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Design of a Hybrid AI-Driven Engineering Model for Energy-Efficient and Sustainable Educational Systems
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A substantial percentage of the world’s energy consumption (almost 40%) and carbon dioxide (CO2) emissions (around 37%) come from the construction industry, especially schools. This work presents a new hybrid artificial intelligence (AI) engineering model that aims to maximize energy performance on campuses in a holistic way. Modules for data-driven forecasting, metaheuristic optimization, and real-time adaptive control are all part of the concept. A thorough energy simulation of a university campus building is used in conjunction with the AI model to assess its performance through a co-simulation framework. Findings show that yearly peak electricity demand may be reduced by 18.7% and total site energy consumption by 22.4% when compared to a baseline building management system, all while keeping indoor thermal comfort levels high. According to the study, one effective way to make school buildings smart, eco-friendly, and energy efficient is to use a hybrid AI-driven method.

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Publication Date
Sun Jan 01 2023
Journal Name
Ssrn Electronic Journal
Sustainable ENERGY by using AI
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As we live in the era of the fourth technological revolution, it has become necessary to use artificial intelligence to generate electric power through sustainable solar energy, especially in Iraq and what it has gone through in terms of crises and what it suffers from a severe shortage of electric power because of the wars and calamities it went through. During that period of time, its impact is still evident in all aspects of daily life experienced by Iraqis because of the remnants of wars, siege, terrorism, wrong policies ruling before and later, regional interventions and their consequences, such as the destruction of electric power stations and the population increase, which must be followed by an increase in electric power stations,

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Publication Date
Sun Feb 01 2026
Journal Name
Civil Engineering Journal
AI-Driven Shear Capacity Model of Steel Studs in Composite Structural Systems
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In composite steel-concrete structures, shear connectors in the form of headed steel studs are commonly utilized to transfer longitudinal shear force developed at the interface between the two materials. To overcome the shortcomings of design codes, which frequently understate shear capacity and fail to take advantage of sophisticated computational methods, this paper presents an optimization attempt to estimate the shear strength of headed steel studs utilizing the Grey Wolf Optimizer (GWO) technique using MATLAB software. Data from 234 experimental tests are employed to identify and highlight key input parameters influencing the shear strength of headed steel studs. These key parameters include concrete compressive strength (f’c

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Publication Date
Thu Jan 01 2026
Journal Name
Bioresource Technology
Hybrid Sono-Electro-Fenton (SEF) process driven by photovoltaic (PV) energy for sustainable hospital effluent treatment
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Publication Date
Sat Aug 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Developing Systems Engineering for Sustainable Infrastructure Projects
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Abstract<p>Globally, Sustainability is very quickly becoming a fundamental requirement of the construction industry as it delivers its projects; whether buildings or infrastructures. Throughout more than two decades, many modeling schemes, evaluation tools, and rating systems have been introduced en route to realizing sustainable construction. Many of these, however, lack consensus on evaluation criteria, a robust scientific model that captures the logic behind their sustainability performance evaluation, and therefore experience discrepancies between rated results and actual performance. Moreover, very few of the evaluation tools available satisfactorily address infrastructure projects. The res</p> ... Show More
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Publication Date
Mon Feb 16 2026
Journal Name
Agribusiness
Economic Analysis of AI‐Driven Resource Efficiency in Sustainable Agriculture in Iraq
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Abstract<p> Water scarcity, rising energy costs, and declining irrigation efficiency are significant barriers to wheat production in Iraq. This study evaluates the economic, environmental, and sustainability impacts of integrating artificial intelligence (AI) into irrigation management under semiarid conditions. Field experiments conducted at the Al‐Ra'id Research Station in Baghdad during the 2025 season compared conventional diesel‐based irrigation with AI‐assisted irrigation that used soil moisture sensors, Internet of Things (IoT) controllers, and predictive weather algorithms. The analysis employed Cobb–Douglas production modeling, cost–benefit analysis, net</p> ... Show More
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Publication Date
Sat Oct 18 2025
Journal Name
Pattern Recognition And Artificial Intelligence
Utilizing Energy-Efficient Deep Learning Technique for Age Estimation Through a Hybrid Methodology
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This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

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Publication Date
Mon Jul 01 2019
Journal Name
International Journal Of Heat And Mass Transfer
Hybrid heat transfer enhancement for latent-heat thermal energy storage systems: A review
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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials &amp; Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Energy Savings in Thermal Insulations for Sustainable Buildings
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Energy use is second to staffing in building operating costs. Sustainable technology in the energy sector is based on utilizing renewable sources of energy such as solar, wind, glazing systems, insulation. Other areas of focus include heating, ventilation and air conditioning; novel materials and construction methods; improved sensors and monitoring systems; and advanced simulation tools that can help building designers make more energy efficient choices. The objective of this research is studying the effect of insulations on energy consumption of buildings in Iraq and identifying the amount of energy savings from application th

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