Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligenc e is the subject of a new report. According to news reporting out of Wroclaw, Po land, by NewsRx editors, research stated, “This study explores the capability of machine learning techniques (MLTs) in predicting IAQ in apartments. Sensor data from kitchen air monitoring were used to determine the conditions in the living room.” Our news reporters obtained a quote from the research from Wroclaw University of Science and Technology: “The analysis was based on several air parameters-tempe rature, relative humidity, CO2 concentration, and TVOC-recorded in five apartmen ts. Multiple input-multiple output prediction models were built. Linear (multipl e linear regression and multilayer perceptron (MLP)) and nonlinear (decision tre es, random forest, k-nearest neighbors, and MLP) methods were investigated. Five -fold cross-validation was applied, where four apartments provided data for mode l training and the remaining one was the source of the test data. The models wer e compared using performance metrics (R2, MAPE, and RMSE). The naive approach wa s used as the benchmark. This study showed that linear MLTs performed best. In t his case, the coefficients of determination were highest: R2 = 0.94 (T), R2 = 0. 94 (RH), R2 = 0.63 (CO2), R2 = 0.84 (TVOC, based on the SGP30 sensor), and R2 = 0.92 (TVOC, based on the SGP30 sensor). The prediction of distinct indoor air pa rameters was not equally effective. Based on the lowest percentage error, best p redictions were attained for indoor air temperature (MAPE = 1.57%), relative humidity (MAPE = 2.97%RH), and TVOC content (MAPE = 0.41% ).”
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