Many endangered plants such as Eryngium viviparum (Apiaceae) present a poor germination rate. This fact could be due to intrinsic and extrinsic seed variability influencing germination and dormancy of seeds. The objective of this study is to better understand the physiological mechanism of seed latency and, through artificial intelligence models, to determine the factors that stimulate germinat...

Fuzzy Logic is an innovative technology that enables the implementation of ‘intelligent’ functions in embedded systems. One of its advantages is, that even complicated functions and adaptive control loops can be implemented with the limited resources of low-cost 8 bit microcontrollers. We will discuss development methodologies, tools used, and code speed/size requirements of three case studies....

This document describes the implementation of a conical tank control system using an adaptive neurofuzzy system. For implementation, indirect approach is used where controller optimized model obtained during plant identification carried out data operation. Furthermore, includes training neuro fuzzy-systems and application to tank. Regarding identification, preliminary takes place for different ...

The ability to simulate the propagation of flood waves is of crucial importance for planning and operational management of river floods. Hydrodynamic and hydrologic numerical models provide such capabilities and represent conventional approaches to river flood modelling. In the recent years, data driven models such as artificial neural networks (ANNs), and neurofuzzy systems have also emerged a...

The paper is a survey of the soft computing methods and their application to the data mining problems. Neural networks, fuzzy sets, neurofuzzy systems, and genetic algorithms are considered. The advantages and disadvantages of the soft computing tools as well as specific issues of their application to the processing of large datasets are analyzed, and the directions for their further improvemen...

The paper compares the use of neural network and neurofuzzy approaches in diagnosis of endogenous intoxication syndrome. The comparison was carried out on real patient data. Data preprocessing, neural network design and experiments are reported. A fuzzy neural network and results of experiments with it are presented. The advantages of fuzzy neural network are shown.

Based on the hypothesis that the brain is a society of semiautonomous neural agents and full autonomy is the result of coordination of semiautonomous functionalities, a multiagent data warehousing (MADWH) and multiagent data mining (MADM) approach is presented for brain modeling and illustrated with robot motion control. An algorithm named Neighbor-Miner is proposed for MADWH and MADM. The algo...