The prevention of credit card fraud is an important application for prediction technique. One major obstacle for using neural network training techniques is the high necessary diagnostic quality: Since only one financial transaction of a thousand is invalid no prediction success less than 99.9% is acceptable. Due to these credit...
This paper illustrates a new approach to characterizing the Frio sandstones for field appraisal. This original methodology is based on seismic facies analysis (using neural network technology applied to seismic-trace shape) combined with petroacoustic modeling from well curves. Seismic facies maps were used to characterize and analyze channel sands. Seismic...
Risk analysis and management of petroleum exploration ventures is growing worldwide and many international petroleum companies have improved their exploration performance by using principles of risk analysis in combination with new technologies This paper intends to show how two different methodologies, a Monte Carlo simulation method and a connectionist approach...
The brand choice problem in marketing has recently been addressed with methods from computational intelligence such as neural networks. Another class of methods from computational intelligence, the so-called ensemble methods such as boosting and stacking has never been applied to the brand choice problem. Ensemble methods generate a number of...
The outcome prediction models using Artificial Neural Network ANN and multivariable logistic regression analysis have been developed in many areas of health care research. Both these methods have advantages and disadvantages. This paper talks about a study which compares the performance of artificial neural network and multivariable logistic regression models,...
This white paper study deals with testing a neural network strategy for a combined analysis of two gene polymorphisms. A Multi Layer Perceptron model showed the best performance and was therefore selected over the other networks. The polymorphism in the transcriptional control region upstream of the 5HTT coding sequence SERTPR...
Supply chain management is a critically significant strategy that enterprises depend on in meeting the challenges of today's highly competitive and dynamic business environments. An important aspect of supply chain management is how enterprises can detect the supply chain behavioral changes due to endogenous and/or exogenous influences and to predict...
Quality improvement provides organizations with significant opportunities to reduce costs, increase sales, provide on time deliveries and foster better customer relationships. The design and manufacturing are among the critical processes for continuous quality improvement. Time series data collected from these processes are the useful source. While there are various techniques...
This paper presents a method of selecting cotton bales to meet the specified ring yarn properties using artificial neural networks. Five yarn properties and yarn count were used as inputs, whereas the Spinning Consistency Index SCI and micronaire were the outputs to the neural network models. Bales were selected according...
NeuroXL Predictor is a powerful, easy-to-use and affordable solution for advanced estimation and forecasting. By harnessing the latest advances in artificial intelligence and neural network technology, it delivers accurate and fast predictions for your business, financial, or sports forecasting tasks. Designed as an add-on to Microsoft Excel, it is easy...
The use of Artificial Neural Networks ANNs within the NASA applications is expected to increase over the next few decades. Currently, there are over 20 NASA funded activities that use Neural Network NN technology. High criticality software applications of NNs will require a rigorous Verification and Validation (V&V) process. No...
This article describes a new methodology of using design of experiments as a precursor to identify the importance of some variables and, thus, reduce the data set needed for training a neural network. Based on the design-of-experiments results, a neural-network training set is generated with more variations for the most...
This white paper research is exploring intelligent drilling that can be applied to multiple applications. The paper reveals that the methodology uses a neural network to classify material lithology where the inputs to the neural network are sensed drill parameters such as thrust, torque, rotary speed and penetration rate, as...
An increasing number of organizations are involved in the development of strategic information systems for effective linkages with their suppliers, customers, and other channel partners involved in transportation, distribution, warehousing and maintenance activities. An efficient inter-organizational inventory management system based on data mining techniques is a significant step in this...
When assessing the likelihood of fraud in commercial banks, an auditor is faced with two related issues: determining significant red flags in the commercial banking industry, and combining red flags in a model Decision Aid based on weights Values of uncertainties assigned to them. Prior research largely ignores the first...
This paper views schizophrenia as producing a failure of attentional modulation that leads to a breakdown in the selective enhancement or inhibition of semantic/lexical representations whose biological substrata are widely distributed across left dominant temporal and frontal lobes. Supporting behavioral evidence includes word recall studies that have pointed to a...
Neural networks have found profound success in the area of pattern recognition. By repeatedly showing a neural network inputs classified into groups, the network can be trained to discern the criteria used to classify, and it can do so in a generalized manner allowing successful classification of new inputs not...
In this paper a proposal and test valuation methodology for improving the efficiency of contingent claims pricing using Artificial Neural Networks ANN. A contingent claim is by now a standard method for pricing under uncertainty nonlinear option embedded contracts, for both financial options standardized or customized and real investment opportunities....
Partly due to a growing interest in direct marketing, it has become an important application field for data mining. The availability of a large number of techniques for analyzing the data may look overwhelming and ultimately unnecessary at first. However, the amount of data used in direct marketing is tremendous....
The concept of consideration sets makes brand choice a two-step process. Households first construct a consideration set which not necessarily includes all available brands and conditional on this set they make a final choice. This paper puts forward a parametric econometric model for this two-step process, where consideration sets usually...
