Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction information were collected for a specific period and put into a specific data set. That data was used to find the value of energy consumption in the building using artificial intelligence and data analysis. A Python library called Scikit-learn is used to implement machine learning algorithms. In particular, the Multi-layer Perceptron regressor (MLPRegressor) algorithm was used to predict the consumption. The importance of this work lies in predicting the amount of energy consumed. The outcomes of this work can be used to predict the energy consumed by any building before it is built. The used methodology shows the ability to predict energy performance in educational buildings using previous results and train the model on them, and prediction accuracy depends on the amount of data available for the training in artificial intelligence (AI) steps to give the highest accuracy. The prediction was checked using root-mean-square error (RMSE) and coefficient of determination (R²) and we arrived at 0.16 and 0.97 for RMSE and R², respectively.
As the demands of sixth-generation (6G) networks escalate towards achieving high speeds and improved energy efficiency, there is an increasing need for intelligent and real-time adaptive solutions within the physical processing layer. This study proposes an innovative engineering framework based on an encapsulated architecture utilising FBGA (micro-distributed spherical array) technology, integrated with an internal artificial intelligence module, to achieve adaptive beamforming with high efficiency in dense wireless environments. The primary objective of this research is to develop an intelligent communication architecture that determines the optimal transmission angles and regulates power consumption in real-time by integrating ar
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The Combined Economic Emission Dispatch (CEED) problem is crucial for optimizing power system operation by minimizing costs and emissions while ensuring grid stability and meeting demand. This paper addresses the complex, nonlinear, and nonconvex nature of CEED, arising from factors like valve-point effects and transmission losses, which necessitates efficient metaheuristic algorithms. We introduce an Improved Zebra Optimization Algorithm (IMZOA), an enhanced bio-inspired technique integrating advanced adaptive foraging and dynamic defense mechanisms, along with a cubic function for CEED modeling, to improve search efficiency and convergence. IMZOA demonstrates significant numerical improvements, achieving up to a 0.80 % cost reduction for
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Determination of the proportion of selected metal elements (Fe, Mn, Co, Cu, Cr, Ni, Mo, Pb, Cd ) using a flame absorption spectroscopy device and the spectroscopy of Graphite furnace, and Phenols so as Free Radical (NO3-, NO2-) using ultraviolet spectroscopy device in the industrial wastewater of Al-Dura (A) and AlNajaf (B) refinery before and after entering the treatment units, taking into consideration the sampling time Varying (more than separated) and setting the temperature during the drawing of the model and conducting a statistical study of the results reached
This studies p- CuO / n - Si hete-rojunction was deposited by high vacuum thermal evaporation of Copper subjected to thermal oxidation at 300 oC on silicon. Surface morphology properties of The optical properties concerning the transmission spectra were studies for prepared thin films. this structure have been studied. XRD anaylsis discover that the peak at (𝟏𝟏𝟏-) and (111) plane are take over for the crystal quality of the CuO films. The band gap of CuO films is found to be 1.54 eV. The average grain size of is measured from AFM analysis is around 14.70 nm. The responsivity photodetector after deposited CuO appear increasing in response
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The systems cooling hybrid solar uses solar collector to convert solar energy into the source of heat for roasting Refrigerant outside of the compressor and this process helps in the transformation of Refrigerant from the gas to a liquid state in two-thirds the top of the condenser instead of two-thirds the bottom of the condenser as in Conventional cooling systems and this in turn reduces the energy necessary to lead the process of cooling. The system cooling hybrid use with a capacity of 1 ton and Refrigerant type R22 and the value of current drawn by the system limits (3.9-4.2A), the same value of electric current calculated by the system are Conventional within this atmosphere of Iraq, and after taking different readings
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Thin film solar cells are preferable to the researchers and in applications due to the minimum material usage and to the rising of their efficiencies. In particular, thin film solar cells, which are designed based one transition metal chalcogenide materials, paly an essential role in solar energy conversion market. In this paper, transition metals with chalcogenide Nickel selenide termed as (NiSe2/Si) are synthesized. To this end, polycrystalline NiSe2 thin films are deposited through the use of vacuum evaporation technique under vacuum of 2.1x10-5 mbar, which are supplied to different annealing temperatures. The results show that under an annealed temperature of 525 K,
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Solar energy has significant advantages compared to conventional sources such as coal and natural gas, including no emissions, no need for fuel, and the potential for installation in a wide range of locations with access to sunlight. In this investigation, heterocyclic derivatives were synthesized from several porphyrin derivatives (4,4',4",4"'-(porphyrin-5,10,15,20-tetrayl) tetra benzoic acid) compound (3), obtained by reaction Pyrrole with 4-formyl benzoic acid. Subsequently, porphyrin derivative-component amides 5a, 5b, and 5c were produced by reacting compound (3) with amine derivatives at a 1:4 molar ratio. These derivatives exhibited varying sensitivities for utilization in solar cells, with compound 5a displaying the highest power
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Partial shading is one of the problems that affects the power production and the efficiency of photovoltaic module. A series of experimental work have been done of partial shading of monocrystalline PV module; 50W, Isc: 3.1A, Voc: 22V with 36 cells in series is achieved. Non-linear power output responses of the module are observed by applying various cases of partial shading (vertical and horizontal shading of solar cells in the module). Shading a single cell (corner cell) has the greatest impact on output energy. Horizontal shading or vertical shading reduced the power from 41W to 18W at constant solar radiation 1000W/m2 and steady state condition. Vertical blocking a column
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