correlation matrix

Among atmospheric disasters, heat waves are the most important atmospheric disasters and a study of the annual mortality rate due to climate hazards shows that heat waves cause the highest mortality rate compared to other climatic events. In this study, the basis of calculations to identify Iranchr('39')s heat waves is the networked data of the maximum temperatures of synoptic and climatic stations in Iran, which in the period (1981-2011) for each day determines the climatic conditions of the country on 7187 cells. After programming in Mat lab software, the days whose standard deviation coefficient was higher than 2 and lasted at least 2 days separated from the Iranian maximum temperature matrix by this program, determined as Iranian heat waves. Then the four-day waves, which were more widespread and frequent, were selected and analyzed. Representative day method was used to study the synoptic heat waves. Saudi low pressure (SLP) and Pakistan low pressure (PLP) were the most important systems for the occurrence of this heat wave. At the time of occurrence of these waves, a strong stability prevails in Iran, low pressure on the ground and high pressure in the upper atmosphere.

Extended abstract Dust is one of the most important environmental events that can dramatically affect and destroy its living areas. The purpose of this study was to investigate the long-term trends in dust events and to investigate the effects of these events in the city of Ilam on the record of respiratory diseases. In this regard, data on recorded events of dusty days during the 1995-2015 statistical periods was taken for two synoptic stations in Ilam and Dehloran. The relationship between time series of dust events could be detected throughout the day as TDE (Total Dust Event), in which total dust storms (including local and overflow and sandstorms and light to medium dust) are used in this research. With the fitting of a linear model at a confidence level of 0.95 (P_value = 0.05), the process of this time series was analyzed. In order to reveal the relationship between the time series of the annual registration of pulmonary and respiratory diseases, which were obtained from male and female patients of Shahid Mostafa Khomeini Hospital in Ilam during the statistical period of 1380-1384, two methods of Pearson correlation of matrix at confidence level of 0.95 (P_value = 0.05) and linear model is used at confidence level. The results showed that the increase of dust records in Ilam and Dehloran stations was 0.8 and 0.96 records per year, respectively. Correlation matrix indicates that at the confidence level, a significant direct correlation was found between the annual number of patients with pulmonary and perfused patients registered in Shahid Mostafa Khomeini Hospital in Ilam and the occurrence of a recession. In spite of the fact that in the years when the number of records of the higher gathering was recorded at two stations in Ilam and Dehloran, a record of the respiratory examination was significantly higher. Also, models based on the relationship between the number of male patient admissions and the events recorded in the two waves of two synoptic stations in Ilam and Dehloran indicate that these two models, respectively, verified 0.79 and 0.69, respectively, of the variability of the time series of client hospital records. In the case of women with pulmonary and respiratory diseases, the model has been fitted, which according to the number of days with dust in Ilam and Dehloran stations showed that these models could define 0.70 and 0.83 of the number of female patients. The correlation matrix indicated that at the confidence level, a significant direct relationship was established between these two time series so that the number of annual records of patients with respiratory diseases recorded in Shaheed Mostafa Khomeini Hospital in Ilam during the years Which had a higher number of dusty days recorded at two stations in Ilam and Dehloran, was significantly higher. The correlation matrix indicated only the direction and severity of the relationship, so that linear regression models were used to quantify this association and to be aware of the susceptibility function of the records of patients with pulmonary and respiratory diseases. The proposed model can be meaningfully and cognitively able to model the association between dust events (as independent variables) and the records of patients with respiratory diseases (as a dependent variable). A model for recording the number of female patient records during the period 2000-2014 based on the number of dusts recorded at Ilam station has been able to justify 0.62 times of the time records of women referring women in Shaheed Mostafa Khomeini Hospital, while The number of recorded events of the Dehloran Synoptic Station, based on the fitted model, has been able to justify about 0.58 of these changes. The fitted models on the relationship between the number of records of hospital male patients and the recorded dust events of two synoptic stations in Ilam and Dehloran showed that these two models were 0.79 and 0.69, respectively, of the variability of the time series of the records of male patient clients To explain. For the total population of patients with pulmonary and respiratory diseases (without attention), the model was also fitted according to the number of days with dust in Ilam and Dehloran stations, which showed that these models also were 0.67 and 0.83 Describe the records of patients referring. Finally, comparing the results of this study with other researches, it was found that the results obtained in Ilam are in agreement with the results of other researchers in Kermanshah and Ahwaz.

Evaporation is one of the climatic variables that predict significant role in the planning of water. Due to the relatively high rainfall in areas of West Iran, awareness of the evaporation rate of water in these areas is essential for proper management.The factors influencing rate of evaporation, which are climatic signals according to their role in predicting enables evaporation. Evaporation prediction was performed using artificial neural network model based on climatic signals. the data of evaporation at three synoptic stations and the most important climate signals whit at least 20 years of monthly analysis using NeuroSolution software. The results show that the most Important signals affecting the evaporation areas include; Nina3, Nina1, Sw monsoon, Mei and Nina4.Comparison of observed data with a high correlation between the ANN output data shows. So that the correlation of the Kermanshah station is 71%, Hamedan 82% and Sanandaj 80%.The output data of the neural network and climatic signals, can accurately predict the top 97% of the areas evaporation.

As the urban development has overtaken the capacity and potentials of the governments and municipalities in extending the infrastructures and providing employment, informal settlements are quickly and irregularly increasing. Studies performed on the informal settlements in Sanandaj (Kurdistan province) suggest that the majority of immigrations to the suburban areas of Sanandaj are from rural areas and are resulted from economical and security concerns (during the imposed war of Iraq against Iran and insecurities within the province). Studies on comprehensive and detailed plans of Sanandaj show that no better position has been considered for the low-income urban classes. In other words, they are missed in the studies. Also the demands of these classes for housing and the way these demands are supposed to be fulfilled have not been studied in the urban development plans. Therefore, one of the reasons that drive these low-income classes to the suburban areas of the cities and their settlement outside the area is attributed to the lack of attention to the demand for housing of these classes in developing formal plans.
In addition to determining the most important structural problems in the informal settlements of Sanandaj, using correlation matrix, the rate of correlation between indices has been studied in this paper and the results suggest that the first important problem in suburban areas of Sanandaj is the usage of high amounts of low quality and inordinate materials in the construction of the buildings. The second important problem is low average area of residential parcels. Finally in this paper, the informal housing area of Sanandaj is assessed, using SWOT technique.