Neural networks in business: techniques and applications for the operations researcher

TL;DR: The study found that neural-network models such as feedforward and feedback propagation artificial neural networks are performing better in its application to human problems and proposed feedforwardand feedback propagation ANN models for research focus based on data analysis factors like accuracy, processing speed, latency, fault tolerance, volume, scalability, convergence, and performance.

TL;DR: A comprehensive review of 196 studies which employ operational research (O.R.) and artificial intelligence (A.I.) techniques in the assessment of bank performance is presented in this article.

TL;DR: Knowledge Management: Systems and Processes as mentioned in this paper is a complete introduction to the subject of knowledge management, and incorporates technical as well as social aspects, concepts and principles, and practical examples.

TL;DR: A survey of journal articles on neural network business applications published between 1988 and 1995 indicates that an increasing amount of neural network research is being conducted for a diverse range of business activities.

TL;DR: The authors demonstrate that Hopfield-type networks can find reasonable solutions to the traveling salesman problem (TSP) and the optimal list-matching problem (LMP) and show how to avoid the difficulties encountered by G.V. Wilson and G.S. Pawley by using a modified energy functional.