The application of neural networks and a qualitative response model to the auditor's going concern uncertainty decision

Article Abstract:

The feasibility of using neural networks to assist the auditor in making an unqualified audit report or a modified report indicating a going concern uncertainty was evaluated. Three networks were used in the study, namely, the generalized reduced gradient optimizer for neural network learning, a backpropagation neural network and a logit model. Results show that all the three networks are capable of giving reliable results, although with different levels of accuracy.

Computer networks, Auditing, Practice, Neural networks, Information management

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The detection of nuclear materials losses

Article Abstract:

A new methodology for identifying and locating materials losses in nuclear storage facilities has been developed. The method, called the Joint Estimation procedure, has been proven to be very robust to outliers and capable of identifying different forms of diversion by means of alternative hypothesis tests. These different forms of materials losses include a one-time loss, a protracted loss of a short duration and long-term protracted removal.

Nuclear industry, Logistics, Materials management

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An analysis of fuzzy clustering and a hybrid model for the auditor's going concern assessment

Article Abstract:

Research is presented concerning the development and testing of a hybrid fuzzy clustering model which can be used to support an auditor's evaluation of a going concern. Factors influencing bankruptcy are discussed.

Business Failures, Research, Beliefs, opinions and attitudes, Fuzzy logic, Decision support systems, Fuzzy systems, Cluster analysis

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