A Neuro-computing Decision Support Environment
NeuCom represents a new generation of a computer environment, it is a self-programmable, learning and reasoning computer environment based on connectionist (Neurocomputing) modules. NeuCom learns from data, thus evolving new connectionist modules. The modules can adapt to new incoming data in an online incremental, life-long learning mode, and can extract meaningful rules that would help people discover new knowledge in their respective fields. NeuCom is based on the theory of Evolving Connectionist Systems (ECOS), proposed for the first time by Professor Nikola Kasabov, as published in (“Evolving connectionist systems: methods and applications in bioinformatics, brain study, and intelligent machines”, N.Kasabov, Springer Verlag, London, 2002). Knowledge Engineering Consulting offers a comprehensive suite of services designed to facilitate the deployment of NeuCom in a variety of projects across health, economic, and financial domains.
Textbook: N.Kasabov, Evolving connectionist systems: The knowledge engineering approach, Springer, 2007,
https://doi.org/10.1007/978-1-84628-347-5. The NeuCom architecture from Kasabov, N. NeuCom: www.theneucom.com
NeuCom can be used to solve complex problems. Such problems are clustering, classification, prediction, adaptive control, data mining, and pattern discovery from databases in a multidimensional, dynamic, and possibly changing data environment. Applications span all areas of Science, Engineering, Medicine, Bio-informatics, Business, Arts and Design, and Education.
NeuCom is both a decision support system and a DSS development environment. NeuCom can be used either as a decisions support system (DSS), where users specify their task and define data to be used, in order to obtain a solution, or - as a DSS development environment for building sophisticated problem-oriented intelligent DSS. The end users in the former case are people who have never programmed computers, but have databases available and need a decision to be made based on existing data and/or human knowledge. In the latter case, users are professional system developers who can develop DSS for various applications in collaboration with experts in the field.