To recognize functional sites within a protein sequence, the non-numerical attributes of the sequence need encoding prior to using a pattern recognition algorithm. The success of recognition depends on the efficient coding of the biological information contained in the sequence. In this regard, a bio-basis function maps a non-numerical sequence space to a numerical feature space, based on an am...

The word biometrics refers to the use of physiological or biological characteristics of human to recognize and verify the identity of an individual. Face is one of the human biometrics for passive identification with uniqueness and stability. In this manuscript we present a new face based biometric system based on neural networks supervised self organizing maps (SOM). We name our method named S...

Through a comprehensive study of existing fuzzy neural systems, this paper presents a Choquet integral-OWA operator based fuzzy neural system named AggFNS as a new hybrid method of CI, which has advantages in universal fuzzy inference operators and importance factor expression during reasoning process. AggFNS was applied in traffic level of service evaluation problem and the experimental result...

In this paper, a Pseudo-Gaussian-based Recurrent Compensatory Fuzzy Neural Network (PG-RCFNN) is proposed for identification of dynamic systems. The recurrent network is embedded in the PG-RCFNN by adding feedback connections in the second layer, where the feedback units act as memory elements. The compensatorybased fuzzy reasoning method is using adaptive fuzzy operations of fuzzy neural netwo...

membership in each class. This viewpoint not only reflects the reality of many applications in which categories have fuzzy boundaries, but also Provides a simple representstion of the potentially complex partition of the feature space. In brief, we use fuzzy i fthen rules to describe a ChsSifier. A typical fuzzy classification rule is like: Fuzzy classification is the task of partitioning a fea...

The goal of this project was two-fold: (1) to provide an algorithm to correctly find and label named entities in text, and (2) to uncover substructure in the named entities (such as a first name, last name distinction among person entities). The underlying algorithm used is a Class Hidden Markov Model (CHMM), a Hidden Markov Model with hidden states that emit observed words as well as observed ...

-The multi-criteria decision making (MCDM)problems with fuzzy preference information on alternatives are essential problems of the importance of weighting and ranking. In order to solve this problem, Analytical Hierarchy Process(AHP) and fuzzy comprehensive evaluation method are coupled to form a new approach named Fuzzy-AHP.This method is different from the traditional FAHP,which used to facil...

This paper analyzes sensitivity of Fuzzy C-means to noisy which generates unreasonable clustering results. We also find that Fuzzy C-means possess monotonicity, which may generate meaningless clustering results. Aiming at these weak points, we present an improved Fuzzy C-means named IFCM (Improved Fuzzy C-means). Firstly, we research the reason of sensitivity and find that constraint leads to s...