Many factors can impact large-scale enterprise management systems, and maintaining these systems can be a complicated and challenging process. Therefore, businesses can benefit from an assortment of models and management styles to track and collect data for processes. Enterprise Business Modeling, Optimization Techniques, and Flexible Information Systems supplies a wide array of research on the intersections of business modeling, information systems, and optimization techniques. These various business models and structuring methods are proposed to provide ideas, methods, and points of view for managers, practitioners, entrepreneurs, and researchers on how to improve business processes.
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Produktdetaljer

ISBN
9781466639485
Publisert
2013-04-30
Utgiver
Vendor
Business Science Reference
Høyde
279 mm
Bredde
216 mm
Aldersnivå
U, P, 05, 06
Språk
Product language
Engelsk
Format
Product format
Kombinasjonsprodukt
Antall sider
252

Om bidragsyterne

Petraq Papajorgji is a professor and dean of engineering at the Canadian Institute of Technology, Albania. His field of reseach is modelling of complex information system. He is author of a number of books in modelling and has a number of publications in his research area. Alaine Margarete Guimarães is a professor in the Computer Sciences Department and serves the State University of Ponta Grossa – Brazil as Director of Research. Dr Alaine teaches classes and guides students in Computer Engineering undergraduate and in Applied Computation graduate degrees. Dr. Alaine has experience in Computer Science with emphasis in Computational Intelligence, acting on the following subjects: agricultural data mining, intelligent systems and information technology applied to agriculture. Current research focuses on agricultural data mining. Dr Alaine is International Editorial Review Board member of International Journal of Agricultural and Environmental Information Systems (IJAEIS) and a Affiliated member of Brazillian society of Computer Science in Agriculture. Mario Guarracino is researcher at High Performance Computing and Networking Institute of the Italian National Research Council. He received a PhD in Mathematics an Ms in Applied Mathematics from University of Naples Federico II. His postdoctoral training from National Research Council focused on low cost high performance architectures for scientific computing. He has been collaborating with Center for Applied Optimization at University of Florida since 2005. He has taught various graduate and undergraduate courses in computer science, statistics and mathematics. His research interests include machine learning methods for computational biology and planning and development of high performance computational components for parallel and distributed problem solving environments. He is author of publications in the field of high performance scientific computing, computational biology and machine learning.