Stock Market Prediction with Multiple Regression, Fuzzy Type-2 Clustering and Neural Networks

AbstractStock market forecasting research offers many challenges and opportunities, with the forecasting of individual stocks or indexes focusing on forecasting either the level (value) of future market prices, or the direction of market price movement. A three-stage stock market prediction system is introduced in this article. In the first phase, Multiple Regression Analysis is applied to define the economic and financial variables which have a strong relationship with the output. In the second phase, Differential Evolution-based type-2 Fuzzy Clustering is implemented to create a prediction model. For the third phase, a Fuzzy type-2 Neural Network is used to perform the reasoning for future stock price prediction. The results of the network simulation show that the suggested model outperforms traditional models for forecasting stock market prices

Enhancement of Transparency and Adaptability by Online Tracking of Enterprise Processes

Enterprises are seeking novel approaches to reduce cost in complying with regulations and requirements from original equipment manufacturers. Consequently, enterprises are investing in manufacturing execution system (MES) solutions for realizing these requirements. However, most of the MES solutions do not support processing of real-time process data acquired from shop floor for online monitoring and control of enterprise processes. Further, monitoring of enterprise processes can be classified into online tracking and passive tracing. In the contribution, a framework is envisaged for online tracking of enterprise processes based on MES concepts. This framework has been validated in an industrial scenario

Eine service-orientierte Grid-Infrastruktur zur Unterstützung medienwissenschaftlicher Filmanalyse

Innerhalb des von der DFG (SFB/FK 615) geförderten Projektes „Methoden und Werkzeuge zur rechnergestützten medienwissenschaftlichen Analyse“ werden Verfahren und Werkzeuge entwickelt, die Medienwissenschaftler bei der Analyse von audiovisuellen Daten unterstützen sollen. In diesem Beitrag wird die Videoanalyse-Software Videana vorgestellt, die eigens entwickelte Verfahren und Konzepte zur Analyse von audio-visuellen Daten beinhaltet. Weiterhin werden Forschungsarbeiten bezüglich einer Grid-Infrastruktur zur Unterstützung medienwissenschaftlicher Forschungsarbeiten sowie zur service-orientierten Analyse von Multimediadaten präsentiert. So verfügt Videana beispielsweise über eine integrierte Grid-Anbindung und erlaubt Mitgliedern einer virtuellen Organisation, rechenintensive Analyseaufgaben auf externen Rechenressourcen auszuführen

ON GRID TECHNOLOGY IN SCIENCE, MEDIA AND INDUSTRY

In the past decade, several national programs for establishing Grid-infrastructures for computationally and data expensive scientific research fields were started. The understanding of the term Grid technology will be given first and the distinction in using this technology in science, media and industry/business is discussed. The German E-Science initiative which started in September 2005 is presented in more detail. The project InGrid, in which the author is involved, for scientific, engineering applications, and collaboration in modelling, simulation and optimization is pointed out with its research goals. For the use of Grid technology in industry the concept of business Grids is discussed and the state of the current research in this area based on value chain analysis is given. Here the focus is put on the use of Grid technology in small and meduim sized enterprises (SME). As an outlook the role of service-oriented computing is discussed.The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.htmlIFSR 2005 : Proceedings of the First World Congress of the International Federation for Systems Research : The New Roles of Systems Sciences For a Knowledge-based Society : Nov. 14-17, 2045, Kobe, JapanSymposium 6, Session 1 : Vision of Knowledge Civilization Future of Knowledge Civilizatio

ON SCALABILITY IN SIMULATION AND OPTIMIZATION OF COMPLEX SYSTEMS

Advances in processing power of modern computer hardware allow the analysis of increasingly complex systems by means of simulation. However, many engineering problems such as design optimization problems in the aircraft industry, facility management in the water industry or design problems in the automotive industry have extremely high computational demands. To solve these problems in reasonable time, parallel computing must be utilized. The availability of affordable parallel computing systems in the form of network of workstations or compute clusters as well as the dawn of grid computing and servcice-oriented architectures is beginning to make parallel computing accessable to a broader community. To exploit the total processing power of many CPUs, intelligent, scalable algorithms are required. In this paper, the concept of scalability is examined in the context of parallel simulation software systems and the distributed solution of simulation-based optimization problems.The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.htmlIFSR 2005 : Proceedings of the First World Congress of the International Federation for Systems Research : The New Roles of Systems Sciences For a Knowledge-based Society : Nov. 14-17, 2088, Kobe, JapanSymposium 3, Session 3 : Intelligent Information Technology and Applications Networks and Agent