This research attend about Alienation form for ornament’s clouds in Quran, which includes four parts, the first part talks about the research problem, the researcher identified by following question :( what’s the Alienation form for ornament’s clouds in Quran?). And then the research importance. The research goal talks about Alienation form for ornament’s clouds in Quran. And also research borders, likes means objectives borders, places borders, As well as Terms Definitions, in second part talks about Theoretical framework and previous studies, includes two parts, the first one study Alienation form, meaning and understandable, the second one talks about Alienation form in Islamic arts, As well as the researcher find only one study has relation with this study, after that’s his foxing for Theoretical framework Indicators , the third part of this study talks about (research procedures), and then rely to Descriptive analytical method to analysis The samples, (4) (50%) Of the total (8) samples according to goal of research. Then find some Results Including:
1- The Alienation form can found it in the movement of snack like (1, 4) (50%), this type of cloud is characterized by giving manifestation physically and aesthetically distinct.
2- The Alienation form lobular Heart pinned like form (1, 2, 3) (75%).this type used for Repetition property.
3- The ornament’s cloud makes inverse rotation Organize like (S) letter in English (3) (25%).
4-The ornament’s cloud makes Free regulation (1, 3) (50%). This Organize has Diversity design, because Get rid of the monotony, to give the ornament’s clouds Exciting and attract the attention.
The Conclusions Including:
1- Employ the decorative for floral decorations Design, to add new decorative Reflect Functional and aesthetic results.
2- The Alienation form gives many design options to make good forms Compatible with Core Area. After the Conclusions, the researcher talks about Recommendations and suggestions
Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the
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