Download Soft Computing Applications in Business by Chris Matthews, Esther Scheurmann (auth.), Bhanu Prasad PDF
By Chris Matthews, Esther Scheurmann (auth.), Bhanu Prasad (eds.)
Soft computing ideas are established in such a lot companies. This ebook includes numerous very important papers at the functions of soppy computing ideas for the enterprise box.
The tender computing ideas utilized in this booklet contain (or very heavily similar to): Bayesian networks, biclustering equipment, case-based reasoning, information mining, Dempster-Shafer concept, ensemble studying, evolutionary programming, fuzzy choice bushes, hidden Markov versions, clever brokers, k-means clustering, greatest probability Hebbian studying, neural networks, opportunistic scheduling, likelihood distributions mixed with Monte Carlo tools, tough units, self organizing maps, help vector machines, doubtful reasoning, different statistical and desktop studying innovations, and combos of those strategies.
The companies or enterprise difficulties addressed during this booklet contain (or very heavily similar to): research of correlations among forex charges, research of united states banks and Moody’s financial institution monetary energy score, arrears administration, company chance id, corporation audit cost evaluate, dental remedies, enterprise inner keep watch over, clever tutoring structures and academic overview, modeling agent habit, motor assurance undefined, mortgage defaults, pricing recommendations for expanding the industry percentage, pricing recommendations in offer chain administration, probabilistic revenues forecasting, consumer relevance suggestions research for on-line textual content retrieval, and international crude oil spot expense forecasting.
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1 Results on the Simplified Difference Dataset In this experiment we work on a simplified difference dataset. A threshold α is defined to make the simplification more reasonable. We use the symbol a to represent an element of the difference dataset. The simplification is as follows: 1. If a>0 and |a|>α, a is replaced with 1. 2. If a<0 and |a|>α, a is replaced with −1. 3. If |a|≤α, a is replaced with 0 After simplification, the generated new dataset contains 1, −1 and 0 only. 1 means upward change, −1 means downward change and 0 means no change.
Smith School of Business, Van Munching Hall, University of Maryland, College Park, MD 20742. edu 3 Department of Computer Science, A. V. edu Abstract. Artificial societies are computer models in which the collective behavior of a population of simulated human decision makers is observed over time. Here we describe an artificial society of “soft computing agents” (model consumers) making probabilistic purchasing decisions about new technological products that are introduced by competing firms. The model is studied under varying conditions to determine the relative success of these firms as they pursue different pricing strategies designed to increase their market share.
In this bicluster, the first 16 months of the total 26 months are in the period from March 1996 to June 1997. In this period, the exchange rates for the three currencies are almost unchanged. Just as the analysis for Bicluster 1, this essential accords with the fact that Argentina, Egypt and Philippine implemented a strictly fixed exchange rate regime in the period from March 1996 to June 1997. We also find that the amount of change in the exchange rates for the three currencies becomes larger from the 17th month of the total 26 months.