This paper presents a new computer aided detection method for identifying malignant images in digital mammograms using fuzzy soft set theory approach. Fuzzy soft set theory is a mathematical model based on parameterization concept for solving uncertainties and we have implemented a more efficient decision making method using fuzzy soft aggregation operator. This method helps the radiologists to...

In this paper, Neuro-Fuzzy based Fuzzy Subtractive Clustering Method (FSCM) and Self Tuning Fuzzy PD-like Controller (STFPDC) were used to solve non-linearity and trajectory problems of pitch AND yaw angles of Twin Rotor MIMO system (TRMS). The control objective is to make the beams of TRMS reach a desired position quickly and accurately. The proposed method could achieve control objectives wit...

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...

An Algorithm to Model Paradigm Shifting in Fuzzy Clustering p. 70 ANFIS Synthesis by Hyperplane Clustering for Time Series Prediction p. 77 Generalized Splitting 2D Flexible Activation Function p. 85 Face Localization with Recursive Neural Networks p. 99 Multi-class Image Coding via EM-KLT Algorithm p. 106 A Face Detection System Based on Color and Support Vector Machines p. 113 A Neural Archit...

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 ...

Text Categorization (TC) is the automated assignment of text documents to predefined categories based on document contents. For the past few years, TC has become very important essentially in the Information Retrieval area, where information needs have tremendously increased with the rapid growth of textual information sources such as the Internet. In this paper, we compare , for text categoriz...

Keyword Extraction is the process of assigning keywords to a document where the important words are selected by the system automatically. This proposed frame work is used to extract the keywords using Fuzzy logic method from Meeting Transcripts. At first, the given input is preprocessed. Subsequently, the preprocessed data will be sent to the features extraction method. In this method three fea...

Brain tumor is the most deadly disease that affects human life span. To segment the brain tumor part, many segmentation techniques have been emerged in image processing like region based Segmentation, Boundary based segmentation. In this paper, several entropies based methods and several cluster techniques are compared and analyzed for brain tumor segmentation. Several entropies such as rough e...

As the number of networked computers grows, intrusion detection is an essential component in keeping networks secure. Various approaches for intrusion detection are currently being in use with each one has its own merits and demerits. This paper presents our work to test and improve the performance of a new class of decision tree c-fuzzy decision tree to detect intrusion. The work also includes...