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Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals
We propose a new, fast, yet reliable method for the construction of neural network (NN) based PIs for NN predictions. Expand
Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals
This paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). Expand
Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances
This paper evaluates the four leading techniques proposed in the literature for construction of prediction intervals (PIs) for neural network point forecasts, and their performance for generating high-quality PIs. Expand
A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings
Electrical load forecasting plays a vital role in order to achieve the concept of next generation power system such as smart grid, efficient energy management and better power system planning. As aExpand
Prediction Intervals for Short-Term Wind Farm Power Generation Forecasts
Quantification of uncertainties associated with wind power generation forecasts is essential for optimal management of wind farms and their successful integration into power systems. This paperExpand
Construction of Optimal Prediction Intervals for Load Forecasting Problems
Short-term load forecasting is fundamental for the reliable and efficient operation of power systems. Despite its importance, accurate prediction of loads is problematic and far remote. OftenExpand
An expert system for selecting wart treatment method
We propose a fuzzy logic rule-based system to predict the responses of two of the best methods (immunotherapy and cryotherapy) to the treatment. Expand
Prediction Interval Estimation of Electricity Prices Using PSO-Tuned Support Vector Machines
We propose a novel technique that generates high-quality PIs in a short time using a particle swarm optimization (PSO) technique. Expand
Prediction Interval Construction and Optimization for Adaptive Neurofuzzy Inference Systems
The performance of an adaptive neurofuzzy inference system (ANFIS) significantly drops when uncertainty exists in the data or system operation. Expand
Classification of healthcare data using genetic fuzzy logic system and wavelets
This paper proposes an integration of fuzzy standard additive model (SAM) with genetic algorithm (GA), called GSAM to deal with uncertainty and computational challenges. Expand