A controller based on neuro-dynamic programming coupled with a fuzzy ARTMAP neural network for a fed-batch bioreactor was developed to roduce cloned invertase in Saccharomyces cerevisiae yeast in a fed-batch bioreactor. The objective was to find the optimal glucose feed rate profile eeded to achieve the highest fermentation profit in this reactive system where the enzyme expression is repressed...

ARTMAP-DS extends fuzzy ARTMAP to discriminate between similar inputs by discounting similarities. When two or more candidate category representations are activated by a given input, features that the candidate representations have in common are ignored prior to determining the winning category. Simulations illustrate the network's ability to recognize similar inputs, such as STAR. and START, i...

Quantitative structural property relations (QSPRs) for boiling points of aliphatic hydrocarbons were derived using a back-propagation neural network and a modified Fuzzy ARTMAP architecture. With the back-propagation model, the selected molecular descriptors were capable of distinguishing between diastereomers. The QSPRs were obtained from four valance molecular connectivity indices (1chiv,2chi...

Osteoporotic is a health burden worldwide, resulting in reduction of physical activity, increased risk of mortality, and incremental medical cost. Mandibular trabecular patterns analyzed on dental panoramic radiographs have been widely studied for identifying postmenopausal women with low skeletal bone mineral density (BMD). In this paper we proposed a new method for detecting osteoporosis usin...

The major aim of processing satellite images is to prepare topical and effectivemaps. The selection of appropriate classification methods plays an important role. Amongvarious methods existing for image classification, artificial neural network method is ofhigh accuracy. In present study, TM images of 1987, and ETM+ images of 2000 and 2006were analyzed using artificial fuzzy ARTMAP neural netwo...

In this paper we investigate the use of a supervised, but self-organizing, Adaptive Resonance Theory type of neural network (Fuzzy-ARTMAP), for first break picking in seismic reflection data. First break picking is the accurate location of the leading energy pulse received by a geophone in response to a seismic shot. The performance of Fuzzy-ARTMAP is compared to our previous work with multi-la...

In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...

Fault diagnosis is a vital discussion in power systems restoration. Recently, much research endeavors have been done for fault section diagnosis of power systems by using several techniques, such as rule-based expert system, logic-based expert system, fuzzy relation based expert system, neural network, optimization techniques based approach, etc. They diagnose the fault from different ways. How...

This paper is a description of recent advances in off-line signature verification research performed at our laboratory. Related works pertain to structural interpretation of signature images, directional PDF used as a global shape factor, the Extended Shadow Code (ESC) and the fuzzy ESC, a cognitive approach based on the Fuzzy ARTMAP, and shape factors related to visual perception.

In this paper, a novel approach is developed using Fuzzy ARTMAP Neural Networks to recognize and classify Swedish road and traffic signs. The Swedish Speed-Limit signs are selected as a case study, but the system can be applied to other signs. A new color detection and segmentation algorithm is presented in which the effects of shadows and highlights are eliminated. Images are taken by a digita...