The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreThis work evaluates the influence of combining twisted fins in a triple-tube heat exchanger utilised for latent heat thermal energy storage (LHTES) in three-dimensional numerical simulation and comparing the outcome with the cases of the straight fins and no fins. The phase change material (PCM) is in the annulus between the inner and the outer tube, these tubes include a cold fluid that flows in the counter current path, to solidify the PCM and release the heat storage energy. The performance of the unit was assessed based on the liquid fraction and temperature profiles as well as solidification and the energy storage rate. This study aims to find suitable and efficient fins number and the optimum values of the Re and the inlet tem
... Show MoreThe dose rate for bremsstrahlung radiation from beta particles with energy (1.710) MeV and (2.28) MeV which comes from (32P and 90Y) beta source respectively have been calculated through six materials (polyethylene, wood, aluminum, iron, tungsten and lead) for first shielding material with thickness (x=1) mm which are putting between beta sources and second shield (polyethylene, aluminum and lead) with thickness (1, 2 &4) mm have been calculated. The distance between beta source and second shield is constant (D=1) cm. This dose rate was found by program called Rad Pro Calculator (version 3.26). The results of dose rate of beta particles were plotted as a function to the atomic number (Z) for first shield materials for each
... Show More