Operational meteorology involves the application of accumulated human expertise. When developing intelligent systems for operational meteorologists, three aspects of forecasting should be considered, namely: forecasting relies on a variety of techniques; experts convey their knowledge with fuzzy terms; and data are often imprecise. No single artificial intelligence (AI) technique is best for al...

The Barato River joins the Ishikari River near the river mouth. That river basin is sometimes in danger of flood because it is low, flat and tidal area around the tributaries influenced by the backwater of the Ishikari River. Therefore the gate is provided at the confluence of Ishikari River to avoid counter flow. Flood forecasting is necessary to determine the gate operation and disaster preve...

The use of intelligent systems for stock market predictions has been widely established. This paper deals with the application of hybridized soft computing techniques for automated stock market forecasting and trend analysis. We make use of a neural network for one day ahead stock forecasting and a neuro-fuzzy system for analyzing the trend of the predicted stock values. To demonstrate the prop...

Accurate and timely flood forecasts are essential for effective management of flood disasters, which has become increasingly frequent over the last decade. Obtaining such forecasts requires high resolution integrated weather and flood models with computational costs optimized to provide sufficient lead time. Existing overland flood modeling software packages do not readily scale to topography g...

The pollution caused by particulate matter (PM) concentration has a negative impact on population health, due to its relationship with several diseases. In this sense, several intelligent systems have been proposed for forecasting the PM concentration. Although it is known in the literature that PM concentration time series behave like random walk, to the authors’ knowledge there is no intellig...

The prognostic system plays a crucial role in estimating the remaining useful life of machine components and forecasting of the future states of machines. The techniques related to prognostics consist of statistical-based, model-based, and data driven or intelligence-based. Among these, artificial intelligence is commonly used due to its flexibility in generating appropriate models for the fore...

3 Introduction Introduction This paper presents a hybrid intelligent system for This paper presents a hybrid intelligent system for electrical load forecast, named by PREVER. electrical load forecast, named by PREVER. Artificial Neural Networks (ANN) were combined with Artificial Neural Networks (ANN) were combined with Heuristic Rules to create the system. Heuristic Rules to create the system....

This paper deals with flood routing in rivers using neural networks. The unsteady river flow may be formulated in terms of two one-dimensional partial differential equations. These are the Saint Venant flow continuity and dynamic equations. Several methods of solution of these equations are known. These methods are based upon characteristics of equations, finite difference, finite element and f...

A model for real-time flood forecasting in river systems with large drainage areas has been developed. Flow variations between upstream and downstream stations are interlinked and are typically governed by reach properties. Unique paired variations establish useful flow correspondence resulting in inflow and outflow forecasting models for a reach. The proposed model can generate forecasts with ...