In this study, autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models were applied to predict the monthly flow time series of two stations, named Begova Chemcermo, for Khabour River. The analysis was performed using several criteria tests. autocorrelation function (ACF) partial (PACF) check accuracy ARIMA model. Akaike (AIC) Bayesian (BIC) equations determin...

Are couples who have been together longer more likely to stick together in the face of adversity? This paper uses monthly data from the Survey of Income and Program Participation to investigate the impact on relationship duration of labor market shocks such as layoff, discharge for cause, and disability. Using a Cox proportional hazard model, I show that generally these labor market shocks sign...

This paper analyzes a monthly global gridded sea-surface wind dataset from Jan 1991 to Dec 2020, sourced the International Comprehensive Ocean-Atmosphere Data Set (ICOADS). The goal is construct schematic maps depicting average distributions of speeds and directions in East Vietnam Sea. These provide visual representation monsoon patterns at different points areas region. statistical analytical...

Axios River is one of the most important transboundary rivers between the Greek and the neighbour country FYROM in the Balkan area. In this paper, Artificial Neural Networks (ANNs) were used to derive and to develop models for prediction the monthly values of some water quality parameters of the river Axios at a station located at Axioupolis site of Greece near the Greece FYROM borders by using...

Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing w...