this research studies the application of hybrid algorithms for predicting the prices of crude oil. brent crude oil price data and hybrid intelligent algorithm (time delay neural network, probabilistic neural network, and fuzzy logic) were used to build intelligent decision support systems for predicting crude oil prices. the proposed model was able to predict future crude oil prices from august...

The nature is composed of infinite process, and each process is surely deterministic (out of mention for the micro process on the level of quantum physics, which is under the uncertainty principle of Heisenberg, 1927), but affected by uncountable number of factors. What we are trying to do with modeling is to find the most dominating factors on a process and to simplify the process with an unde...

Floods represent the most devastating natural hazards in the world, affecting more people and causing more property damage than any other natural phenomena. One of the important problems associated with flood monitoring is flood extent extraction from satellite imagery, since it is impractical to acquire the flood area through field observations. This paper presents a method to flood extent ext...

Streamflow forecasting has an important role in water resource management (e.g. flood control, drought management, reservoir design, etc.). In this paper, the application of Adaptive Neuro Fuzzy Inference System (ANFIS) is used for long-term streamflow forecasting (monthly, seasonal) and moreover, cross-validation method (K-fold) is investigated to evaluate test-training data in the model.Then,...

Existing flood forecasting models are highly data specific, and their operational performance depends upon the science used to build and operate these models as well as their ability to respond to dynamic and rapidly changing events. Soft computing is one of the latest approaches for the development of systems, which possess computational intelligence. It attempts to integrate several different...

electricity price predictions have become a major discussion on competitive market under deregulated power system. but, the exclusive characteristics of electricity price such as non-linearity, non-stationary and time-varying volatility structure present several challenges for this task. in this paper, a new forecast strategy based on the iterative neural network is proposed for day-ahead price...

Accurate streamflow predictions are crucial for mitigating flood damage and addressing operational flood scenarios. In recent years, sequential data assimilation methods have drawn attention due to their potential to handle explicitly the various sources of uncertainty in hydrologic models. In this study, we implement two ensemble-based sequential data assimilation methods for streamflow foreca...

“Hydromax” is the river flow forecasting system for the early warning of extreme hydrological events (floods as well as low waters) in the Meuse river basin and its tributaries. Hydromax provides in real-time short-term predictions of river flows based on past rainfall and river flow measurements, and long-term flood forecasting based on meteorological forecasts. It is now successfully in routi...