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The ALICE experiment at the LHC has studied inclusive J/ψ production at central and forward rapidities in pp collisions at √ s = 7 TeV. In this Letter, we report on the first results obtained detecting the J/ψ through the dilepton decay into e + e − and µ + µ − pairs in the rapidity ranges |y| < 0.9 and 2.5 < y < 4, respectively, and with acceptance down to zero p T . In the dielectron channel the analysis was carried out on a data sample corresponding to an integrated luminosity L int = 5.6 nb −1 and the number of signal events is N J/ψ = 352 ± 32 (stat.) ± 28 (syst.); the corresponding figures in the dimuon channel are L int = 15.6 nb −1 and N J/ψ = 1924 ± 77 (stat.) ± 144 (syst.). The measured production cross sections are σ J/ψ (|y| < 0.9) = 12.4 ± 1.1 (stat.) ± 1.8 (syst.) +1.8 −2.7 (syst.pol.) µb and σ J/ψ (2.5 < y < 4) = 6.31 ± 0.25 (stat.) ± 0.76 (syst.) +0.95 −1.96 (syst.pol.) µb. The differential cross sections, in transverse momentum and rapidity, of the J/ψ were also measured.

This paper presents the forecast of electricity consumption based on mathematical models by using the available historical consumption, with daily resolution, including upscaling, applying a hybrid model that incorporates multiple linear regression with artificial neural networks. Therefore, the hybrid model exploits both the unique features of the regression model and of the artificial neural network to determine different patterns. Thus, it is advantageous to model linear and nonlinear patterns separately using different models and then combine the forecasts to improve overall performance modelling and forecasting. The applied methodology is very reliable given that the forecast errors are close to zero, and the observed differences are justified essentially by temperature effect.