Financial applications of artificial neural networksM QiCiteSeerX - Scientific documents that cite the following paper: Financial applications of artificial neural networksdoi:10.1016/S0169-7161(96)14020-7Min QiHandbook of StatisticsM. Qi, "Financial applications of artificial neural networks", in ...
Applications of Neural Network Radial Basis Function in Economics and Financial Time SeriesRadial Basis FunctionNeural NetworksTime-SeriesForecastingStock ReturnsMATLABError Backpropagation AlgorithmIn this paper we present the Radial Basis Neural Network Function. We examine some simple numerical examples of ...
Sentiment in annual reports is recognized as being an important determinant of future financial performance. The aim of this study is to examine the effect... P Hájek,V Olej - International Conference on Engineering Applications of Neural Networks 被引量: 32发表: 2013年 Modeling credit scoring ...
Financial Applications of Learning from Hints 来自 ResearchGate 喜欢 0 阅读量: 37 作者: YS Abu-Mostafa 摘要: The basic paradigm for learning in neural networks is 'learning from examples' where a training set of input-output examples is used to teach the network the target function. Learning ...
Through a structured review of over 100 studies, this review paper contributes to the understanding of GNN applications in financial fraud detection, offering insights into their adaptability and potential integration strategies.This is a preview of subscription content, log in via an institution to ...
however,theplayfieldiswideopen,alotofresearchopportunitiesstillexist.Inthispaper, wetriedtoprovideastate-of-the-artsnapshotofthedevelopedDLmodelsforfinancial applications,asoftoday.Wenotonlycategorizedtheworksaccordingtotheirintended subfieldinfinancebutalsoanalyzedthembasedontheirDLmodels.Inaddition,weals...
Discover how AI in financial compliance is transforming finance businesses. This insight explores its diverse applications, benefits, solutions, future trends and more.
Financial Applications of Self-Organizing Maps Applications of neural networks to finance and investments can be found in several books and articles. The great majority of these applications use supervised neural network models for forecasting market trends, creating trading models, ... GJ Deboeck - ...
This thesis explores the utility of computational intelligent techniques and aims to contribute to the growing literature of hybrid neural networks and genetic programming applications in financial forecasting. The theoretical background and the description of the forecasting techniques are given in the firs...
Graph neural networks build on the concept of representing local structural and feature context natively within the model. Information from both edge and node features is propagated through aggregation and message passing to neighboring nodes.