to investigate of change in waves height under the influence of climate change using artificial neural network and wavelet

prediction of the waves’ specifications that is one of the key factors effective on transformation ofcoasts, production of renewable energies and design of marine structures, has always been importante.height of the waves is one of the most important and effective parameters of the wave. differentfactors are effective in variation of the waves’ height. in this research, variation in waves height underchange of universal climate and heating – that as one of the consequences of collection of greenhousegases,isconsideredas one of the most important environmental challenges in the world – has beenstudied. the effect of weather changes in variation of waves height using the ecological data gainedfrom cgcm2 model that is one of the types of gcm models, was investigated under two scripts: a2and b2. in order to predict the waves height using the step by step regression method out of weathervariants stimulated in cgcm2 ecological model, those sets of variants that had the most correlationwith variation of waves height, have been selected. two ann and dwnn models were made in orderto study the relationship between the variants of climate and waves height, and dwnn model that is acombination of ann model and wavelet theory, showed better and more accurate results. the resultsfor years 2089 to 2100 express an increase from 10 to 46 cm at minimum of daily average of wavesheight and also increase from 10 to 36 cm at maximum of daily average of wave, gained in the regionof chabahar. with consideration to noticeable increase of average of waves height, this subject mustbe considered in different affairs such as management of coastal regions.