RBF) and the backpropagation (BP) neural network models. The clustering-RBFNN model has the attract...

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 higher than 50 % by various data mining methods describ...

This paper presents novel GA-ANFIS expert system prototype for dermatological disease detection by using dermatological features and diagnoses collected in real conditions. Nine dermatological features are used as inputs to classifiers that are based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for the first level of fuzzy model optimization. After that, they are used as inputs in Genetic ...