Summer monsoon rainfall contributes more than 75% of the annual rainfall in India. For the state of Maharashtra, India, this is more than 80% for almost all regions of the state. The high variability of rainfall during this period necessitates the classification of rainy and non-rainy days. While there are various approaches to rainfall classification, this paper proposes rainfall classification based on weather variables. This paper explores the use of support vector machine (SVM) and artificial neural network (ANN) algorithms for the binary classification of summer monsoon rainfall using common weather variables such as relative humidity, temperature, pressure. The daily data, for the summer monsoon months, for nineteen years, was collected for the Shivajinagar station of Pune in the state of Maharashtra, India. Classification accuracy of 82.1 and 82.8%, respectively, was achieved with SVM and ANN algorithms, for an imbalanced dataset. While performance parameters such as misclassification rate, F1 score indicate that better results were achieved with ANN, model parameter selection for SVM was less involved than ANN. Domain adaptation technique was used for rainfall classification at the other two stations of Maharashtra with the network trained for the Shivajinagar station. Satisfactory results for these two stations were obtained only after changing the training method for SVM and ANN.

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In this research article, a compact wideband stack patch antenna array integrated with compact stack electromagnetic band gap (EBG) structure for multiple input multiple output (MIMO) application is proposed. The wide resonance bandwidth is achieved at 2.45 GHz band by stack arrangement of compact meander line slot driven and parasitic patch elements. The isolation bandwidth is matched with resonance bandwidth with the design of a compact stack L slot EBG structure. The polarization diversity and three-layer EBG structure ensure an enhancement in isolation level. To validate the performance of the proposed stack antenna array, a prototype was fabricated and tested for different MIMO parameters. The measured result confirms the effectiveness of the proposed antenna array in a diverse MIMO environment.

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