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Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent
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The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is suitable for multi-objective optimisation based on cooperative multi-agent systems (CMAS). The framework of DCLTML is used greedy iterative training to get an optimal set of weights and tabulated as a layer for each clustering structure. Such layers can deal with the challenges of large space and its massive data. Then the layer weights of each cluster are tuned by the Quasi-Newton (QN) algorithm to make the action sequence of CMAS optimal. Such a policy of CMAS effectively manipulates the inputs of the AHU, where the agents of the AHU activate the natural ventilation and set chillers into an idle state when the outdoor temperature crosses the recommended value. So, it is reasonable to assess the impact potential of thermal mass and hybrid ventilation strategy in reducing cooling energy; accordingly, the assigning results of the proposed DCLTML show that its main cooling coil saves >40% compared to the conventional benchmarks. Besides significant energy savings and improving environmental comfort, the DCLTML exhibits superior high-speed response and robustness performance and eliminates fatigue and wear due to shuttering valves. The results show that the DCLTML algorithm is a promising new approach for controlling HVAC systems. It is more robust to environmental variations than traditional controllers, and it can learn to control the HVAC system in a way that minimises energy consumption. The DCLTML algorithm is still under development, but it can potentially revolutionise how HVAC systems are controlled.

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Educational And Psychological Researches
The Teaching Practices of Faculty Members in Northern Border University According to the Brain-Based Learning Theory
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The present study aims to identify the most and the least common teaching practices among faculty members in Northern Border University according to brain-based learning theory, as well as to identify the effect of sex, qualifications, faculty type, and years of experiences in teaching practices. The study sample consisted of (199) participants divided into 100 males and 99 females. The study results revealed that the most teaching practice among the study sample was ‘I am trying to create an Environment of encouragement and support within the classroom which found to be (4.4623). As for the least teaching practice was ‘I use a natural musical sounds to create student's mood to learn’ found to be (2.2965). The study results also in

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Publication Date
Wed Jun 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Promising Gains of 5G Networks with Enhancing Energy Efficiency Using Improved Linear Precoding Schemes
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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Toxicity Reduction of Reactive Red Dye-238 Using Advanced Oxidation Process by Solar Energy
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Decolorization of red azo dye (Cibacron Red FN-R) from synthetic wastewater has been investigated as a function of solar advanced oxidation process. The photocatalytic activity using ZnO as a photocatalysis has been estimated. Different parameters affected the removal efficiency, including pH of the solution, initial dye concentration and H2O2 concentration were evaluated to find out the optimum value of these parameters. The results proved that the optimal pH value was 8 and the most efficient H2O2 concentration was 100mg/L. Toxicity reduction percent for effluent solution was also monitored to assess the degradation process. This treatment method was able to strongly reduce the color and toxicity of reactive red dye-238 to about (99 an

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Development of Intelligent Control Strategy for an Anesthesia System Based on Radial Basis Function Neural Network Like PID Controller
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Publication Date
Wed Aug 05 2020
Journal Name
Advances In Structural Engineering
Strength compensation of deep beams with large web openings using carbon fiber–reinforced polymer sheets
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This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while

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Publication Date
Wed Aug 05 2020
Journal Name
Advances In Civil Engineering
Strength compensation of deep beams with large web openings using carbon fiber–reinforced polymer sheets
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This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while

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Publication Date
Tue Jan 01 2019
Journal Name
Aip Conference Proceedings
Temperature dependence energy distribution function for proton-tritium fusion reaction
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The physical behavior for the energy distribution function (EDF) of the reactant particles depending upon the gases (fuel) temperature are completely described by a physical model covering the global formulas controlling the EDF profile. Results about the energy distribution for the reactant system indicate a standard EDF, in which it’s arrive a steady state form shape and intern lead to fix the optimum selected temperature.

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Publication Date
Wed Nov 06 2024
Journal Name
2024 17th International Conference On Development In Esystem Engineering (dese)
Improving Cardiovascular Prediction Performance Using Machine Learning Based Feature Selection
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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Tue Dec 28 2021
Journal Name
2021 2nd Information Technology To Enhance E-learning And Other Application (it-ela)
Pedestrian and Objects Detection by Using Learning Complexity-Aware Cascades
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