In this study, several data-driven techniques including system identification, time series, and adaptive neuro-fuzzy inference system (ANFIS) models were applied to predict groundwater level for different forecasting period. The results showed that ANFIS models out-perform both time series and...

Majuli was once the largest river islands and the cultural home of the Asomiya community. Today, repeated floods of the Brahmaputra have ensured that the community has lost home and hearth to erosion. This is the report on the first round of relief carried out in Majuli on 25th and 26th August...

There is a long established history of applying Artificial Neural Networks (ANNs) to financial data sets. In this paper, the authors demonstrate the use of this methodology to develop a financially viable, short-term trading system. When developing short-term systems, the authors typically site...

Alternate Models for Forecasting Hedge Fund ReturnsMichael HoldenFaculty Sponsor: Gordon Dash, Finance and Decision SciencesInvestors have always wanted to improve the efficiency of modeling realized volatility to maximize directional trading returns and substantially improve profitability. As...

Weibull distributions play an important role in reliability studies and have many applications in engineering. It normally appears in the statistical scripts as having two parameters, making it easy to estimate its parameters. However, once you go beyond the two parameter distribution, things...

We developed a real-time forecasting system, aiNet-GISPSRIL, for evaluating the spatiotemporal probability of occurrence of rainfall-triggered landslides. In this system, the aiNet (a kind of artificial neutral network based on a self-organizing system) and GIS are merged for integrating the...

For those working in the field of landslide prevention, the estimation of hazard levels and the consequent production of thematic maps are principal objectives. They are achieved through careful analytical studies of the characteristics of landslide prone areas, thus, providing useful...

This article presents a multidisciplinary approach to landslide susceptibility mapping by means of logistic regression, artificial neural network, and geographic information system (GIS) techniques. The methodology applied in ranking slope instability developed through statistical models...

Without a doubt, landslide is one of the most disastrous natural hazards and landslide susceptibility maps (LSMs) in regional scale are the useful guide to future development planning. Therefore, the importance of generating LSMs through different methods is popular in the international...

A wavelet network model is developed to predict the inflow of Three Gorges dam in Yangtze River, China. The model makes use of the multi-resolution analysis of wavelet analysis and the nonlinear capability of artificial neural network. The short and long term input runoff of Three Gorges dam,...