首页|Research Study Findings from Daffodil International University Update Understand ing of Machine Learning (Broadband high gain performance MIMO antenna array for 5 G mm-wave applicationsbased gain prediction using machine learning approach)
Research Study Findings from Daffodil International University Update Understand ing of Machine Learning (Broadband high gain performance MIMO antenna array for 5 G mm-wave applicationsbased gain prediction using machine learning approach)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on ar tificial intelligence. According to news originating from Dhaka, Bangladesh, by NewsRx editors, the research stated, "This paper presents the findings about imp lementing a machine learning (ML) technique to optimize the performance of 5 G m m wave applications utilizing multiple-input multiple-output (MIMO) antennas ope rating at the 28 GHz frequency band." Financial supporters for this research include King Saud University. Our news journalists obtained a quote from the research from Daffodil Internatio nal University: "This article examines various methodologies, including simulati on, measurement, and the utilization of an RLCequivalent circuit model, to eval uate the appropriateness of an antenna for its intended applications. In additio n to its compact dimensions, the proposed design exhibits a maximum gain of 10.3 4 dBi, superior isolation exceeding 26 dB, and a broad bandwidth of 16.56 % Centered at 28 GHz and spanning from 25.905 to 30.544 GHz. Another supervised re gression machine learning technique is utilized to predict the antenna's gain ac curately. Machine learning (ML) models can be assessed by several measures, such as the variance score, R square, mean square error (MSE), mean absolute error ( MAE), root mean square error (RMSE), and Mean Absolute Percentage Error (MAPE). Among the six machine learning models considered, it is seen that the Gaussian P rocess Regression (GPR) model exhibits the lowest error and achieves the highest level of accuracy in forecasting gain. The antenna under consideration has prom ising qualities for its intended use in high-band 5 G applications."
Daffodil International UniversityDhakaBangladeshAsiaBroadbandCyborgsElectronicsEmerging TechnologiesMach ine Learning
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