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Www cccp project net free download5/9/2023 We compared the performance of the widely-used feed-forward back-propagation artificial neural network (ANN) with random forest (RF), an ensemble-based method gaining popularity in prediction-for predicting the hourly HVAC energy consumption of a hotel in Madrid, Spain. Simplified and data-driven models are often the preferred option where pertinent information for detailed simulation are not available and where fast responses are required. The reported sensor has potential applications in various fields requiring CO, CO2 and CH4 detection such as in coal mines.Įnergy prediction models are used in buildings as a performance evaluation engine in advanced control and optimisation, and in making informed decisions by facility managers and utilities for enhanced energy efficiency. Based on an Allan deviation analysis, the 1σ detection limits under static operation are 2.96, 4.54 and 2.84 parts per million in volume (ppmv) for CO, CO2 and CH4, respectively and the 1σ detection limits under dynamic operations are 8.83, 8.69 and 10.29 ppmv for the three gas species, respectively. Effects of the motor rotating period on sensor performances were also investigated and a rotation speed of 0.4π rad/s was required to obtain a stable sensing performance, corresponding to a detection period of ~10 s to realize one round of detection. Detailed measurements under static detection mode (without rotation) and dynamic mode (with rotation) were performed to study the performance of the sensor system for the three gas species. A stepper motor-based rotating system and a single-reflection spherical optical mirror were designed and adopted to realize and enhance multi-gas detection. A multi-gas sensor system was developed that uses a single broadband light source and multiple carbon monoxide (CO), carbon dioxide (CO2) and methane (CH4) pyroelectric detectors by use of the time division multiplexing (TDM) technique.
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