Cellular automata: a decision support system for stock market trading

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That is it's a high-risk environment for investors. The DSS can be used by operations management and other planning levels in an organization to compile information and data, and to synthesize it into actionable intelligence. However, the latter plays a critical role in the stock market environment. Carmel O'Grady The email address of this maintainer does not seem to be valid anymore. Business Email. The goal is designing a simulated environment that is similar to the stock for the brokers and enthusiasts to help them to choose an appropriate portfolio. The DSS can either be completely computerized or powered by humans. A learning algorithm of fuzzy neural networks with triangular fuzzy weights. A DSS can generate information and output it graphically, such as a bar chart that represents projected revenue or as a written report. We show that the proposed structure-level adaptive neural networks are superior to fixed-structure neural networks due to the compact size of their hidden layers and improved generalization ability. Typical information used by a DSS include target or projected revenue and sales figures, sales figures from different time periods, and other inventory. A DSS lets users sift through and analyze massive amounts of data, and compile information that can be used to solve problems and make better decisions. The DSS is an application that produces comprehensive information. This allows to link your profile to stock trading decision support system item.

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Cellular automata: a decision support system for stock market trading

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Cellular automata: a decision support system for stock market trading

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