flooding, which is an overflow of water, brings massive biological and economic problems all around the world and disrupts many people’s lives. based on several effective factors in flood occurrence as well as unknown relationships between parameters, researchers have used various methods to forecast flood over the past decade. an investigation of the conducted studies on flood forecasting reve...

A colleague once pondered, "If everyone has the algorithms, will they not get the same answers?" This question reflects an important observation and is one of the reasons for this conference-Blending Quantitative and Traditional Equity Analysis-at this time. Consider three advances in quantitative modeling that have emerged recently: nonlinear estimation, conditional forecasting, and improved h...

This important new text and reference for researchers and students in machine learning, game theory, statistics, and information theory offers the first comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. ...

High-quality products are considered as one of the most important practices for achieving success. However, it is really hard to predict and forecast the product quality due to some undetermined parameters. In order to forecast product quality from various aspects, we propose an integrated model of utilizing grey theory and neural network. In this paper, the grey forecasting model for product q...

The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Networks for financial forecasting applications. The theory of the SVM algorithm is based on statistical learning theory. Training of SVMs leads to a quadratic programming (QP) problem. Preliminary computational results f...