Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting

Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting

Hybridizing chaotic evolutionary algorithms with support vector regression (SVR) to improve forecasting accuracy is a hot topic in electricity load forecasting. Trapping at local optima and premature convergence are critical shortcomings of the tabu search (TS) algorithm. This paper investigates potential improvements of the TS algorithm by applying quantum computing mechanics to enhance the se...

Electricity Load Forecasting Using Support Vector Regression with Memetic Algorithms

Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR) has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly alg...

Tehran Stock Price Modeling and Forecasting Using Support Vector Regression (SVR) and Its Comparison with the Classic Model ARIMA

APPLICATION OF THE HYBRID HARMONY SEARCH WITH SUPPORT VECTOR MACHINE FOR IDENTIFICATION AND CALSSIFICATION OF DAMAGED ZONE AROUND UNDERGROUND SPACES

An excavation damage zone (EDZ) can be defined as a rock zone where the rock properties and conditions have been changed due to the processes related to an excavation. This zone affects the behavior of rock mass surrounding the construction that reduces the stability and safety factor and increase probability of failure of the structure. This paper presents an approach to build a model for the ...

Applications of the Chaotic Quantum Genetic Algorithm with Support Vector Regression in Load Forecasting

Accurate electricity forecasting is still the critical issue in many energy management fields. The applications of hybrid novel algorithms with support vector regression (SVR) models to overcome the premature convergence problem and improve forecasting accuracy levels also deserve to be widely explored. This paper applies chaotic function and quantum computing concepts to address the embedded d...