Application of the back propagation neural network algorithm with monotonicity constraints for two-group classification problems

Article Abstract:

The potentials of a single output neural network with a sigmoid activation function and the BPLMS learning algorithm are investigated. In line with this, monotonicity constraints are applied to the back propagation learning algorithm to improve neural network learning ability in generating classification boundaries. When the sample data set is controlled by a linear classification function, there is improvement in neural network performance when the vectors are related monotonically.

Computer networks, Neural networks, Heuristic programming

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How prevalent are stable-Paretian distributed financial variables?

Article Abstract:

An analysis describing financial variable modeling is presented. Earlier studies have supported the use of the stable-Paretian distribution model for explaining financial variables such as stocks, futures prices and exchange rates. However, more recent studies show that the Paretian model lacks enough basis for application to stable-distributed financial variables. In addition, it is shown that a number of accounting ratios exhibit stability as modeling variables.

Models, Financial markets

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Cost efficiency benchmarking for operational units with multiple cost drivers

Article Abstract:

Research is presented concerning the development of a validation model based on data published by property tax collection offices in the metropolitan area of London. Maximum performance efficiency is discussed.

Cost Control Techniques, Evaluation, Industrial efficiency, Economic efficiency, Data envelopment analysis, Statistics, Statistics (Data), Benchmarks, Benchmarking, Cost (Economics), Costs (Economics), Cost control

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