The design and implementation of an intelligent agent-based negotiation shopping system
Multiagent and Grid Systems
An intelligent system integrated with fuzzy ontology for product recommendation and retrieval
FS'07 Proceedings of the 8th Conference on 8th WSEAS International Conference on Fuzzy Systems - Volume 8
Fuzzy Sets and Systems
Intelligent fabric hand prediction system with fuzzy neural network
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Journal of Global Optimization
Artificial neural network in FPGA for temperature prediction
NOLISP'11 Proceedings of the 5th international conference on Advances in nonlinear speech processing
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Multiregression based on upper and lower nonlinear integrals
International Journal of Intelligent Systems
A hybrid fuzzy intelligent agent-based system for stock price prediction
International Journal of Intelligent Systems
Enhanced fuzzy-filtered neural networks for material fatigue prognosis
Applied Soft Computing
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Weather forecasting has been one of the most challenging problems around the world for more than half a century. Not only because of its practical value in meteorology, but it is also a typical "unbiased" time series forecasting problem in scientific research. In this paper, we propose an innovative, intelligent multiagent-based environment, namely intelligent Java Agent Development Environment (iJADE), to provide an integrated and intelligent agent-based platform in the e-commerce environment. In addition to the facilities found in contemporary agent development platforms, which focus on the autonomy and mobility of the multiagents, iJADE provides an intelligent layer (known as the "conscious layer") to implement various AI functionalities in order to produce "smart" agents. From an implementation point of view, we introduce a weather forecasting system known as iJADE WeatherMAN - a weather forecasting system that uses fuzzy-neuro-based intelligent agents for automatic weather information gathering and filtering, and for time series weather prediction. Compared with the previous studies on single point sources using a similar network and other networks, such as the radial basis function network, learning vector quantization and the Naïve Bayesian network, our experimental results are very promising. This neural-based rainfall forecasting system is useful and can be used in parallel with traditional forecast methods that are used at the Hong Kong Observatory.