A Cohesion-Based Heuristic Feature Selection for Short-Term Traffic Forecasting

pattern-based short-term traffic forecasting for urban heterogeneous conditions

short-term traffic flow forecasting plays a significant role in the intelligent transportation systems (its), especially for the traffic signal control and the transportation planning research. two mainly problems restrict the forecasting of urban freeway traffic parameters. one is the freeway traffic changes non-regularly under the heterogeneous traffic conditions, and the other is the success...

Hybrid filter-wrapper feature selection for short-term load forecasting

13 Selection of input features plays an important role in developing models for short14 term load forecasting (STLF). Previous studies along this line of research have focused 15 pre-dominantly on filter and wrapper methods. Given the potential value of a hybrid 16 selection scheme that includes both filter and wrapper methods in constructing an 17 appropriate pool of features, coupled with the...

A Permutation Importance-Based Feature Selection Method for Short-Term Electricity Load Forecasting Using Random Forest

The prediction accuracy of short-term load forecast (STLF) depends on prediction model choice and feature selection result. In this paper, a novel random forest (RF)-based feature selection method for STLF is proposed. First, 243 related features were extracted from historical load data and the time information of prediction points to form the original feature set. Subsequently, the original fe...

A data-driven multi-model methodology with deep feature selection for short-term wind forecasting

Type-2 fuzzy logic approach for short-term traffic forecasting

The performance of many components in intelligent transportation systems depends heavily on the quality of short-term traffic forecasts. We propose a new method for forecasting traffic based on type-2 fuzzy logic. Type-2 fuzzy logic is powerful in handling uncertainties, including uncertainties in measurements and data used to calibrate the parameters. In our formulation, the value of a members...