Sharif Digital Repository

Predicting groundwater level fluctuations is essential for effective water resource management and environmental preservation. This study examines and compares two modeling techniques, namely Wavelet Neural Networks (WNN) and Artificial Neural Networks (ANN), for predicting fluctuations in the aquifer levels in the Varamin plain. Traditional hydrological models often struggle to detect nonlinear relationships present in hydrological data, which may lead to inconsistencies in predictions. The research focuses on groundwater level fluctuations in the Varamin plain over a 30-year period, from October 1989 to September 2018. Statistical methods such as mean, median, and variance calculations are... 

Chlorophyll-a, as an important component in evaluating water resources, has a significant impact on the status of water resources. This component is dependent on various quality parameters, such as phosphorus concentration, nitrogen concentration, turbidity, suspended solid concentration, temperature, pH, and dissolved oxygen concentration in water. To evaluate the quality status of surface water, it is necessary to estimate the exact concentration of chlorophyll-a in different temporal and spatial ranges. The objective of this study is to simulate and predict the concentration of chlorophyll-a in different temporal and spatial ranges using a combined application of machine learning models,... 

In recent years, Machine Learning models have been developed in Signal Processing, Computer Vision and Neuroscience areas. There are two categories of Machine Learning models which are supervised and unsupervised learning models. Regression and classification problems are two popular problems examples of supervised learning models. From unsupervised learning problems, we can mention the clustering problem. Support Vector Regression (SVR), Decision Tree Regression and Bagging Ensemble Regression models are some important models of the regression problem. For classification problems, we can also mention to Support Vector Classification, Decision Tree Classification, and Bagging Ensemble... 

The water crisis in Iran is not only caused by climatic changes, in other words, human factors have also influenced the increase in water consumption. The intertwining of various economic, political, and social factors has caused a direct and dynamic impact on water resources. Undoubtedly, one of the most important processes in policy-making and in the continuation of planning the country's water resources is the approval of useful laws from the point of view of implementation, monitoring and finally having a positive impact on the subject under discussion. From this point of view, the main research question is the role of laws on the current state of water resources management. The first...