Modelling, analysis and forecasting of climate elements for prevention and management of environmental climate hazards in northern Iran
Keywords:
Natural hazards, Extreme's temperature, Climate change, ANFIS, Northern IranAbstract
Considering the importance of minimum and maximum temperatures in the agricultural and gardening
sector, which each year causes significant losses in this sector. In order to avoid hazards in this section,
detailed research has to be done and then filed a file with management and planning. The purpose of the
present study and forecast the hazardous effects of thirty days extremes temperature on gardening and
agronomy crops in the north bar of Iran. For this purpose, the first stage data were obtained for the whole
station temperature over a period of 30 years (1989-2018). Then, using ANFIS (Adaptive-Network-based
Fuzzy Inference Systems) adaptive neural network model, the data were analyzed for prediction in the next 6
years. Then, to measure the land suitability of Iran's northern strip for cultivating based on the predicted data,
two models including Vikor (Vlse Kriterijumsk Optimizacija Kompromisno Resenje) and Topsis (Technique
for Order Preference by Similarity to Ideal Solution) were used. Both the Topsis and Vikor multivariate
decision making models combined the minimum temperature of the stations well, but did not reflect well at
the maximum temperature in the worst-priority stations. According to the findings of the study, with respect
to the friction extremes modeling, the maximum temperature showed the lowest defect compared to the
minimum temperature. In Golestan province, the maximum temperature peaks and at least both are in weak
increment, but in Gilan province, the maximum temperature peaks and at least both the maximum and
maximum temperatures are higher. Mazandaran province showed maximum temperature and minimum
temperature in both incremental and minimum temperature conditions.
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