首页|Reports Outline Machine Learning Study Results from Moulay Ismail University (Ma chine Learning-based Predicting of Pcmintegrated Building Thermal Performance: an Application Under Various Weather Conditions In Morocco)
Reports Outline Machine Learning Study Results from Moulay Ismail University (Ma chine Learning-based Predicting of Pcmintegrated Building Thermal Performance: an Application Under Various Weather Conditions In Morocco)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-A new study on Machine Learning is now available. According to news originatingfrom Meknes, Morocco, by NewsRx corres pondents, research stated, "As is now stands, the buildingsector is among the ‘ big three' significant energy consumer and greenhouse gas contributor in the wor ld.Consequently, there has been a growing movement towards the development and adoption of renewableenergy sources, energy efficient measures and energy manag ement strategies."Our news journalists obtained a quote from the research from Moulay Ismail Unive rsity, "Phase changematerials (PCMs) are considered as an alluring option for e nergy efficiency measures in building. In thispaper, a case study building, bas ed on typical residential construction in Morocco, was selected to assessthe po tential energy savings of adding PCM to the roof for twenty-four cities using th e dynamic simulationtool, TRNSYS. Thereafter, thirteen machine learning techniq ues, including ANN, DT, SVM, ELM, GB,RF, TB, GLRM, GPR, LR, GAM, KRRM and LRR w ere assessed for predicting the hourly heating, cooling,and total energy consum ptions. The models were trained and tested on a dataset that was gathered fromt he simulations in twenty-four locations in Morocco. The outdoor dry-bulb tempera ture, the relativehumidity, the wind velocity, the wind direction, and the tota l solar radiation were considered as the keyfeatures. The obtained results reve aled that using PCM, can effectively lower the total energy demandfor all the c ities under study, with exception for very cold climate given by Ifrane and Mide lt, where theannual total energy consumption shows an increasing trend."
MeknesMoroccoAfricaCyborgsEmergi ng TechnologiesMachine LearningMoulay Ismail University
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