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Artificial Intelligence Based Flood Forecasting for River Hunza at Danyor Station in Pakistan

Yaseen Muhammad Waseem, Awais Muhammad, Riaz Khuram, Rasheed Muhammad Babar, Waqar Muhammad, Rasheed Sajid

Archives of Hydro-Engineering and Environmental Mechanics

2022

Vol. 69, nr 1

59--77

Floods can cause significant problems for humans and can damage the economy. Implementing a reliable flood monitoring warning system in risk areas can help to reduce the negative impacts of these natural disasters. Artificial intelligence algorithms and statistical approaches are employed by researchers to enhance flood forecasting. In this study, a dataset was created using unique features measured by sensors along the Hunza River in Pakistan over the past 31 years. The dataset was used for classification and regression problems. Two types of machine learning algorithms were tested for classification: classical algorithms (Random Forest, RF and Support Vector Classifier, SVC) and deep learning algorithms (Multi-Layer Perceptron, MLP). For the regression problem, the result of MLP and Support Vector Regression (SVR) algorithms were compared based on their mean square, root mean square and mean absolute errors. The results obtained show that the accuracy of the RF classifier is 0.99, while the accuracies of the SVC and MLP methods are 0.98; moreover, in the case of flood prediction, the SVR algorithm outperforms the MLP approach.

Numerical Investigation of the Air Gap Distribution of Jackets with Different Fits and its Influence on Human Temperature

Awais Muhammad, Krzywinski Sybille, Kyosev Yordan

Fibres & Textiles in Eastern Europe

2021

Vol. 29, no. 6 (150)

77--86

The air gaps underneath clothing have a great influence on the thermal regulation of the human body. The distribution of the air gaps depends on the shape of the human body as well as on clothing style, fit, and deformation properties. This paper reports on the influence of clothing fit on thermophysiological parameters of the human body through thermal simulation. Four different fits of jacket and a test person were considered for the investigation and for simulation purposes. The results of the simulation concluded that different thermal regulations of the human body were exhibited for different fits of the jacket, which is due to distinct air gaps between the human body and clothing for each fit of the jacket. This research work presents a fast method to predict the influence of clothing fit on thermal comfort, which is usually studied by a time-consuming, laborious method – the wear trial.