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.
Abstract:
We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.
In this research, I estimate the reliability function of cluster function by using the seemingly unrelate
... Show MoreHuman beings are starting to benefit from the technology revolution that witness in our time. Where most researchers are trying to apply modern sciences in different areas of life to catch up on the benefits of these technologies. The field of artificial intelligence is one of the sciences that simulate the human mind, and its applications have invaded human life. The sports field is one of the areas that artificial intelligence has been introduced. In this paper, artificial intelligence technology Fast-DTW (Fast-Dynamic Time Warping) algorithm was used to assess the skill performance of some karate skills. The results were shown that the percentage of improvement in the skill performance of Mai Geri is 100%.
Abstract Background: Dne of the key component of nasal tipplasty is effecter control of naral tip projection. Several cartilage grafts have been decreased for this purpose each had its own advantage and disadvantage. Aim: To evaluate using of double teostrut graft for controlling of tip projection. Patients and Methods: A total number of 170 patients were subjected to primary and secondary rhino plaster between January 2020 to January 2023. Those patients had double Teostrut banner graft for support of their nasal tip and maintaining tip projection after operation. Results: The follow period was ranging between 6-12 months. The shape of the nose was evaluating by patents vernal analogues scale. The average score for patients satisfaction wa
... Show MoreThis investigation aimed to explain the mechanism of MFCA by applying this method on air-cooled engine factory which was suffering from high production cost. The results of this study revealed that MFCA is a useful tool to identify losses and inefficiencies of the production process. It is found that the factory is suffering from high losses due to material energy and system losses. In conclusion, it is calculated that system losses are the highest among all the losses due to inefficient use of available production capacity.
In this paper Heun method has been used to find numerical solution for first order nonlinear functional differential equation. Moreover, this method has been modified in order to treat system of nonlinear functional differential equations .two numerical examples are given for conciliated the results of this method.
In this paper, the topic of forecasting the changes in the value of Iraqi crude oil exports for the period from 2019 to 2025, using the Markov transitional series based on the data of the time series for the period from January 2011 to November 2018, is real data obtained from the published data of the Central Agency Of the Iraqi statistics and the Iraqi Ministry of Oil that the results reached indicate stability in the value of crude oil exports according to the data analyzed and listed in the annex to the research.
Keywords: Using Markov chains
In this work, the possibility of utilizing osmosis phenomenon to produce energy as a type of the renewable energy using Thin Film Composite Ultra Low Pressure membrane TFC-ULP was studied. Where by forward osmosis water passes through the membrane toward the concentrated brine solution, this will lead to raise the head of the high brine solution. This developed static head may be used to produce energy. The aim of the present work is to study the static head developed and the flux on the high brine water solution side when using forward and reverse osmosis membranes for an initial concentration range from 35-300 g/l for each type of membrane used at room temperature and pressure conditions, and finally calculating the maximum possible po
... Show MoreThis study delves into the design optimization of a hydropower harvesting system, exploring various parameters and their influence on system performance. By modifying the variables within the model to suit different flow conditions, a judiciously optimized design is attainable. Notably, the lift force generated is found to be intricately linked to the strategic interplay of the bluff body's location, cylinder dimensions, and flow velocity. The findings culminate in the establishment of empirical equations, one for lift force and another for displacement, based on the force equation. Many energy harvesting approaches hinge on the reciprocating motion inherent to the structural system. The methodology developed in this study emerges as a pot
... Show MoreRecently, wireless charging based RF harvesting has interfered our lives [1] significantly through the different applications including biomedical, military, IoT, RF energy harvesting, IT-care, and RFID technologies. Wirelessly powered low energy devices become significantly essential for a wide spectrum of sensing applications [1]. Such devices require for low energy resources from sunlight, mechanical vibration, thermal gradients, convection flows or other forms of harvestable energy [2]. One of the emerging power extraction resources based on passive devices is harvesting radio frequency (RF) signals powers [3]–[5]. Such applications need devices that can be organized in very large numbers, so, making separate node battery impractical.
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