This paper proposed a price forecasting system for electric market participants to reduce the risk of price volatility. Combining the Radial Basis Function Network (RBFN) and Orthogonal Experimental Design (OED), an Enhanced Radial Basis Function Network (ERBFN) has been proposed for the solving process. The Locational Marginal Price (LMP), system load, transmission flow and temperature of the ...

Forests are essential natural resources that directly impact the ecosystem. However, rising frequency of forest fires due to and artificial climate change has become a critical issue. A revolutionary municipal application proposes deploying an intelligence-based fire warning system prevent major disasters. This work aims present overview vision-based methods for detecting categorizing fires. Th...

Although a large number of researches have been carried out into the analysis of nonlinear phenomena, little is reported about using reinforcement learning, which is widely used in artificial intelligent, intelligent control, and other fields. Here, we consider the problem of chaotic time series using a self-organized fuzzy neural network and reinforcement learning, in particular, a learning al...

Nowadays positioning system is no longer only for military purpose, while it has been widely applied to various livelihood purposes such as biological information, emergency rescue, public facilities and individual safety. While the most frequently used to identify the coordinates of users is global positioning system (GPS), however, it tends to be interfered by indoor buildings such that it ca...

The resolution of the environmental/economic dispatch (EED) problem using the different methods which are proposed in literature consumes an important computing time. Thus, the present paper deals with a technique based on two steps to solve the EED problem of electric energy power in real-time for forecast load curve. The first step uses the NSGAII approach (Non-dominated Sorting Genetic Algor...

This paper reports on an experimental comparison of two visual object recognition methods: a radial basis function network (RBFN) which is an artificial neural network, and a synthetic discriminant function network (SDFN) which classifies objects statistically via analysis with optimal spatial filters. Both methods require training with a set of images representative of the objects to be recogn...

Decision tree (DT) is one of the most popular classification algorithms in data mining and machine learning. However, the performance of DT based credit scoring model is often relatively poorer than other techniques. This is mainly due to two reasons: DT is easily affected by (1) the noise data and (2) the redundant attributes of data under the circumstance of credit scoring. In this study, we ...

Floods, one of the most significant natural hazards, often result in loss of life and property. Accurate hourly streamflow forecasting is always a key issue in hydrology for flood hazard mitigation. To improve the performance of hourly streamflow forecasting, a methodology concerning the development of neural network (NN) based models with an enforced learning strategy is proposed in this paper...

This paper proposes a hybrid algorithm to solve the optimal energy dispatch of an ice storage air-conditioning system. Based on a real air-conditioning system, the data, including the return temperature of chilled water, the supply temperature of chilled water, the return temperature of ice storage water, and the supply temperature of ice storage water, are measured. The least-squares regressio...