Improving the accuracy of wind power forecasting is an important measure to deal with uncertainty and volatility power. Wind speed direction are most factors affecting generation turbines. In this paper, we propose a method that combines sparrow search algorithm (SSA) deep extreme learning machine (DELM). Based on DELM model, length time series’ influence performance neural network validated th...

With the development of electric market, load forecasting has been increasingly pursued by many scholars. Because is affected factors, it characterized volatility and uncertainty, cannot be forecasted accurately only a single model. In research, short-term integrated model proposed to solve problem inaccurate The key point using forecast optimize decomposed sequence improve accuracy forecast. E...

Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting. It combines elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA aims at decomposing the original series into a sum of a small number of interpretable components such as a slowly varying trend, oscillatory components and a ‘...

Singular spectrum analysis (SSA) is a popular filtering and forecasting method that used in wide range of fields such as time series signal processing. A commonly approach to identify the meaningful components grouping step SSA utilization visual information eigentriples. Another supplementary employing an algorithm performs clustering based on dissimilarity matrix defined by weighted correlati...

When building geotechnical constructions like retaining walls and dams is of interest, one the most important factors to consider soil’s shear strength parameters. This study makes an effort propose a novel predictive model strength. The implements extreme gradient boosting (XGBoost) technique coupled with powerful optimization algorithm, salp swarm algorithm (SSA), predict various soils. To do...

Simulated annealing (SA) algorithm is a popular intelligent optimisation algorithm, but its efficiency is unsatisfactory. To improve its efficiency, this paper presents a swarm SA (SSA) algorithm by exploiting the learned knowledge from searching history. In SSA, a swarm of individuals run SA algorithm collaboratively. Inspired by ant colony optimisation (ACO) algorithm, SSA stores knowledge in...

In this paper, the data analysis and short term price forecasting in Iran electricity market as a market with pay-as-bid payment mechanism has been considered. The proposed method is a modified singular spectral analysis (SSA) method. SSA decomposes a time series into its principal components i.e. its trend and oscillation components, which are then used for time series forecasting effectively....