Accurate electric load forecasting is critical in guaranteeing the efficiency of the load
dispatch and supply by a power system, which prevents the wasting of electricity and …

Accurate electric load forecasting can provide critical support to makers of energy policy and
managers of power systems. The support vector regression (SVR) model can be hybridized …

Using the perspective of microfoundations, this article discusses the role that cooperation
and technological orientation play on innovativeness. We place special emphasis on the …

Corporate social responsibility (CSR) and circular economy (CE) have assumed
considerable importance in the efforts for sustainable development. However, some …

Singular value decomposition (SVD) is one of the most widely used algorithms for
dimensionality reduction and performing principal component analysis, which represents an …

The presence of outliers is very common in regression problems and the use of robust
regression methods is strongly recommended such that the bad fitted observations not affect …

In this paper, a new approach is presented to fit arobust fuzzy regression model based on
some fuzzy quantities. Inthis approach, we first introduce a new distance between two …

In real life, we usually encounter with interval-valued data when analyzing imprecise data or
massive data sets. In this paper, a regularized interval MM estimate (RIMME) for interval …

Interval-valued data has garnered attention across various applications, leading to
increased research into spatial interval-valued data models. The integration of uncertainty …

The least squares method is a frequently used technique in fuzzy regression analysis.
However, it is highly sensitive to outliers in the dataset. To address this challenge, we …