A hybrid robust system considering outliers for electric load series forecasting

Design of an anti-lock regenerative braking system for a series hybrid electric vehicle

In this paper, an adaptive rule based controller for an anti-lock regenerative braking system (ARBS) of a series hybrid electric bus (SHEB) has been proposed. The proposed controller integrates the regenerative braking and wheel anti-lock functions by controlling the electric motor of the hybrid vehicle, without using any conventional mechanical anti-lock braking system. The performance of the ...

Building a Fuzzy Expert System for Electric Load Forecasting Using a Hybrid Neural Network

This paper presents the development of a hybrid neural network to model a fuzzy expert system for time series forecasting of electricc load. The hybrid neural network is trained to develop fuzzy logic rules andjind optimal inputloutput membership values of load and weather parameters. A hybrid learning algorithm consisting of unsupervised and supervised learning phases is used for training the ...

Fuzzy Load Forecasting of Electric Power System

In order to efficiently improve the prediction accuracy, two load forecasting model based on fuzzy theory are presented, which are fuzzy clustering model and improved fuzzy regression analysis model .The method of fuzzy clustering is used to divide the area by the similar feature of load increasing. The new division is promising to improve the result of evident degree of clustering index to pow...

Hybrid Swarm System for Time Series Forecasting

In this paper, a hybrid swarm system is presented for time series forecasting. It consists of an intelligent hybrid model composed of an Arti cial Neural Network (ANN) and a Particle Swarm Optimizer (PSO), which search the relevant time lags for a correct characterization of the time series, as well as the number of processing units in the hidden layer, the training algorithm and the modeling o...

A Hybrid Intelligent System For Forecasting Gasoline Price