This paper aims to illustrate implementation of one such solution, wherein a predictive capacity model was build coupling the application, system usage data and business usage estimates to address the capacity
We structure the remaining paper by focusing first on the literature review of the core concept used in the conceptual framework followed by the hypothesis development section. Next, we presented a detailed methodology section covering the study context, survey instrument design, sampling, and data co...
Agouzoul A, Simeu E, Tabaa M (2022) Building energy consumption enhancement using a neural network based model predictive control synthesis in FPGA. In: 2022 International conference on microelectronics (ICM), December. IEEE, pp 262–265 Ahn KU, Park CS (2020) Application of deep q-networks...
By incorporating real-time data, the digital twin goes beyond a simple 3D model and allows for a thorough understanding of the performance of the asset over the course of its existence. This technology makes it easier to make knowledgeable decisions, perform predictive analysis, and come up with...
Additionally, the tests are performed in a deterministic setting since the BOPTEST framework does not yet provide the functionality to emulate uncertainties. Although RL-MPC is expected to excel in stochastic settings, this study shows that it can achieve similar performance levels to MPC in the ...
What started as a successful pilot was rapidly deployed to around 20 USG plants within a year. The true power of the predictive analytics and optimization system quickly became evident in the field, where the cost of raw materials and production styles vary by location. “SAS enabled us to an...
Predictive maintenance models can detect and anticipate faults by analyzing this data, minimizing energy waste and optimizing resource allocation [11]. Yet, identifying the most effective ML models for fault detection remains a challenge, as model performance can vary significantly based on the ...
This filtration process culminates in the generation of tailored recommendations. Below are some tools and Libraries/Algorithms that can be useful for data filtering Microsoft Excel/Google Sheets Pandas/NumPy Collaborative Filtering This systematic approach ensures that a recommendation engine optimally ...
buildings are cooling and heating technologies that must be considered to address energy consumption and corresponding CO2emission (Abergel & Delmastro, 2020). Currently, heating demand in industry and building is higher than cooling; however, cooling demand is increasing gradually, mainly due to air...
Conversely, eDEWS excelled in outbreak detection but was limited to that function. To enhance malaria surveillance and outbreak response, integrating both systems is recommended to combine their strengths. In Uganda, a national multi-hazard emergency preparedness and response plan was developed using ...