Neural Network Estimation of Tourism Climatic Index (TCI) Based on Temperature-Humidity Index (THI)-Jordan Region Using Sensed Datasets

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Jordan which is located in the heart of the world contains hundreds of historical and archaeological locations that have a supreme potential in enticing visitors. The impact of clime is important on many aspects of life such as the development of tourism and human health, tourists always wanted to choose the most convenient time and place that have appropriate weather circumstances. The goal of this study is to specify the preferable months (time) for tourism in Jordan regions. Neural network has been utilized to analyze several parameters of meteorologist (raining, temperature, speed of wind, moisture, sun radiation) by analyzing and specify tourism climatic index (TCI) and equiponderate it with THI index. The outcomes of this study shows that the finest time of the year to entice tourists is “ April” which is categorized as to be “extraordinary” for visitors. TCI outcomes indicates that conditions are not convenient for tourism from July to August because of high temperature.

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